Duration
@@ -81,11 +81,11 @@
Exporting Query ResultsA maximum of 1000 records can be displayed in the query result on the console. To view more or all data, you can export the data to OBS. The procedure is as follows:
You can export results on the SQL Jobs page or the SQL Editor page.
- On the Job Management > SQL Jobs page, you can click More > Export Result in the Operation column to export the query result.
- After the query statements are successfully executed on the SQL Editor page, click
 next to the View Result tab page to export query results.
-  If no column of the numeric type is displayed in the query result, the result cannot be exported.
+ If there are no numerical columns in the query results, job results cannot be exported.
- Table 2 Exporting parametersParameter
+Table 2 ParametersParameter
|
Description
|
@@ -98,13 +98,13 @@
|---|
Queues
|
-The queue where the jobs are executed. SQL jobs can be executed only in SQL queues. For details about how to create a queue, see Creating a Queue.
+ | The queue where the jobs are executed. SQL jobs can only be executed on SQL queues. For details about how to create a queue, see Creating a Queue.
|
Compression Format
|
-Compression format of the data to be exported. The following options are supported:
-
+ | Compression format of the data to be exported. The options are:
+
|
Storage Path
diff --git a/docs/dli/umn/dli_01_0019.html b/docs/dli/umn/dli_01_0019.html
index 615a5f4c..cf8a514c 100644
--- a/docs/dli/umn/dli_01_0019.html
+++ b/docs/dli/umn/dli_01_0019.html
@@ -30,7 +30,7 @@
| Tag value
|
You can perform the following operations:
-- Click the text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Click the text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
|
diff --git a/docs/dli/umn/dli_01_0022.html b/docs/dli/umn/dli_01_0022.html
index a13e448d..c4ab9648 100644
--- a/docs/dli/umn/dli_01_0022.html
+++ b/docs/dli/umn/dli_01_0022.html
@@ -29,7 +29,7 @@
Tag value
|
You can specify the tag value in either of the following ways:
-- Click the text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Click the text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
|
diff --git a/docs/dli/umn/dli_01_0253.html b/docs/dli/umn/dli_01_0253.html
index 2ba7e5e2..5efbeac4 100644
--- a/docs/dli/umn/dli_01_0253.html
+++ b/docs/dli/umn/dli_01_0253.html
@@ -7,7 +7,7 @@
PrerequisitesThe data to be imported has been stored on OBS.
Procedure- You can import data on either the Data Management page or the SQL Editor page.
- To import data on the Data Management page:
- On the left of the management console, choose Data Management > Databases and Tables.
- Click the name of the database corresponding to the table where data is to be imported to switch to the table management page.
- Locate the row where the target table resides and choose More > Import in the Operation column. The Import dialog box is displayed.
- - To import data on the SQL Editor page:
- On the left of the management console, click SQL Editor.
- In the navigation tree on the left of SQL Editor, click Databases to see all databases. Click the database where the target table belongs. The table list is displayed.
- Click
 on the right of the table and choose Import from the shortcut menu. The Import page is displayed.
+ - To import data on the SQL Editor page:
- On the left of the management console, click SQL Editor.
- In the navigation tree on the left of SQL Editor, click Databases to see all databases. Click the database where the target table belongs. The table list is displayed.
- Click on the right of the table and choose Import from the shortcut menu. The Import page is displayed.
- In the Import dialog box, set the parameters based on Table 1.
@@ -49,8 +49,8 @@
Path
|
-You can directly enter a path or click  and select an OBS path. If no bucket is available, you can directly switch to the OBS management console and create an OBS bucket.
-- When creating an OBS table, you must specify a folder as the directory. If a file is specified, data import may be failed.
- If a folder and a file have the same name in the OBS directory, the file path is preferred as the path of the data to be imported.
+ | You can directly enter a path or click and select an OBS path. If no bucket is available, you can directly switch to the OBS management console and create an OBS bucket.
+- When creating an OBS table, you must specify a folder as the directory. If a file is specified, data import may be failed.
- If a folder and a file have the same name in the OBS directory, the file path is preferred as the path of the data to be imported.
NOTE: The path can be a file or folder.
|
@@ -121,7 +121,7 @@
Click OK.You can view the imported data in either of the following ways: Currently, only the first 10 records are displayed.
-- Choose Data Management > Databases and Tables in the navigation pane of the console. Locate the row that contains the database where the target table belongs and click More > View Properties in the Operation column. In the displayed dialog box, click the Preview tab to view the imported data.
- In the Databases tab of the SQL Editor, click the database name to go to the table list. Click
 on the right of a table name and choose View Properties from the shortcut menu. In the displayed dialog box, click Preview to view the imported data.
+- Choose Data Management > Databases and Tables in the navigation pane of the console. Locate the row that contains the database where the target table belongs and click More > View Properties in the Operation column. In the displayed dialog box, click the Preview tab to view the imported data.
- On the Databases tab of the SQL Editor, click the database name to go to the table list. Click on the right of a table name and choose View Properties from the shortcut menu. In the displayed dialog box, click Preview to view the imported data.
(Optional) View the status and execution result of the importing job on the Job Management > SQL Jobs page.
diff --git a/docs/dli/umn/dli_01_0320.html b/docs/dli/umn/dli_01_0320.html
index a48a40c4..8cddb3ff 100644
--- a/docs/dli/umn/dli_01_0320.html
+++ b/docs/dli/umn/dli_01_0320.html
@@ -10,7 +10,7 @@
On the OBS console, you can configure lifecycle rules for a bucket to periodically delete objects in it or change object storage classes.
- SQL statements can be executed in batches on the SQL editor page.
-- Commonly used keyworks in the job editing window are highlighted in different colors.
- Both single-line comment and multi-line comment are allowed. Use two consecutive hyphens (--) in each line to comment your statements.
+- Commonly used syntax in the job editing window is highlighted in different colors.
- Both single-line comment and multi-line comment are allowed. Use two consecutive hyphens (--) in each line to comment your statements.
Navigation paneThe navigation pane on the left consists of Databases, Queues, and Templates tabs.
@@ -49,10 +49,10 @@
SQL Editing WindowSQL job editing window is displayed in the upper right part of the page.
+ SQL Editing WindowSQL job editing window is displayed in the upper right part of the page. For details about the parameters, see Table 2.
The SQL statement editing area is below the operation bar. For details about keyboard shortcuts, see Table 3.
- Table 2 Components of the SQL job editing windowNo.
+Table 2 Components of the SQL job editing windowNo.
|
Button & Drop-Down List
|
@@ -65,7 +65,7 @@
Queues
|
Select a queue from the drop-down list box. If no queue is available, the default queue is displayed. Refer to Creating a Queue and create a queue.
-SQL jobs can be executed only on SQL queues.
+SQL jobs can only be executed on SQL queues.
|
|---|
3
@@ -189,7 +189,7 @@
- View Result
-
Table 5 Operations in the result tabOperation
+Table 5 Operations on the result tabOperation
|
Description
|
@@ -205,16 +205,16 @@
Click  to view the query result in a chart or table.
|
|---|
-Export the result
+ | Export job results
|
-Export the job execution results to the created OBS bucket. For details, see SQL Job Management.
+ | Export the job execution results to the created OBS bucket.
|
SQL Query Procedure- Log in to the DLI management console. On the page displayed, choose Job Management > SQL Jobs. On the page displayed, click Create Job.
On the SQL editor page, the system prompts you to create an OBS bucket to store temporary data generated by DLI jobs. In the Set Job Bucket dialog box, click Setting. On the page displayed, click the edit button in the upper right corner of the job bucket card. In the Set Job Bucket dialog box displayed, enter the job bucket path and click OK.
+ SQL Query Procedure- Log in to the DLI management console. On the page displayed, choose Job Management > SQL Jobs. On the page displayed, click Create Job.
On the SQL editor page, the system prompts you to create an OBS bucket to store temporary data generated by DLI jobs. In the Set Job Bucket dialog box, click Setting. On the page displayed, click the edit button in the upper right corner of the job bucket card. In the Set Job Bucket dialog box displayed, enter the job bucket path and click OK.
- Select a queue from the queue list in the upper left corner of the SQL job editing window. For details about how to create a queue, see Creating a Queue.
- In the upper right corner of the SQL job editing window, select a database, for example, qw, from the Databases drop-down list.
- Create a table, for example, qw. For details about how to create a database and table, see Creating a Database or a Table.
- In the SQL job editing window, enter the following SQL statement:
| SELECT * FROM qw.qw LIMIT 10;
|
diff --git a/docs/dli/umn/dli_01_0363.html b/docs/dli/umn/dli_01_0363.html
index 1fb0600d..4100a31b 100644
--- a/docs/dli/umn/dli_01_0363.html
+++ b/docs/dli/umn/dli_01_0363.html
@@ -8,53 +8,53 @@
- To create a queue on the SQL Editor page:
- In the navigation pane of the DLI management console, click SQL Editor.
- Click Queues. On the tab page displayed, click
 on the right to create a queue.
- On the Create Queue page displayed, set the parameters according to Table 1.
-
Table 1 ParametersParameter
+Table 1 ParametersParameter
|
-Description
+ | Description
|
|---|
-Name
+ | Name
|
-Name of a queue.
+ | Name of a queue.
- The queue name can contain only digits, letters, and underscores (_), but cannot contain only digits, start with an underscore (_), or be left unspecified.
- The length of the name cannot exceed 128 characters.
NOTE: The queue name is case-insensitive. Uppercase letters will be automatically converted to lowercase letters.
|
-Type
+ | Type
|
-- For SQL: compute resources used for SQL jobs.
- For general purpose: compute resources used for Spark and Flink jobs.
NOTE: Selecting Dedicated Resource Mode enables you to create a dedicated queue. Enhanced datasource connections can only be created for dedicated queues.
+ - For SQL: compute resources used for SQL jobs.
- For general purpose: compute resources used for Spark and Flink jobs.
NOTE: Selecting Dedicated Resource Mode enables you to create a dedicated queue. Enhanced datasource connections can only be created for dedicated queues.
|
|
-Specifications
+ | Specifications
|
-The compute nodes' total number of CUs. One CU equals one vCPU and 4 GB of memory. DLI automatically assigns CPU and memory resources to each compute node, and the client does not need to know how many compute nodes are being used.
+ | The compute nodes' total number of CUs. One CU equals one vCPU and 4 GB of memory. DLI automatically assigns CPU and memory resources to each compute node, and the client does not need to know how many compute nodes are being used.
|
-Description
+ | Description
|
-Description of the queue to be created. The description can contain a maximum of 128 characters.
+ | Description of the queue to be created. The description can contain a maximum of 128 characters.
|
-Advanced Settings
+ | Advanced Settings
|
-In the Queue Type area, select Dedicated Resource Mode and then click Advanced Settings. - Default: The system automatically configures the parameter.
- Custom
CIDR Block: You can specify the CIDR block. For details, see Modifying the CIDR Block. If DLI enhanced datasource connection is used, the CIDR block of the DLI queue cannot overlap with that of the data source.
+In the Queue Type area, select Dedicated Resource Mode and then click Advanced Settings. - Default: The system automatically configures the parameter.
- Custom
CIDR Block: You can specify the CIDR block. For details, see Modifying the CIDR Block. If DLI enhanced datasource connection is used, the CIDR block of the DLI queue cannot overlap with that of the data source.
Queue Type: When running an AI-related SQL job, select AI-enhanced. When running other jobs, select Basic.
|
|
-Tags
+ | Tags
|
-Tags used to identify cloud resources. A tag includes the tag key and tag value. If you want to use the same tag to identify multiple cloud resources, that is, to select the same tag from the drop-down list box for all services, you are advised to create predefined tags on the Tag Management Service (TMS).
+ | Tags used to identify cloud resources. A tag includes the tag key and tag value. If you want to use the same tag to identify multiple cloud resources, that is, to select the same tag from the drop-down list box for all services, you are advised to create predefined tags on the Tag Management Service (TMS).
NOTE: - A maximum of 20 tags can be added.
- Only one tag value can be added to a tag key.
- The key name in each resource must be unique.
- Tag key: Enter a tag key name in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
- - Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
|
diff --git a/docs/dli/umn/dli_01_0367.html b/docs/dli/umn/dli_01_0367.html
index 8c80f04d..e4bb90f6 100644
--- a/docs/dli/umn/dli_01_0367.html
+++ b/docs/dli/umn/dli_01_0367.html
@@ -47,7 +47,7 @@
- Tag key: Enter a tag key name in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
-- Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
diff --git a/docs/dli/umn/dli_01_0376.html b/docs/dli/umn/dli_01_0376.html
index 1632ded9..b4821638 100644
--- a/docs/dli/umn/dli_01_0376.html
+++ b/docs/dli/umn/dli_01_0376.html
@@ -3,7 +3,7 @@
Modifying the Owners of Databases and Tables
During actual use, developers create databases and tables and submit them to test personnel for testing. After the test is complete, the databases and tables are transferred to O&M personnel for user experience. In this case, you can change the owner of the databases and tables to transfer data to other owners.
Modifying the Database OwnerYou can change the owner of a database on either the Data Management page or the SQL Editor page. - On the Data Management page, change the database owner.
- On the left of the management console, choose Data Management > Databases and Tables.
- On the Databases and Tables page, locate the database you want and click More > Modify Database in the Operation column.
- In the displayed dialog box, enter a new owner name (an existing username) and click OK.
- - Change the database owner on the SQL Editor page.
- On the left of the management console, click SQL Editor.
- In the navigation tree on the left, click Databases, click
 on the right of the database you want to modify, and choose Modify Database from the shortcut menu. - In the displayed dialog box, enter a new owner name (an existing username) and click OK.
+ - Change the database owner on the SQL Editor page.
- On the left of the management console, click SQL Editor.
- In the navigation tree on the left, click Databases, click on the right of the database you want to modify, and choose Modify Database from the shortcut menu.
- In the displayed dialog box, enter a new owner name (an existing username) and click OK.
diff --git a/docs/dli/umn/dli_01_0378.html b/docs/dli/umn/dli_01_0378.html
index 5af837a1..c4ef4d49 100644
--- a/docs/dli/umn/dli_01_0378.html
+++ b/docs/dli/umn/dli_01_0378.html
@@ -6,12 +6,61 @@
FunctionsYou can query and analyze heterogeneous data sources such as RDS, and GaussDB(DWS) on the cloud using access methods, such as visualized interface, RESTful API, JDBC, and Beeline. The data format is compatible with five mainstream data formats: CSV, JSON, Parquet, and ORC.
- Basic functions
- You can use standard SQL statements to query in SQL jobs.
- Flink jobs support Flink SQL online analysis. Aggregation functions such as Window and Join, geographic functions, and CEP functions are supported. SQL is used to express service logic, facilitating service implementation.
- For spark jobs, fully-managed Spark computing can be performed. You can submit computing tasks through interactive sessions or in batch to analyze data in the fully managed Spark queues.
- - Federated analysis of heterogeneous data sources
- Spark datasource connection: Data sources such as DWS, RDS, and CSS can be accessed through DLI.
- Interconnection with multiple cloud services is supported in Flink jobs to form a rich stream ecosystem. The DLI stream ecosystem consists of cloud service ecosystems and open source ecosystems.
- Cloud service ecosystem: DLI can interconnect with other services in Flink SQL. You can directly use SQL to read and write data from cloud services.
- Open-source ecosystems: After connections to other VPCs are established through datasource connections, you can access all data sources and output targets (such as Kafka, HBase, and Elasticsearch) supported by Flink and Spark in your dedicated DLI queue.
+ - Federated analysis of heterogeneous data sources
- Spark datasource connection: Data sources such as GaussDB(DWS), RDS, and CSS can be accessed through DLI.
- Interconnection with multiple cloud services is supported in Flink jobs to form a rich stream ecosystem. The DLI stream ecosystem consists of cloud service ecosystems and open source ecosystems.
- Cloud service ecosystem: DLI can interconnect with other services in Flink SQL. You can directly use SQL to read and write data from cloud services.
- Open-source ecosystems: After connections to other VPCs are established through datasource connections, you can access all data sources and output targets (such as Kafka, HBase, and Elasticsearch) supported by Flink and Spark in your dedicated DLI queue.
- Storage-compute decoupling
DLI is interconnected with OBS for data analysis. In this architecture where storage and compute are decoupled, resources of these two types are charged separately, helping you reduce costs and improving resource utilization.
You can choose single-AZ or multi-AZ storage when you create an OBS bucket for storing redundant data on the DLI console. The differences between the two storage policies are as follows:
- Multi-AZ storage means data is stored in multiple AZs, improving data reliability. If the multi-AZ storage is enabled for a bucket, data is stored in multiple AZs in the same region. If one AZ becomes unavailable, data can still be properly accessed from the other AZs. The multi-AZ storage is ideal for scenarios that demand high reliability. You are advised to use this policy.
- Single-AZ storage means that data is stored in a single AZ, with lower costs.
+ - Elastic resource pool
Elastic resource pools support the CCE cluster architecture for heterogeneous resources so you can centrally manage and allocate them. For details, see Elastic Resource Pool.
+Elastic resource pools have the following advantages:
+- Unified management
- You can manage multiple internal clusters and schedule jobs. You can manage millions of cores for compute resources.
- Elastic resource pools can be deployed across multiple AZs to support high availability.
+ - Tenant resource isolation
Resources of different queues are isolated to reduce the impact on each other.
+ - Shared access and flexibility
- Minute-level scaling helps you to handle request peaks.
- Queue priorities and CU quotas can be set at different time to improve resource utilization.
+ - Job-level isolation (supported in later versions)
SQL jobs can run on independent Spark instances, reducing mutual impacts between jobs.
+ - Automatic scaling (supported in later versions)
The queue quota is updated in real time based on workload and priority.
+
+Using elastic resource pools has the following advantages.
+
+Advantage
+ |
+No Elastic Resource Pool
+ |
+Use Elastic Resource Pool
+ |
+
|---|
+
+Efficiency
+ |
+You need to set scaling tasks repeatedly to improve the resource utilization.
+ |
+Dynamic scaling can be done in seconds.
+ |
+
+Resource utilization
+
+ |
+Resources cannot be shared among different queues.
+For example, a queue has idle CUs and another queue is heavily loaded. Resources cannot be shared. You can only scale up the second queue.
+ |
+Queues added to the same elastic resource pool can share compute resources.
+ |
+
+When you set a data source, you must allocate different network segments to each queue, which requires a large number of VPC network segments.
+ |
+You can add multiple general-purpose queues in the same elastic resource pool to one network segment, simplifying the data source configuration.
+ |
+
+Resource allocation
+ |
+If resources are insufficient for scale-out tasks of multiple queues, some queues will fail to be scaled out.
+ |
+You can set the priority for each queue in the elastic resource pool based on the peak hours to ensure proper resource allocation.
+ |
+
+
+
+
DLI Core Engine: Spark+Flink- Spark is a unified analysis engine that is ideal for large-scale data processing. It focuses on query, compute, and analysis. DLI optimizes performance and reconstructs services based on open-source Spark. It is compatible with the Apache Spark ecosystem and interfaces, and improves performance by 2.5x when compared with open-source Spark. In this way, DLI enables you to perform query and analysis of EB's of data within hours.
- Flink is a distributed compute engine that is ideal for batch processing, that is, for processing static data sets and historical data sets. You can also use it for stream processing, that is, processing real-time data streams and generating data results in real time. DLI enhances features and security based on the open-source Flink and provides the Stream SQL feature required for data processing.
diff --git a/docs/dli/umn/dli_01_0384.html b/docs/dli/umn/dli_01_0384.html
index aaa00c55..27f7efa0 100644
--- a/docs/dli/umn/dli_01_0384.html
+++ b/docs/dli/umn/dli_01_0384.html
@@ -5,11 +5,11 @@
On the Overview page, click Create Job in the upper right corner of the Spark Jobs tab or click Create Job in the upper right corner of the Spark Jobs page. The Spark job editing page is displayed.
On the Spark job editing page, a message is displayed, indicating that a temporary DLI data bucket will be created. The created bucket is used to store temporary data generated by DLI, such as job logs and job results. You cannot view job logs if you choose not to create it. The bucket will be created and the default bucket name is used.
If you do not need to create a DLI temporary data bucket and do not want to receive this message, select Do not show again and click Cancel.
- Prerequisites- You have uploaded the dependencies to the corresponding OBS bucket on the Data Management > Package Management page. For details, see Creating a Package.
- Before creating a Spark job to access other external data sources, such as OpenTSDB, HBase, Kafka, GaussDB(DWS), RDS, CSS, CloudTable, DCS Redis, and DDS, you need to create a cross-source connection to enable the network between the job running queue and external data sources.
- For details about the external data sources that can be accessed by Spark jobs, see Cross-Source Analysis Development Methods.
- For details about how to create a datasource connection, see Enhanced Datasource Connections.
On the Resources > Queue Management page, locate the queue you have created, and choose More > Test Address Connectivity in the Operation column to check whether the network connection between the queue and the data source is normal. For details, see Testing Address Connectivity.
+Prerequisites- You have uploaded the dependencies to the corresponding OBS bucket on the Data Management > Package Management page. For details, see Creating a Package.
- Before creating a Spark job to access other external data sources, such as OpenTSDB, HBase, Kafka, GaussDB(DWS), RDS, CSS, CloudTable, DCS Redis, and DDS, you need to create a datasource connection to enable the network between the job running queue and external data sources.
Procedure- In the left navigation pane of the DLI management console, choose > . The Spark Jobs page is displayed.
Click Create Job in the upper right corner. In the job editing window, you can set parameters in Fill Form mode or Write API mode.
+Procedure- In the left navigation pane of the DLI management console, choose > . The Spark Jobs page is displayed.
Click Create Job in the upper right corner. In the job editing window, you can set parameters in Fill Form mode or Write API mode.
The following uses the Fill Form as an example. In Write API mode, refer to the Data Lake Insight API Reference for parameter settings.
- Select a queue.
Select the queue you want to use from the drop-down list box.
- Configure the job.
Configure job parameters by referring to Table 1.
@@ -29,6 +29,7 @@
Select the package to be executed. The value can be .jar or .py.
You can select the name of a JAR or pyFile package that has been uploaded to the DLI resource management system. You can also specify an OBS path, for example, obs://Bucket name/Package name.
+Spark 3.3.x or later supports only packages in OBS paths.
|
Main Class (--class)
diff --git a/docs/dli/umn/dli_01_0403.html b/docs/dli/umn/dli_01_0403.html
index bf55a6e3..5caf870f 100644
--- a/docs/dli/umn/dli_01_0403.html
+++ b/docs/dli/umn/dli_01_0403.html
@@ -6,74 +6,64 @@
- Flink SQL uses SQL statements to define jobs and can be submitted to any general purpose queue.
- Flink Jar customizes a JAR package job based on Flink APIs. It runs on dedicated queues.
Flink job management provides the following functions:
-Assigning Agency PermissionsAgencies are required for DLI to execute Flink jobs. You can set the agency when logging in to the management console for the first time or go to Global Configurations > Service Authorization to modify the agencies.
- The permissions are as follows:
- - Tenant Administrator (global) permissions are required to access data from OBS to execute Flink jobs on DLI, for example, obtaining OBS/GaussDB(DWS) data sources, log dump (including bucket authorization), checkpointing enabling, and job import and export.
Due to cloud service cache differences, permission setting operations require about 60 minutes to take effect.
-
- - DIS Administrator permissions are required to use DIS data as the data source of DLI Flink jobs.
Due to cloud service cache differences, permission setting operations require about 30 minutes to take effect.
-
- - To use CloudTable data as the data source of DLI Flink jobs, CloudTable Administrator permissions are required.
Due to cloud service cache differences, permission setting operations require about 3 minutes to take effect.
-
-
- Flink Jobs PageOn the Overview page, click Flink Jobs to go to the Flink job management page. Alternatively, you can choose Job Management > Flink Jobs from the navigation pane on the left. The page displays all Flink jobs. If there are a large number of jobs, they will be displayed on multiple pages. DLI allows you to view jobs in all statuses.
- Table 1 Job management parametersParameter
+Table 1 Job management parametersParameter
|
-Description
+ | Description
|
|---|
-ID
+ | ID
|
-ID of a submitted Flink job, which is generated by the system by default.
+ | ID of a submitted Flink job, which is generated by the system by default.
|
-Name
+ | Name
|
-Name of the submitted Flink job.
+ | Name of the submitted Flink job.
|
-Type
+ | Type
|
-Type of the submitted Flink job. Including:
+ | Type of the submitted Flink job. Including:
- Flink SQL: Flink SQL jobs
- Flink Jar: Flink Jar jobs
|
-Status
+ | Status
|
-Job statuses, including:
+ | Job statuses, including:
- Draft
- Submitting
- Submission failed
- Running: After the job is submitted, a normal result is returned.
- Running exception: The job stops running due to an exception.
- Downloading
- Idle
- Stopping
- Stopped
- Stopping failed
- Creating the savepoint
- Completed
|
-Description
+ | Description
|
-Description of the submitted Flink job.
+ | Description of the submitted Flink job.
|
-Username
+ | Username
|
-Name of the user who submits a job.
+ | Name of the user who submits a job.
|
-Created
+ | Created
|
-Time when a job is created.
+ | Time when a job is created.
|
-Started
+ | Started
|
-Time when a Flink job starts to run.
+ | Time when a Flink job starts to run.
|
-Duration
+ | Duration
|
-Time consumed by job running.
+ | Time consumed by job running.
|
-Operation
+ | Operation
|
-- Edit: Edit a created job. For details, see Editing a Job.
- Start: Start and run a job. For details, see Starting a Job.
- More
- FlinkUI: After you click this button, the Flink job execution page is displayed.
NOTE: When you execute a job on a created queue, the cluster is restarted. It takes about 10 minutes. If you click FlinkUI before the cluster is created, an empty projectID will be cached. The FlinkUI page cannot be displayed.
+ - Edit: Edit a created job. For details, see Editing a Job.
- Start: Start and run a job. For details, see Starting a Job.
- More
- FlinkUI: After you click this button, the Flink job execution page is displayed.
NOTE: When you execute a job on a created queue, the cluster is restarted. It takes about 10 minutes. If you click FlinkUI before the cluster is created, an empty projectID will be cached. The FlinkUI page cannot be displayed.
You are advised to use a dedicated queue so that the cluster will not be released. Alternatively, wait for a while after the job is submitted (the cluster is created), and then check FlinkUI.
- Stop: Stop a Flink job. If this function is unavailable, jobs in the current status cannot be stopped.
- Delete: Delete a job.
NOTE: A deleted job cannot be restored.
diff --git a/docs/dli/umn/dli_01_0410.html b/docs/dli/umn/dli_01_0410.html
index 8b788b4a..810edd3c 100644
--- a/docs/dli/umn/dli_01_0410.html
+++ b/docs/dli/umn/dli_01_0410.html
@@ -119,7 +119,7 @@
√
|
|
|
-RDS MySQL
+ | RDS for MySQL
|
√
|
diff --git a/docs/dli/umn/dli_01_0418.html b/docs/dli/umn/dli_01_0418.html
index 6786c04b..cd6d3aea 100644
--- a/docs/dli/umn/dli_01_0418.html
+++ b/docs/dli/umn/dli_01_0418.html
@@ -2,7 +2,7 @@
Creating an IAM User and Granting Permissions
You can use Identity and Access Management (IAM) to implement fine-grained permissions control on DLI resources. For details, see Overview.
- If your cloud account does not need individual IAM users, then you may skip over this chapter.
+ If your cloud account does not need individual IAM users, then you may skip over this section.
This section describes how to create an IAM user and grant DLI permissions to the user. Figure 1 shows the procedure.
PrerequisitesBefore assigning permissions to user groups, you should learn about system policies and select the policies based on service requirements. For details about system permissions supported by DLI, see DLI System Permissions.
@@ -12,7 +12,7 @@
- Create a user group and grant the permission to it.
Create a user group on the IAM console, and assign the DLI ReadOnlyAccess permission to the group.
- Create a user and add the user to the user group.
Create a user on the IAM console and add the user to the group created in 1.
- Log in and verify the permission.
Log in to the management console using the newly created user, and verify that the user's permissions.
-- Choose Service List > Data Lake Insight. The DLI management console is displayed. If you can view the queue list on the Queue Management page but cannot buy DLI queues by clicking Buy Queue in the upper right corner (assume that the current permission contains only DLI ReadOnlyAccess), the DLI ReadOnlyAccess permission has taken effect.
- Choose any other service in Service List. If a message appears indicating that you have insufficient permissions to access the service, the DLI ReadOnlyAccess permission has already taken effect.
+- Choose Service List > Data Lake Insight. The DLI management console is displayed. If you can view the queue list on the Queue Management page but cannot buy DLI queues by clicking Buy Queue in the upper right corner (assume that the current permission contains only DLI ReadOnlyAccess), the DLI ReadOnlyAccess permission has taken effect.
- Choose any other service in Service List. If a message appears indicating that you have insufficient permissions to access the service, the DLI ReadOnlyAccess permission has already taken effect.
DLI has a comprehensive permission control mechanism and supports fine-grained authentication through Identity and Access Management (IAM). You can create policies in IAM to manage DLI permissions. You can use both the DLI's permission control mechanism and the IAM service for permission management.
Application Scenarios of IAM AuthenticationWhen using DLI on the cloud, enterprise users need to manage DLI resources (queues) used by employees in different departments, including creating, deleting, using, and isolating resources. In addition, data of different departments needs to be managed, including data isolation and sharing.
DLI uses IAM for refined enterprise-level multi-tenant management. IAM provides identity authentication, permissions management, and access control, helping you securely access to your cloud resources.
- With IAM, you can use your cloud account to create IAM users for your employees, and assign permissions to the users to control their access to specific resource types. For example, some software developers in your enterprise need to use DLI resources but must not delete them or perform any high-risk operations. To achieve this result, you can create IAM users for the software developers and grant them only the permissions required for using DLI resources.
+ With IAM, you can use your account to create IAM users for your employees, and assign permissions to the users to control their access to specific resource types. For example, some software developers in your enterprise need to use DLI resources but must not delete them or perform any high-risk operations. To achieve this result, you can create IAM users for the software developers and grant them only the permissions required for using DLI resources.
For a new user, you need to log in for the system to record the metadata before using DLI.
- IAM is free of charge. You pay only for the resources you use.
- If your cloud account does not need individual IAM users for permissions management, skip this chapter.
+ IAM is free to use, and you only need to pay for the resources in your account.
+ If your account does not need individual IAM users for permissions management, skip over this section.
DLI System PermissionsTable 1 lists all the system-defined roles and policies supported by DLI.
Type: There are roles and policies. - Roles: A type of coarse-grained authorization mechanism that defines permissions related to user responsibilities. Only a limited number of service-level roles are available. When using roles to grant permissions, you also need to assign other roles on which the permissions depend. However, roles are not an ideal choice for fine-grained authorization and secure access control.
- Policies: A type of fine-grained authorization mechanism that defines permissions required to perform operations on specific cloud resources under certain conditions. This mechanism allows for more flexible policy-based authorization, meeting requirements for secure access control. For example, you can grant DLI users only the permissions for managing a certain type of ECSs.
@@ -156,7 +156,7 @@
ExamplesAn Internet company mainly provides game and music services. DLI is used to analyze user behaviors and assist decision making.
- As shown in Figure 1, the Leader of the Basic Platform Team has applied for a Tenant Administrator account to manage and use cloud services. The Leader of the Basic Platform Team creates a subaccount with the DLI Service Administrator permission to manage and use DLI, as the Big Data Platform Team requires DLI for data analysis. The Leader of the Basic Platform Team creates a Queue A and assigns it to Data Engineer A to analyze the gaming data. A Queue B is also assigned to Data Engineer B to analyze the music data. Besides granting the queue usage permission, the Leader of the Basic Platform Team grants data (except the database) management and usage permissions to the two engineers.
+ As shown in Figure 1, the Leader of the Basic Platform Team has applied for a Tenant Administrator account to manage and use cloud services. The Leader of the Basic Platform Team creates a subaccount with the DLI Service Administrator permission to manage and use DLI, as the Big Data Platform Team requires DLI for data analysis. The Leader of the Basic Platform Team creates a Queue A and assigns it to Data Engineer A to analyze the gaming data. A Queue B is also assigned to Data Engineer B to analyze the music data. Besides granting the queue usage permission, the Leader of the Basic Platform Team grants data (except the database) management and usage permissions to the two engineers.
Figure 1 Granting permissions
The Data Engineer A creates a table named gameTable for storing game prop data and a table named userTable for storing game user data. The music service is a new service. To explore potential music users among existing game users, the Data Engineer A assigns the query permission on the userTable to the Data Engineer B. In addition, Data Engineer B creates a table named musicTable for storing music copyrights information.
Table 3 describes the queue and data permissions of Data Engineer A and Data Engineer B.
diff --git a/docs/dli/umn/dli_01_0441.html b/docs/dli/umn/dli_01_0441.html
index 65511366..d649fdf6 100644
--- a/docs/dli/umn/dli_01_0441.html
+++ b/docs/dli/umn/dli_01_0441.html
@@ -3,585 +3,601 @@
Common Operations Supported by DLI System Policy
Table 1 lists the common operations supported by each system policy of DLI. Choose proper system policies according to this table. For details about the SQL statement permission matrix in DLI in terms of permissions on databases, tables, and roles, see SQL Syntax of Batch Jobs > Data Permissions Management > Data Permissions List in the Data Lake Insight SQL Syntax Reference.
- Table 1 Common operations supported by each system policyResources
+Table 1 Common operations supported by each system permissionResource
|
-Operation
+ | Operation
|
-Description
+ | Description
|
-DLI FullAccess
+ | DLI FullAccess
|
-DLI ReadOnlyAccess
+ | DLI ReadOnlyAccess
|
-Tenant Administrator
+ | Tenant Administrator
|
-DLI Service Administrator
+ | DLI Service Administrator
|
|---|
-Queue
+ | Queue
|
-DROP_QUEUE
+ | DROP_QUEUE
|
-Deleting a queue
+ | Deleting a Queue
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SUBMIT_JOB
+ | SUBMIT_JOB
|
-Submitting the job
+ | Submitting a job
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-CANCEL_JOB
+ | CANCEL_JOB
|
-Terminating the job
+ | Terminating a Job
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-RESTART
+ | RESTART
|
-Restarting a queue
+ | Restarting a queue
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-GRANT_PRIVILEGE
+ | GRANT_PRIVILEGE
|
-Granting permissions to the queue
+ | Granting permissions to a queue
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-REVOKE_PRIVILEGE
+ | REVOKE_PRIVILEGE
|
-Revoking permissions from the queue
+ | Revoking permissions to a queue
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SHOW_PRIVILEGES
+ | SHOW_PRIVILEGES
|
-Viewing the queue permissions of other users
+ | Viewing the queue permissions of other users
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-Database
+ | Database
|
-DROP_DATABASE
+ | DROP_DATABASE
|
-Deleting a database
+ | Deleting a database
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-CREATE_TABLE
+ | CREATE_TABLE
|
-Creating a table
+ | Creating a table
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-CREATE_VIEW
+ | CREATE_VIEW
|
-Creating a view
+ | Creating a view
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-EXPLAIN
+ | EXPLAIN
|
-Explaining the SQL statement as an execution plan
+ | Explaining the SQL statement as an execution plan
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-CREATE_ROLE
+ | CREATE_ROLE
|
-Creating a role
+ | Creating a role
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-DROP_ROLE
+ | DROP_ROLE
|
-Deleting a role
+ | Deleting a role
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SHOW_ROLES
+ | SHOW_ROLES
|
-Displaying a role
+ | Displaying a role
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-GRANT_ROLE
+ | GRANT_ROLE
|
-Binding a role
+ | Binding a role
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-REVOKE_ROLE
+ | REVOKE_ROLE
|
-Unbinding the role
+ | Unbinding a role
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SHOW_USERS
+ | SHOW_USERS
|
-Displaying the binding relationships between all roles and users
+ | Displaying the binding relationships between all roles and users
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-GRANT_PRIVILEGE
+ | GRANT_PRIVILEGE
|
-Granting permissions to the database
+ | Granting permissions to the database
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-REVOKE_PRIVILEGE
+ | REVOKE_PRIVILEGE
|
-Revoking permissions to the database
+ | Revoking permissions to the database
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SHOW_PRIVILEGES
+ | SHOW_PRIVILEGES
|
-Viewing database permissions of other users
+ | Viewing database permissions of other users
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-DISPLAY_ALL_TABLES
+ | DISPLAY_ALL_TABLES
|
-Displaying tables in the database
+ | Displaying tables in a database
|
-√
+ | √
|
-√
+ | √
|
-√
+ | √
|
-√
+ | √
|
-DISPLAY_DATABASE
+ | DISPLAY_DATABASE
|
-Displaying databases
+ | Displaying databases
|
-√
+ | √
|
-√
+ | √
|
-√
+ | √
|
-√
+ | √
|
-CREATE_FUNCTION
+ | CREATE_FUNCTION
|
-Creating a function
+ | Creating a function
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-DROP_FUNCTION
+ | DROP_FUNCTION
|
-Deleting a function
+ | Deleting a function
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SHOW_FUNCTIONS
+ | SHOW_FUNCTIONS
|
-Displaying all functions
+ | Displaying all functions
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-DESCRIBE_FUNCTION
+ | DESCRIBE_FUNCTION
|
-Displaying function details
+ | Displaying function details
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-Table
+ | Table
|
-DROP_TABLE
+ | DROP_TABLE
|
-Deleting a table
+ | Deleting tables
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SELECT
+ | SELECT
|
-Querying a table
+ | Querying tables
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-INSERT_INTO_TABLE
+ | INSERT_INTO_TABLE
|
-Inserting
+ | Inserting table data
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-ALTER_TABLE_ADD_COLUMNS
+ | ALTER_TABLE_ADD_COLUMNS
|
-Adding a column
+ | Adding a column
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-INSERT_OVERWRITE_TABLE
+ | INSERT_OVERWRITE_TABLE
|
-Rewriting
+ | Overwriting a table
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-ALTER_TABLE_RENAME
+ | ALTER_TABLE_RENAME
|
-Renaming a table
+ | Renaming a table
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-ALTER_TABLE_ADD_PARTITION
+ | ALTER_TABLE_ADD_PARTITION
|
-Adding partitions to the partition table
+ | Adding partitions to the partition table
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-ALTER_TABLE_RENAME_PARTITION
+ | ALTER_TABLE_RENAME_PARTITION
|
-Renaming a table partition
+ | Renaming a table partition
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-ALTER_TABLE_DROP_PARTITION
+ | ALTER_TABLE_DROP_PARTITION
|
-Deleting partitions from a partition table
+ | Deleting partitions from a partition table
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SHOW_PARTITIONS
+ | SHOW_PARTITIONS
|
-Displaying all partitions
+ | Displaying all partitions
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-ALTER_TABLE_RECOVER_PARTITION
+ | ALTER_TABLE_RECOVER_PARTITION
|
-Restoring table partitions
+ | Restoring table partitions
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-ALTER_TABLE_SET_LOCATION
+ | ALTER_TABLE_SET_LOCATION
|
-Setting the partition path
+ | Setting the partition path
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-GRANT_PRIVILEGE
+ | GRANT_PRIVILEGE
|
-Granting permissions to the table
+ | Granting permissions to the table
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-REVOKE_PRIVILEGE
+ | REVOKE_PRIVILEGE
|
-Revoking permissions from the table
+ | Revoking permissions to the table
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-SHOW_PRIVILEGES
+ | SHOW_PRIVILEGES
|
-Viewing table permissions of other users
+ | Viewing table permissions of other users
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
|
-DISPLAY_TABLE
+ | DISPLAY_TABLE
|
-Displaying a table
+ | Displaying a table
|
-√
+ | √
|
-√
+ | √
|
-√
+ | √
|
-√
+ | √
|
-DESCRIBE_TABLE
+ | DESCRIBE_TABLE
|
-Displaying table information
+ | Displaying table information
|
-√
+ | √
|
-×
+ | ×
|
-√
+ | √
|
-√
+ | √
+ |
+
+Enhanced datasource connection
+ |
+BIND_QUEUE
+ |
+Binding an enhanced datasource connection to a queue
+It is only used to grant permissions across projects.
+ |
+×
+ |
+×
+ |
+×
+ |
+×
|
diff --git a/docs/dli/umn/dli_01_0447.html b/docs/dli/umn/dli_01_0447.html
index b64b33d3..46b309c2 100644
--- a/docs/dli/umn/dli_01_0447.html
+++ b/docs/dli/umn/dli_01_0447.html
@@ -59,7 +59,7 @@
Modifying Permissions for an Existing User or ProjectFor a user or project that has some permissions on the database, you can revoke the existing permissions or grant new ones.
- If the options in Set Permission are gray, the corresponding account does not have the permission to modify the database. You can apply to the administrator, database owner, or other authorized users for granting and revoking permissions of databases.
+ If the options in Set Permission are gray, the corresponding account does not have the permission to modify the database. You can apply to the administrator, database owner, or other authorized users for granting and revoking permissions of databases.
- In the User Permission Info list, find the user whose permission needs to be set.
- If the user is a sub-user, you can set permissions for it.
- If the user is already an administrator, you can only view the permissions information.
In the Project Permission Info list, locate the project for which you want to set permissions and click Set Permission.
diff --git a/docs/dli/umn/dli_01_0448.html b/docs/dli/umn/dli_01_0448.html
index 3d2b929c..0507e675 100644
--- a/docs/dli/umn/dli_01_0448.html
+++ b/docs/dli/umn/dli_01_0448.html
@@ -47,29 +47,29 @@
- For details about the OBS table permissions, see Table 2.
-
Table 2 Parameter descriptionParameter
+Table 2 Parameter descriptionParameter
|
-Description
+ | Description
|
|---|
-Authorization Object
+ | Authorization Object
|
-Select User or Project.
+ | Select User or Project.
|
-Username/Project
+ | Username/Project
|
-- If you select User, enter the IAM username when granting table permissions to the user.
NOTE: The username is an existing IAM user name and has logged in to the DLI management console.
+ - If you select User, enter the IAM username when granting table permissions to the user.
NOTE: The username is an existing IAM user name and has logged in to the DLI management console.
- - If you select Project, select the project to be authorized in the current region.
NOTE: If you select Project, you can only view information about the authorized tables and their databases.
+ - If you select Project, select the project to be authorized in the current region.
NOTE: If you select Project, you can only view information about the authorized tables and their databases.
|
|
-Non-inheritable Permissions
+ | Non-inheritable Permissions
|
-Select a permission to grant it to the user, or deselect a permission to revoke it. - The following permissions are applicable to both user and project authorization:
- View Table Creation Statement: This permission allows you to view the statement for creating the current table.
- View Table Information: This permission allows you to view information about the current table.
- Select Table: This permission allows you to query data of the current table.
- Drop Table: This permission allows you to delete the current table.
- Rename Table: Rename the current table.
- Insert: This permission allows you to insert data into the current table.
- Overwrite: This permission allows you to insert data to overwrite the data in the current table.
- Add Column: This permission allows you to add columns to the current table.
- Grant Permission: This permission allows you to grant table permissions to other users or projects.
- Revoke Permission: This permission allows you to revoke the table's permissions that other users or projects have but cannot revoke the table owner's permissions.
- View Other Users' Permissions: This permission allows you to query other users' permission on the current table.
+Select a permission to grant it to the user, or deselect a permission to revoke it. - The following permissions are applicable to both user and project authorization:
- View Table Creation Statement: This permission allows you to view the statement for creating the current table.
- View Table Information: This permission allows you to view information about the current table.
- Select Table: This permission allows you to query data of the current table.
- Drop Table: This permission allows you to delete the current table.
- Rename Table: Rename the current table.
- Insert: This permission allows you to insert data into the current table.
- Overwrite: This permission allows you to insert data to overwrite the data in the current table.
- Add Column: This permission allows you to add columns to the current table.
- Grant Permission: This permission allows you to grant table permissions to other users or projects.
- Revoke Permission: This permission allows you to revoke the table's permissions that other users or projects have but cannot revoke the table owner's permissions.
- View Other Users' Permissions: This permission allows you to query other users' permission on the current table.
The partition table also has the following permissions: - Add Partition: This permission allows you to add a partition to a partition table.
- Delete Partition: This permission allows you to delete existing partitions from a partition table.
- Configure Path for Partition: This permission allows you to set the path of a partition in a partition table to a specified OBS path.
- Rename Table Partition: This permission allows you to rename partitions in a partition table.
- Restore Table Partition: This permission allows you to export partition information from the file system and save the information to metadata.
- View All Partitions: This permission allows you to view all partitions in a partition table.
@@ -92,7 +92,7 @@
Authorization Object
|
-Select User or Project.
+ | Select User or Project.
|
Username/Project
diff --git a/docs/dli/umn/dli_01_0451.html b/docs/dli/umn/dli_01_0451.html
index ef9bda21..b770dde8 100644
--- a/docs/dli/umn/dli_01_0451.html
+++ b/docs/dli/umn/dli_01_0451.html
@@ -143,12 +143,12 @@
| DLI:*:*:table:databases.dbname.tables.*
|
-DLI, any region, any account ID, all table resources of database dbname
+ | DLI, any region, any account ID, all table resources of database dbname
|
DLI:*:*:database:databases.dbname
|
-DLI, any region, any account ID, resource of database dbname
+ | DLI, any region, any account ID, resource of database dbname
|
DLI:*:*:queue:queues.*
@@ -240,7 +240,7 @@
| |
|
- Combine all the preceding fields into a JSON file to form a complete policy. You can set multiple actions and resources. You can also create a policy on the visualized page provided by IAM. For example:
The authorized user has the permission to create and delete any database, submit jobs for any queue, and delete any table under any account ID in any region of DLI.
+ - Combine all the preceding fields into a JSON file to form a complete policy. You can set multiple actions and resources. You can also create a policy on the visualized page provided by IAM. For example:
Create a policy that grants users the permission to create and delete databases, submit jobs for any queue, and delete tables under any account ID in any region of DLI.
{
"Version": "1.1",
"Statement": [
diff --git a/docs/dli/umn/dli_01_0455.html b/docs/dli/umn/dli_01_0455.html
index 691fb9cf..49ac41b5 100644
--- a/docs/dli/umn/dli_01_0455.html
+++ b/docs/dli/umn/dli_01_0455.html
@@ -3,7 +3,7 @@
Creating a Flink SQL Job
This section describes how to create a Flink SQL job. You can use Flink SQLs to develop jobs to meet your service requirements. Using SQL statements simplifies logic implementation. You can edit Flink SQL statements for your job in the DLI SQL editor. This section describes how to use the SQL editor to write Flink SQL statements.
DLI Flink OpenSource SQL jobs are fully compatible with the syntax of Flink 1.10 and 1.12 provided by the community. In addition, Redis, GaussDB(DWS), and DIS data source types are added based on the community connector.
- Prerequisites- You have prepared the data input and data output channels. For details, see Preparing Flink Job Data.
- When you use a Flink SQL job to access other external data sources, such as OpenTSDB, HBase, Kafka, DWS, RDS, CSS, CloudTable, DCS Redis, and DDS, you need to create a cross-source connection to connect the job running queue to the external data source.
- For details about the external data sources that can be accessed by Flink jobs, see Cross-Source Analysis Development Methods.
- For details about how to create a datasource connection, see Enhanced Datasource Connections. After a datasource connection is created, you can choose More > Test Address Connectivity in the Operation column on the Queue Management page to check whether the network connection between the queue and the external data source is normal. For details, see Testing Address Connectivity.
+Prerequisites- You have prepared the data input and data output channels. For details, see Preparing Flink Job Data.
- When you use a Flink SQL job to access other external data sources, such as OpenTSDB, HBase, Kafka, GaussDB(DWS), RDS, CSS, CloudTable, DCS Redis, and DDS, you need to create a datasource connection to connect the job running queue to the external data source.
- For details about the external data sources that can be accessed by Flink jobs, see Cross-Source Analysis Development Methods.
- For details about how to create a datasource connection, see Enhanced Datasource Connections. After a datasource connection is created, you can choose More > Test Address Connectivity in the Operation column on the Queue Management page to check whether the network connection between the queue and the external data source is normal. For details, see Testing Address Connectivity.
Creating a Flink SQL Job- In the left navigation pane of the DLI management console, choose > . The Flink Jobs page is displayed.
- In the upper right corner of the Flink Jobs page, click Create Job.
- Specify job parameters.
@@ -43,7 +43,7 @@
- Tag key: Enter a tag key name in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
-- Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
diff --git a/docs/dli/umn/dli_01_0457.html b/docs/dli/umn/dli_01_0457.html
index 240999b5..63d5939e 100644
--- a/docs/dli/umn/dli_01_0457.html
+++ b/docs/dli/umn/dli_01_0457.html
@@ -2,7 +2,7 @@
Creating a Flink Jar Job
This section describes how to create a Flink Jar job. You can perform secondary development based on Flink APIs, build your own JAR file, and submit the JAR file to DLI queues. DLI is fully compatible with open-source community APIs. To create a custom Flink job, you need to compile and build application JAR files. You must have a certain understanding of Flink secondary development and have high requirements related to stream computing complexity.
- Prerequisites- Ensure that a dedicated queue has been created. To create a dedicated queue, select Dedicated Resource Mode when you choose the type of a queue during purchase.
- When creating a Flink Jar job to access other external data sources, such as OpenTSDB, HBase, Kafka, GaussDB(DWS), RDS, CSS, CloudTable, DCS Redis, and DDS, you need to create a cross-source connection to connect the job running queue to the external data source.
- For details about the external data sources that can be accessed by Flink jobs, see Cross-Source Analysis Development Methods.
- For details about how to create a datasource connection, see Enhanced Datasource Connections.
On the Resources > Queue Management page, locate the queue you have created, and choose More > Test Address Connectivity in the Operation column to check whether the network connection between the queue and the data source is normal. For details, see Testing Address Connectivity.
+Prerequisites- Ensure that a dedicated queue has been created. To create a dedicated queue, select Dedicated Resource Mode when you choose the type of a queue during purchase.
- When you use a Flink Jar job to access other external data sources, such as OpenTSDB, HBase, Kafka, GaussDB(DWS), RDS, CSS, CloudTable, DCS Redis, and DDS, you need to create a datasource connection to connect the job running queue to the external data source.
- When running a Flink Jar job, you need to build the secondary development application code into a Jar package and upload the JAR package to the created OBS bucket. Choose Data Management > Package Management to create a package. For details, see Creating a Package.
DLI does not support the download function. If you need to modify the uploaded data file, please edit the local file and upload it again.
@@ -43,7 +43,7 @@
- Tag key: Enter a tag key name in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
-- Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
diff --git a/docs/dli/umn/dli_01_0461.html b/docs/dli/umn/dli_01_0461.html
index dd839112..1381b13e 100644
--- a/docs/dli/umn/dli_01_0461.html
+++ b/docs/dli/umn/dli_01_0461.html
@@ -19,7 +19,7 @@
Stopping a JobYou can stop a job in the Running or Submitting state.
- In the left navigation pane of the DLI management console, choose > . The Flink Jobs page is displayed.
- Stop a job using either of the following methods:
- Stopping a job
Locate the row that contains the job to be stopped, click More in the Operation column, and select Stop.
-Alternatively, you can select the row where the job you want to stop locates and click Stop in the upper left of the job list.
+Alternatively, you can select the row where the job you want to stop locates and click Stop in the upper left of the job list.
- Batch stopping jobs
Locate the rows containing the jobs you want to stop and click Stop in the upper left of the job list.
- In the displayed Stop Job dialog box, click OK to stop the job.
- Before stopping a job, you can trigger a savepoint to save the job status information. When you start the job again, you can choose whether to restore the job from the savepoint.
- If you select Trigger savepoint, a savepoint is created. If Trigger savepoint is not selected, no savepoint is created. By default, the savepoint function is disabled.
- The lifecycle of a savepoint starts when the savepoint is triggered and stops the job, and ends when the job is restarted. The savepoint is automatically deleted after the job is restarted.
@@ -51,7 +51,7 @@
- When switching to another project or user, you need to grant permissions to the new project or user. For details, see Managing Flink Job Permissions.
- Only jobs whose data format is the same as that of Flink jobs exported from DLI can be imported.
- In the left navigation pane of the DLI management console, choose > . The Flink Jobs page is displayed.
- Click Import Job in the upper right corner. The Import Job dialog box is displayed.
-
- Select the complete OBS path of the job configuration file to be imported. Click Next.
- Configure the same-name job policy and click next. Click Next.
- Select Overwrite job of the same name. If the name of the job to be imported already exists, the existing job configuration will be overwritten and the job status switches to Draft.
- If Overwrite job of the same name is not selected and the name of the job to be imported already exists, the job will not be imported.
+ - Select the complete OBS path of the job configuration file to be imported. Click Next.
- Configure the same-name job policy and click next. Click Next.
- Select Overwrite job of the same name. If the name of the job to be imported already exists, the existing job configuration will be overwritten and the job status switches to Draft.
- If Overwrite job of the same name is not selected and the name of the job to be imported already exists, the job will not be imported.
- Ensure that Config File and Overwrite Same-Name Job are correctly configured. Click Confirm to import the job.
Modifying Name and DescriptionYou can change the job name and description as required.
diff --git a/docs/dli/umn/dli_01_0462.html b/docs/dli/umn/dli_01_0462.html
index ed73481a..989e5407 100644
--- a/docs/dli/umn/dli_01_0462.html
+++ b/docs/dli/umn/dli_01_0462.html
@@ -2,7 +2,7 @@
Flink Job Details
After creating a job, you can view the job details to learn about the following information:
-
+
Viewing Job DetailsThis section describes how to view job details. After you create and save a job, you can click the job name to view job details, including SQL statements and parameter settings. For a Jar job, you can only view its parameter settings.
- In the left navigation pane of the DLI management console, choose > . The Flink Jobs page is displayed.
- Click the name of the job to be viewed. The Job Detail tab is displayed.
In the Job Details tab, you can view SQL statements, configured parameters.
The following uses a Flink SQL job as an example.
@@ -158,7 +158,7 @@
- Checking the Job Monitoring InformationYou can use Cloud Eye to view details about job data input and output.
+ Checking Job Monitoring InformationYou can use Cloud Eye to view details about job data input and output.
- In the left navigation pane of the DLI management console, choose > . The Flink Jobs page is displayed.
- Click the name of the job you want. The job details are displayed.
Click Job Monitoring in the upper right corner of the page to switch to the Cloud Eye console.
The following table describes monitoring metrics related to Flink jobs.
diff --git a/docs/dli/umn/dli_01_0463.html b/docs/dli/umn/dli_01_0463.html
index dfd6ead3..3b873fc2 100644
--- a/docs/dli/umn/dli_01_0463.html
+++ b/docs/dli/umn/dli_01_0463.html
@@ -31,7 +31,7 @@
Tag value
|
You can perform the following operations:
-- Click the text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Click the text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
|
diff --git a/docs/dli/umn/dli_01_0464.html b/docs/dli/umn/dli_01_0464.html
index 8c19c3c4..5077550b 100644
--- a/docs/dli/umn/dli_01_0464.html
+++ b/docs/dli/umn/dli_01_0464.html
@@ -7,25 +7,25 @@
Flink SQL Sample TemplateThe template list displays existing sample templates for Flink SQL jobs. Table 1 describes the parameters in the template list.
The scenarios of sample templates can be different, which are subject to the console.
- Table 1 Parameters in the Flink SQL sample template listParameter
+Table 1 Parameters in the Flink SQL sample template listParameter
|
-Description
+ | Description
|
|---|
-Name
+ | Name
|
-Name of a template, which has 1 to 64 characters and only contains letters, digits, hyphens (-), and underlines (_).
+ | Name of a template, which has 1 to 64 characters and only contains letters, digits, hyphens (-), and underlines (_).
|
-Description
+ | Description
|
-Description of a template. It contains 0 to 512 characters.
+ | Description of a template. It contains 0 to 512 characters.
|
-Operation
+ | Operation
|
-Create Job: Create a job directly by using the template. After a job is created, the system switches to the Edit page under .
+ | Create Job: Create a job directly by using the template. After a job is created, the system switches to the Edit page under .
|
@@ -98,7 +98,7 @@
- Tag key: Enter a tag key name in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
-- Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
@@ -107,50 +107,50 @@
- Click OK to enter the editing page.
The Table 4 describes the parameters on the template editing page.
- Table 4 Template parametersParameter
+Table 4 Template parametersParameter
|
-Description
+ | Description
|
|---|
-Name
+ | Name
|
-You can modify the template name.
+ | You can modify the template name.
|
-Description
+ | Description
|
-You can modify the template description.
+ | You can modify the template description.
|
-Saving Mode
+ | Saving Mode
|
-- Save Here: Save the modification to the current template.
- Save as New: Save the modification as a new template.
+ | - Save Here: Save the modification to the current template.
- Save as New: Save the modification as a new template.
|
-SQL statement editing area
+ | SQL statement editing area
|
-In the area, you can enter detailed SQL statements to implement business logic. For details about how to compile SQL statements, see Data Lake Insight SQL Syntax Reference.
+ | In the area, you can enter detailed SQL statements to implement business logic. For details about how to compile SQL statements, see Data Lake Insight SQL Syntax Reference.
|
-Save
+ | Save
|
-Save the modifications.
+ | Save the modifications.
|
-Create Job
+ | Create Job
|
-Use the current template to create a job.
+ | Use the current template to create a job.
|
-Format
+ | Format
|
-Format SQL statements. After SQL statements are formatted, you need to compile SQL statements again.
+ | Format SQL statements. After SQL statements are formatted, you need to compile SQL statements again.
|
-Theme Settings
+ | Theme Settings
|
-Change the font size, word wrap, and page style (black or white background).
+ | Change the font size, word wrap, and page style (black or white background).
|
diff --git a/docs/dli/umn/dli_01_0485.html b/docs/dli/umn/dli_01_0485.html
index b6fbd347..ed0c3da6 100644
--- a/docs/dli/umn/dli_01_0485.html
+++ b/docs/dli/umn/dli_01_0485.html
@@ -12,8 +12,6 @@
- Permission Management for Global Variables
-- Service Authorization
-
diff --git a/docs/dli/umn/dli_01_0486.html b/docs/dli/umn/dli_01_0486.html
deleted file mode 100644
index 54f641d0..00000000
--- a/docs/dli/umn/dli_01_0486.html
+++ /dev/null
@@ -1,57 +0,0 @@
-
-
-Service Authorization
-PrerequisitesOnly the tenant account or a subaccount of user group admin can authorize access.
-
- ProcedureAfter entering the DLI management console, you are advised to set agency permissions to ensure that DLI can be used properly.
- If you need to adjust the agency permissions, modify them on the Service Authorization page. For details about the required agency permissions, see Table 1.
- - Select required agency permissions and click Update Authorization. Only the tenant account or a subaccount of user group admin can authorize access. If the message "Agency permissions updated" is displayed, the update is successful.
- Once service authorization has succeeded, an agency named dli_admin_agency on IAM will be created. Go to the agency list to view the details. Do not delete dli_admin_agency.
-
-
- Table 1 DLI agency permissionsPermission
- |
-Details
- |
-Remarks
- |
-
|---|
-
-Tenant Administrator (global service)
- |
-Tenant Administrator permissions are required to access data from OBS to execute Flink jobs on DLI, for example, obtaining OBS/DWS data sources, log dump (including bucket authorization), checkpointing enabling, and job import and export.
- |
-Due to cloud service cache differences, permission setting operations require about 60 minutes to take effect.
- |
-
-DIS Administrator
- |
-DIS Administrator permissions are required to use DIS data as the data source of DLI Flink jobs.
- |
-Due to cloud service cache differences, permission setting operations require about 30 minutes to take effect.
- |
-
-VPC Administrator
- |
-VPC Administrator permissions are required to use the VPC, subnet, route, VPC peering connection, and port for DLI datasource connections.
- |
-Due to cloud service cache differences, permission setting operations require about 3 minutes to take effect.
- |
-
-SMN Administrator
- |
-To receive notifications when a DLI job fails, SMN Administrator permissions are required.
- |
-Due to cloud service cache differences, permission setting operations require about 3 minutes to take effect.
- |
-
-
-
-
-
- Testing Address Connectivity
-It can be used to test the connectivity between the DLI queue and the peer IP address specified by the user in common scenarios, or the connectivity between the DLI queue and the peer IP address bound to the datasource connection in cross-source connection scenarios. The operation is as follows:
+ It can be used to test the connectivity between the DLI queue and the peer IP address specified by the user in common scenarios, or the connectivity between the DLI queue and the peer IP address bound to the datasource connection in datasource connection scenarios. The operation is as follows:
- On the Queue Management page, locate the row containing the target queue, click More in the Operation column, and select Test Address Connectivity.
- On the Test Address Connectivity page, enter the address to be tested. The domain name and IP address are supported, and the port number can be specified.
- Click Test.
If the test address is reachable, a message is displayed on the page, indicating that the address is reachable.
If the test address is unreachable, the system displays a message indicating that the address is unreachable. Check the network configurations and try again. Network configurations include the VPC peering and the datasource connection. Check whether they have been activated.
diff --git a/docs/dli/umn/dli_01_0498.html b/docs/dli/umn/dli_01_0498.html
index 58e84739..6bd0eaab 100644
--- a/docs/dli/umn/dli_01_0498.html
+++ b/docs/dli/umn/dli_01_0498.html
@@ -3,7 +3,7 @@
(Recommended) Creating a Flink OpenSource SQL Job
This section describes how to create a Flink OpenSource SQL job.
DLI Flink OpenSource SQL jobs are fully compatible with the syntax of Flink 1.10 and 1.12 provided by the community. In addition, Redis, GaussDB(DWS), and DIS data source types are added based on the community connector. For details about the syntax and restrictions of Flink SQL DDL, DML, and functions, see Table API & SQL.
- Prerequisites- You have prepared the data input and data output channels. For details, see Preparing Flink Job Data.
- Before creating a Flink OpenSource SQL job to access other external data sources, such as OpenTSDB, HBase, Kafka, GaussDB(DWS), RDS, CSS, CloudTable, DCS Redis, and DDS, you need to create a cross-source connection to connect the job running queue to the external data source.
- For details about the external data sources that can be accessed by Flink jobs, see Cross-Source Analysis Development Methods.
- For details about how to create a datasource connection, see Enhanced Datasource Connections.
On the Resources > Queue Management page, locate the queue you have created, and choose More > Test Address Connectivity in the Operation column to check whether the network connection between the queue and the data source is normal. For details, see Testing Address Connectivity.
+Prerequisites- You have prepared the data input and data output channels. For details, see Preparing Flink Job Data.
- Before creating a Flink OpenSource SQL job to access other external data sources, such as OpenTSDB, HBase, Kafka, GaussDB(DWS), RDS, CSS, CloudTable, DCS Redis, and DDS, you need to create a datasource connection to connect the job running queue to the external data source.
- Tag key: Enter a tag key name in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
-- Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
diff --git a/docs/dli/umn/dli_01_0504.html b/docs/dli/umn/dli_01_0504.html
new file mode 100644
index 00000000..6c85a9c6
--- /dev/null
+++ b/docs/dli/umn/dli_01_0504.html
@@ -0,0 +1,113 @@
+
+
+ Overview
+ Elastic Resource PoolAn elastic resource pool provides compute resources (CPU and memory) for running DLI jobs. The unit is CU. One CU contains one CPU and 4 GB memory.
+ You can create multiple queues in an elastic resource pool. Compute resources can be shared among queues. You can properly set the resource pool allocation policy for queues to improve compute resource utilization.
+
+ SpecificationsDLI offers compute resources in the specifications listed in Table 1.
+
+ Table 1 Elastic resource pool specificationsEdition
+ |
+Specification
+ |
+Constraint
+ |
+Scenario
+ |
+
|---|
+
+Basic
+ |
+16–64 CUs
+ |
+- High reliability and availability are not supported.
- Queue properties and job priorities cannot be set.
- Notebook instances cannot be interconnected with.
+For more constraints and limitations on elastic resource pools, see Constraints.
+ |
+This edition is suitable for testing scenarios with low resource consumption and low requirements for resource reliability and availability.
+ |
+
+Standard
+ |
+64 CUs or higher
+ |
+For more constraints and limitations on elastic resource pools, see Constraints.
+ |
+This edition offers powerful computing capabilities, high availability, and flexible resource management. It is suitable for large-scale computing tasks and business scenarios with long-term resource planning needs.
+ |
+
+
+
+
+
+ Constraints- The region of an elastic resource pool cannot be changed.
- Jobs of Flink 1.10 or later can run in elastic resource pools.
- The network segment of an elastic resource pool cannot be changed after being set.
- You can only view the scaling history of resource pools in the last 30 days.
- Elastic resource pools cannot access the Internet.
+
+
+
+ ScenarioResources too fixed to meet a range of requirements.
+ The quantities of compute resources required for jobs change in different time of a day. If the resources cannot be scaled based on service requirements, they may be wasted or insufficient. Figure 1 shows the resource usage during a day.
+ - After ETL jobs are complete, no other jobs are running during 04:00 to 07:00 in the early morning. The resources could be released at that time.
- From 09:00 to 12:00 a.m. and 02:00 to 04:00 p.m., a large number of ETL report and job queries are queuing for compute resources.
Figure 1 Fixed resources
+
+ Resources are isolated and cannot be shared.
+ A company has two departments, and each run their jobs on a DLI queue. Department A is idle from 08:00 to 12:00 a.m. and has remaining resources, while department B has a large number of service requests during this period and needs more resources to meet the requirements. Since the resources are isolated and cannot be shared between department A and B, the idle resources are wasted. Figure 2 Resource waste due to resource isolation
+
+ Elastic resource pools can be accessed by different queues and automatically scaled to improve resource utilization and handle resource peaks.
+ You can use elastic resource pools to centrally manage and allocate resources. Multiple queues can be bound to an elastic resource pool to share the pooled resources.
+
+ Architecture and AdvantagesElastic resource pools support the CCE cluster architecture for heterogeneous resources so you can centrally manage and allocate them.
+ Elastic resource pools have the following advantages:
+ - Unified management
- You can manage multiple internal clusters and schedule jobs. You can manage millions of cores for compute resources.
- Elastic resource pools can be deployed across multiple AZs to support high availability. (This function will be supported in later versions.)
+ - Tenant resource isolation
Resources of different queues are isolated to reduce the impact on each other.
+ - Shared access and flexibility
- Specifications can be scaled in seconds to help you handle request peaks.
- Queue priorities and CU quotas can be set at different time to improve resource utilization.
+ - Job-level isolation (supported in later versions)
SQL jobs can run on independent Spark instances, reducing mutual impacts between jobs.
+ - Automatic scaling (supported in later versions)
The queue quota is updated in real time based on workload and priority.
+
+ Using elastic resource pools has the following advantages.
+
+ Advantage
+ |
+No Elastic Resource Pool
+ |
+Use Elastic Resource Pool
+ |
+
|---|
+
+Efficiency
+ |
+You need to set scaling tasks repeatedly to improve the resource utilization.
+ |
+Dynamic scaling can be done in seconds.
+ |
+
+Resource utilization
+ |
+Resources cannot be shared among different queues.
+For example, if queue 1 has 10 unused CUs and queue 2 requires more resources due to heavy load, queue 2 cannot utilize the resources of queue 1. It has to be scaled up.
+ |
+Queues added to the same elastic resource pool can share compute resources.
+ |
+
+When you set a data source, you must allocate different network segments to each queue, which requires a large number of VPC network segments.
+ |
+You can add multiple general-purpose queues in the same elastic resource pool to one network segment, simplifying the data source configuration.
+ |
+
+Resource allocation
+ |
+If resources are insufficient for scale-out tasks of multiple queues, some queues will fail to be scaled out.
+ |
+You can set the priority for each queue in the elastic resource pool based on the peak hours to ensure proper resource allocation.
+ |
+
+
+
+
+ You can perform the following operations on elastic resource pools:
+
+
+
+
+
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+
+
+ Creating an Elastic Resource Pool
+ For details about the application scenarios of elastic resource pools, see the Overview. This section describes how to create an elastic resource pool.
+ Precautions- If you use an enhanced datasource connection, the network segment of the elastic resource pool cannot overlap that of the data source.
- The network segment of an elastic resource pool cannot be changed after being set.
+
+ Creating an Elastic Resource Pool- In the navigation pane on the left, choose Resources > Resource Pool.
- On the Resource Pool page, click Buy Resource Pool in the upper right corner.
- On the displayed page, set the following parameters:
+ Table 1 ParametersParameter
+ |
+Description
+ |
+
|---|
+
+Region
+ |
+Select a region. Select a region near you to ensure the lowest latency possible.
+ |
+
+Project
+ |
+Each region corresponds to a project.
+ |
+
+Name
+ |
+Name of the elastic resource pool.
+- The name can contain only digits, letters, and underscores (_), but cannot contain only digits or start with an underscore (_) or digit.
- The description can contain a maximum of 128 characters.
+ NOTE: The elastic resource pool name is case-insensitive. Uppercase letters will be automatically converted to lowercase letters.
+
+ |
+
+CU Range
+ |
+The maximum and minimum CUs allowed for the elastic resource pool.
+ |
+
+Description
+ |
+Description of the elastic resource pool
+ |
+
+CIDR Block
+ |
+The CIDR block to which the elastic resource pool belongs. If you use an enhanced datasource connection, the CIDR block of the elastic resource pool cannot overlap that of the data source. The CIDR block of an elastic resource pool cannot be modified after being set.
+Recommended CIDR block:
+10.0.0.0~10.255.0.0/16~19
+172.16.0.0~172.31.0.0/16~19
+192.168.0.0~192.168.0.0/16~19
+ |
+
+Enterprise Project
+ |
+If the created elastic resource pool belongs to an enterprise project, select the enterprise project.
+An enterprise project facilitates project-level management and grouping of cloud resources and users.
+ NOTE: This parameter is displayed only for users who have enabled the Enterprise Management Service.
+
+ |
+
+Tags
+ |
+Tags used to identify cloud resources. A tag includes the tag key and tag value. If you want to use the same tag to identify multiple cloud resources, that is, to select the same tag from the drop-down list box for all services, you are advised to create predefined tags on the Tag Management Service (TMS).
+ NOTE: - A maximum of 20 tags can be added.
- Only one tag value can be added to a tag key.
- The key name in each resource must be unique.
+
+- Tag key: Enter a tag key name in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
+
+
+- Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+
+
+ |
+
+
+
+ - Click Buy and confirm the configurations.
- Click Pay. Wait until the status of the elastic resource pool changes to Available. The elastic resource pool is successfully created.
- Refer to Creating an Elastic Resource Pool and Running a Job and Configuring Scaling Policies for Queues to perform subsequent operations as needed.
+
+
+
+
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+
+
+ Managing Queues
+ Multiple queues can be added to an elastic resource pool. For details about how to add a queue, see Adding a Queue. You can configure the number of CUs you want based on the compute resources used by DLI queues during peaks and troughs and set priorities for the scaling policies to ensure stable running of jobs.
+ Precautions- In any time segment of a day, the total minimum CUs of all queues in an elastic resource pool cannot be more than the minimum CUs of the pool.
- In any time segment of a day, the maximum CUs of any queue in an elastic resource pool cannot be more than the maximum CUs of the pool.
- The periods of scaling policies cannot overlap.
- The period of a scaling policy can only be set by hour and specified by the start time and end time. For example, if you set the period to 00-09, the time range when the policy takes effect is [00:00, 09:00). The period of the default scaling policy cannot be modified.
- In any period, compute resources are preferentially allocated to meet the minimum number of CUs of all queues. The remaining CUs (total CUs of the elastic resource pool – total minimum CUs of all queues) are allocated in accordance with the scaling policy priorities.
- After the queue is scaled out, the system starts billing you for the added CUs. So, if you do not have sufficient requirements, scale in your queue to release unnecessary CUs to save cost.
+
Table 1 CU allocation (without jobs)Scenario
+ |
+CUs
+ |
+
|---|
+
+An elastic resource pool has a maximum number of 256 CUs for queue A and queue B. The scaling policies are as follows:
+- Queue A: priority 5; period: 00:00–9:00; minimum CU: 32; maximum CU: 64
- Queue B: priority 10; time period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+From 00:00 a.m. to 09:00 a.m.:
+- The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 160 CUs remaining.
- The remaining CUs are allocated based on the priorities. Queue B is prior to queue A. Therefore, queue B gets 128 CUs, and queue A has 32 CUs.
+ |
+
+An elastic resource pool has a maximum number of 96 CUs for queue A and queue B. The scaling policies are as follows:
+- Queue A: priority 5; period: 00:00–9:00; minimum CU: 32; maximum CU: 64
- Queue B: priority 10; time period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+From 00:00 a.m. to 09:00 a.m.:
+- The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are no remaining CUs.
- The allocation is complete.
+ |
+
+An elastic resource pool has a maximum number of 128 CUs for queue A and queue B. The scaling policies are as follows:
+- Queue A: priority 5; period: 00:00–9:00; minimum CU: 32; maximum CU: 64
- Queue B: priority 10; time period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+From 00:00 a.m. to 09:00 a.m.:
+- The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 32 CUs remaining.
- The remaining 32 CUs are preferentially allocated to queue B.
+ |
+
+An elastic resource pool has a maximum number of 128 CUs for queue A and queue B. The scaling policies are as follows:
+- Queue A: priority 5; period: 00:00–9:00; minimum CU: 32; maximum CU: 64
- Queue B: priority 5; time period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+From 00:00 a.m. to 09:00 a.m.:
+- The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 32 CUs remaining.
- The two queues have the same priority, the remaining 32 CUs are randomly allocated to the two queues.
+ |
+
+
+
+ Table 2 CU allocation (with jobs)Scenario
+ |
+Actual CUs of Elastic Resource Pool
+ |
+CUs Allocated to Queue A
+ |
+CUs Allocated to Queue B
+ |
+Allocation Description
+ |
+
|---|
+
+Queues A and B are added to the elastic resource pool. The scaling policies are as follows:
+- Queue A: period: 00:00–9:00; minimum CU: 32; maximum CU: 64
- Queue B: period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+192 CUs
+ |
+64 CUs
+ |
+128 CUs
+ |
+If the actual CUs of the elastic resource pool are greater than or equal to the sum of the maximum CUs of the two queues,
+the maximum CUs are allocated to both queues.
+ |
+
+96 CUs
+ |
+32 CUs
+ |
+64 CUs
+ |
+The elastic resource pool preferentially meets the minimum CUs of the two queues.
+After the minimum CUs are allocated to the two queues, no CUs are allocatable.
+ |
+
+128 CUs
+ |
+32 CUs to 64 CUs
+ |
+64 CUs to 96 CUs
+ |
+The elastic resource pool preferentially meets the minimum CUs of the two queues. That is, 32 CUs are allocated to queue A, 64 CUs are allocated to queue B, and the remaining 32 CUs are available.
+The remaining CUs are allocated based on the queue load and priority. The actual CUs of the queue change within the range listed.
+ |
+
+
+
+
+
+ Managing Queues- In the navigation pane on the left, choose Resources > Resource Pool.
- Locate the target elastic resource pool and click Queue MGMT in the Operation column. The Queue Management page is displayed.
- View the queues added to the elastic resource pool.
+ Table 3 Queue parametersParameter
+ |
+Description
+ |
+
|---|
+
+Name
+ |
+Queue name
+ |
+
+Type
+ |
+Queue type
+- For SQL
- For general purpose
+ |
+
+Period
+ |
+The start and end time of the queue scaling policy. This time range includes the start time but not the end time, that is, [start time, end time).
+ |
+
+Min CUs
+ |
+Minimum number of CUs allowed by the scaling policy.
+ |
+
+Max CUs
+ |
+Maximum number of CUs allowed by the scaling policy.
+ |
+
+Priority
+ |
+Priority of the scaling policy for a queue in the elastic resource pool. The priority ranges from 1 to 100. A smaller value indicates a lower priority.
+ |
+
+Engine
+ |
+For a queue running SQL jobs, the engine is Spark.
+For a queue for general purpose, the engine can be Spark or Flink, but it is displayed by -- in this page.
+ |
+
+Created
+ |
+Time when a queue is added to the elastic resource pool
+ |
+
+Enterprise Project
+ |
+Enterprise project the queue belongs to.
+Queues under different enterprise projects can be added to an elastic resource pool.
+ |
+
+Owner
+ |
+User who added this queue
+ |
+
+Operation
+ |
+- Edit: Modify or add a scaling policy.
- Delete: Delete the queue.
+ |
+
+
+
+ - Locate the target queue and click Edit in the Operation column.
- In the displayed Queue Management pane, perform the following operations as needed:
- Add: Click Create to add a scaling policy. Set Priority, Period, Min CU, and Max CU, and click OK.
- Modify: Modify parameters of an existing scaling policy and click OK.
- Delete: Locate the row that contains the scaling policy you want, click Delete and click OK.
The Priority and Period parameters must meet the following requirements:
+ - Priority: The default value is 1. The value ranges from 1 to 100. A bigger value indicates a higher priority.
- Period:
- You can only set the period to hours in [start time,end time) format.
- For example, if the Period to 01 and 17, the scaling policy takes effect at 01:00 a.m. till 05:00 p.m.
- The periods of scaling policies with different priorities cannot overlap.
+ - Max CUs and Min CUs:
- In any time segment of a day, the total minimum CUs of all queues in an elastic resource pool cannot be more than the minimum CUs of the pool.
- In any time segment of a day, the maximum CUs of any queue in an elastic resource pool cannot be more than the maximum CUs of the pool.
+
+
+
+ - After you finish the settings, click statistics icon in the upper right corner of the queue list to view all scaling policies of all queue in the elastic resource pool.
+
- View the scaling task generated when the scaling starts. Go to Job Management > SQL Jobs and view the jobs of the SCALE_QUEUE type.
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0507.html b/docs/dli/umn/dli_01_0507.html
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+
+
+ Setting CUs
+ CU settings are used to control the maximum and minimum CU ranges for elastic resource pools to avoid unlimited resource scaling.
+ For example, an elastic resource pool has a maximum of 256 and two queues, and each queue must have at least 64 CUs. If you want to add another queue that needs at lest 256 CUs to the elastic resource pool, the operation is not allowed due to the maximum CUs of the elastic resource pool.
+ Precautions- In any time segment of a day, the total minimum CUs of all queues in an elastic resource pool cannot be more than the minimum CUs of the pool.
- In any time segment of a day, the maximum CUs of any queue in an elastic resource pool cannot be more than the maximum CUs of the pool.
- When you change the minimum CUs of a created elastic resource pool, ensure that the value is no more than the current CU value. Otherwise, the modification fails.
+
+ Setting CUs- In the navigation pane on the left, choose Resources > Resource Pool.
- Locate the row that contains the desired elastic resource pool, click More in the Operation column, and select Set CUs.
- In the Set CUs dialog box, set the minimum CUs on the left and the maximum CUs on the right. Click OK.
+
+ FAQ- How Do I Change the Minimum CUs of the Existing Queues in an Elastic Resource Pool If the Total CUs of the Queues Equal the Minimum CUs of the Elastic Resource Pool?
Answer:
+- Step 1: Increase the maximum number of CUs of the existing queues so that the current number of CUs of the elastic resource pool is no less than the target minimum number of CUs (the sum of the minimum number of CUs of the queues you want to change to).
If the maximum number of CUs of the elastic resource pool is equal to its minimum number of CUs, increase the maximum number of CUs.
+
+ - Step 2: Set the minimum CUs of the elastic resource pool.
- Step 3: Change the minimum CUs of the existing queues in the elastic resource pool.
+ - How Do I Add Queues to an Elastic Resource Pool If the Total CUs of the Queues Equal the Minimum CUs of the Elastic Resource Pool?
Answer:
+- Step 1: Increase the maximum number of CUs of the existing queues so that the current number of CUs of the elastic resource pool is no less than the target minimum number of CUs (the sum of the minimum number of CUs of the queues you want to change to).
If the maximum number of CUs of the elastic resource pool is equal to its minimum number of CUs, increase the maximum number of CUs.
+
+ - Step 2: Set the minimum CUs of the elastic resource pool.
- Step 3: Add queues to the elastic resource pool.
- Step 4: Restore the maximum CUs of the queues you have increased in Step 1.
+
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0508.html b/docs/dli/umn/dli_01_0508.html
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+
+
+ Elastic Resource Pool
+
+
+
diff --git a/docs/dli/umn/dli_01_0509.html b/docs/dli/umn/dli_01_0509.html
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+
+
+ Adding a Queue
+ You can add one or more queues to an elastic resource pool to run jobs. This section describes how to add a queue to an elastic resource pool.
+ PrecautionsAutomatic scaling of an elastic resource pool cannot be triggered for Flink jobs.
+
+ Adding a Queue- In the navigation pane on the left, choose Resources > Resource Pool.
- Locate the target elastic resource pool and click Add Queue in the Operation column.
- On the Add Queue page, configure basic queue information. The following table describes the parameters.
+ Table 1 Queue informationParameter
+ |
+Description
+ |
+
|---|
+
+Name
+ |
+Name of the queue to add
+ |
+
+Type
+ |
+- For SQL: The queue is used to run SQL jobs.
- General general purpose: The queue is used to run Spark and Flink jobs.
+ |
+
+Engine
+ |
+If Type is For SQL, the queue engine can be spark or trino.
+ |
+
+Enterprise Project
+ |
+Select the enterprise project the queue belongs to. Queues under different enterprise projects can be added to an elastic resource pool.
+Enterprise projects let you manage cloud resources and users by project.
+ NOTE: This parameter is displayed only for users who have enabled the Enterprise Management Service.
+
+ |
+
+Description
+ |
+Description about the queue.
+ |
+
+Tags
+ |
+Tags used to identify cloud resources. A tag includes the tag key and tag value. If you want to use the same tag to identify multiple cloud resources, that is, to select the same tag from the drop-down list box for all services, you are advised to create predefined tags on the Tag Management Service (TMS).
+ NOTE: - A maximum of 20 tags can be added.
- Only one tag value can be added to a tag key.
- The key name in each resource must be unique.
+
+- Tag key: Enter a tag key name in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
+
+
+- Tag value: Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+
+
+ |
+
+
+
+ - Click Next. On the displayed page, configure a scaling policy for the queue in the elastic resource pool.
Click Create to add a scaling policy with specified priority, period, Minimum CUs, and Maximum CUs. The parameters of each scaling policy are as follows:
+
+Table 2 Auto scaling policyParameter
+ |
+Description
+ |
+
|---|
+
+Priority
+ |
+A bigger priority value indicates a higher priority. You can set a number ranging from 1 to 100.
+ |
+
+Period
+ |
+Time segment when the policy takes effects. It can be set only by hour. The start time is on the left, and the end time is on the right.
+
+- The periods of scaling policies with different priorities cannot overlap.
+ |
+
+Min CU
+ |
+Minimum number of CUs allowed by the scaling policy.
+- In any time segment of a day, the total minimum CUs of all queues in an elastic resource pool cannot be more than the minimum CUs of the pool.
- If the minimum CUs of the queue is less than 16 CUs, both Max. Spark Driver Instances and Max. Prestart Spark Driver Instances set in the queue properties do not apply. Refer to Setting Queue Properties.
+ |
+
+Max CU
+ |
+Maximum number of CUs allowed by the scaling policy.
+In any time segment of a day, the maximum CUs of any queue in an elastic resource pool cannot be more than the maximum CUs of the pool.
+ |
+
+
+
+ The first scaling policy is the default policy and cannot be deleted or modified.
+
+ - Click OK. View all queues and scaling policies added to the elastic resource pool by referring to Managing Queues.
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0513.html b/docs/dli/umn/dli_01_0513.html
index 76be00db..30981876 100644
--- a/docs/dli/umn/dli_01_0513.html
+++ b/docs/dli/umn/dli_01_0513.html
@@ -14,7 +14,7 @@
- DLI Operations That Can Be Recorded by CTS
- - Quotas
+ - Quota Management
diff --git a/docs/dli/umn/dli_01_0514.html b/docs/dli/umn/dli_01_0514.html
index 59156f94..95de5686 100644
--- a/docs/dli/umn/dli_01_0514.html
+++ b/docs/dli/umn/dli_01_0514.html
@@ -32,7 +32,7 @@
Datasource connection status. The following three statuses are available:
- NOTE: If the connection status is Failed, click  on the left to view the detailed error information.
+ NOTE: If the connection status is Failed, click on the left to view the detailed error information.
|
diff --git a/docs/dli/umn/dli_01_0515.html b/docs/dli/umn/dli_01_0515.html
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@@ -0,0 +1,94 @@
+
+
+ Creating an Elastic Resource Pool and Running a Job
+ This section walks you through the procedure of adding a queue to an elastic resource pool and binding an enhanced datasource connection to the elastic resource pool. Figure 1 Process of creating an elastic resource pool
+
+
+ Table 1 ProcedureStep
+ |
+Description
+ |
+Reference
+ |
+
|---|
+
+Create an elastic resource pool
+ |
+Create an elastic resource pool and configure basic information, such as the billing mode, CU range, and CIDR block.
+ |
+Creating an Elastic Resource Pool
+ |
+
+Add a queue to the elastic resource pool
+ |
+Add the queue where your jobs will run on to the elastic resource pool. The operations are as follows:
+- Set basic information about the queue, such as the name and type.
- Configure the scaling policy of the queue, including the priority, period, and the maximum and minimum CUs allowed for scaling.
+ |
+Adding a Queue
+Managing Queues
+ |
+
+(Optional) Create an enhanced datasource connection.
+ |
+If a job needs to access data from other data sources, for example, GaussDB(DWS) and RDS, you need to create a datasource connection.
+The created datasource connection must be bound to the elastic resource pool.
+ |
+Creating an Enhanced Datasource Connection
+ |
+
+Run a job.
+ |
+Create and submit the job as you need.
+ |
+SQL Job Management
+Overview
+Creating a Spark Job
+ |
+
+
+
+
+ Step 1: Create an Elastic Resource Pool- Log in to the DLI management console. In the navigation pane on the left, choose Resources > Resource Pool.
- On the displayed Resource Pool page, click Buy Resource Pool in the upper right corner.
- On the displayed page, set the following parameters:
- Name: Enter the name of the elastic resource pool. For example, pool_test.
- CU range: Minimum and maximum CUs of the elastic resource pool.
- CIDR Block: Network segment of the elastic resource pool. For example, 172.16.0.0/18.
- Set other parameters as required.
+For details about how to create an elastic resource pool, see Creating an Elastic Resource Pool.
+ - Click Buy. Confirm the configuration and click Pay.
- Go to the Resource Pool page to view the creation status. If the status is Available, the elastic resource pool is ready for use.
+
+ Step 2: Add a Queue to the Elastic Resource Pool- In the Operation column of the created elastic resource pool, click Add Queue.
- Specify the basic information about the queue. The configuration parameters are as follows:
+
- Click Next. On the displayed page, set Min CU to 64 and Max CU to 64.
- Click OK. The queue is added.
+
+ (Optional) Step 3: Create an Enhanced Datasource ConnectionIn this example, a datasource connection is required to connect to RDS. You need to create a datasource connection. If your job does not need to connect to an external data source, skip this step.
+ - Log in to the RDS console and create an RDS DB instance. For details, see . Log in to the RDS instance, create a database and name it test2.
- Locate the row that contains the test2 database, click Query SQL Statements in the Operation column. On the displayed page, enter the following statement to create table tabletest2. Click Execute SQL. The table creation statement is as follows:
CREATE TABLE `tabletest2` (
+ `id` int(11) unsigned,
+ `name` VARCHAR(32)
+) ENGINE = InnoDB DEFAULT CHARACTER SET = utf8mb4;
+ - On the RDS console, choose Instances form the navigation pane. Click the name of a created RDS DB instance to view its basic information.
- In the Connection Information pane, obtain the floating IP address, database port, VPC, and subnet.
- Click the security group name. In the Inbound Rules tab, add a rule to allow access from the CIDR block of the elastic resource pool. For example, if the CIDR block of the elastic resource pool is 172.16.0.0/18 and the database port is 3306, set the rule Priority to 1, Action to Allow, Protocol to TCP and Port to 3306, Type to IPv4, and Source to 172.16.0.0/18.
Click OK. The security group rule is added.
+ - Log in to the DLI management console. In the navigation pane on the left, choose Datasource Connections. On the displayed page, click Create in the Enhanced tab.
- In the displayed dialog box, set the following parameters:
- Connection Name: Name of the enhanced datasource connection
- Resource Pool: Select the elastic resource pool created in Step 1: Create an Elastic Resource Pool.
If you cannot decide the elastic resource pool in this step, you can skip this parameter, go to the Enhanced tab, and click More > Bind Resource Pool in the Operation column of the row that contains this datasource connection after it is created.
+
+ - VPC: Select the VPC of the RDS DB instance obtained in 4.
- Subnet: Select the subnet of the RDS DB instance obtained in 4.
- Set other parameters as you need.
+Click OK. Click the name of the created datasource connection to view its status. You can perform subsequent steps only after the connection status changes to Active.
+ - Click Resources > Queue Management, select the target queue, for example, general_test. In the Operation column, click More and select Test Address Connectivity.
- In the displayed dialog box, enter Floating IP address:Database port of the RDS database in the Address box and click Test to check whether the database is reachable.
+
+ Step 4: Run a JobRun a Flink SQL jab on a queue in an elastic resource pool.
+ - On the DLI management console, choose Job Management > Flink Jobs. On the Flink Jobs page, click Create Job.
- In the Create Job dialog box, set Type to Flink SQL and Name to testFlinkSqlJob. Click OK.
- On the job editing page, set the following parameters:
- Queue: Select the general_test queue added to the elastic resource pool in Step 2: Add a Queue to the Elastic Resource Pool.
- Save Job Log: Enable this function.
- OBS Bucket: Select an OBS bucket for storing job logs and grant access permissions of the OBS bucket as prompted.
- Enable Checkpointing: Enable.
- Enter the SQL statement in the editing pane. The following is an example. Modify the parameters in bold as you need.
CREATE SINK STREAM car_info (id INT, name STRING) WITH (
+ type = "rds",
+ region = "", /* Change the value to the current region ID. */
+ 'pwd_auth_name'="xxxxx", // Name of the datasource authentication of the password type created on DLI. If datasource authentication is used, you do not need to set the username and password for the job.
+db_url = "mysql://192.168.x.x:3306/test2", /* The format is mysql://floating IP address:port number of the RDS database/database name. */
+table_name = "tabletest2" /* Table name in RDS database */
+);
+INSERT INTO
+ car_info
+SELECT
+ 13,
+ 'abc';
+
+ - Click Check Semantic and ensure that the SQL statement passes the check. Click Save. Click Start, confirm the job parameters, and click Start Now to execute the job.
- Wait until the job is complete. The job status changes to Completed.
- Log in to the RDS console, click the name of the RDS DB instance. On the displayed page, click the name of the created database, for example, test2, and click Query SQL Statements in the Operation column of the row that containing the tabletest2 table.
- On the displayed page, click Execute SQL. Check whether data has been written into the RDS table.
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0516.html b/docs/dli/umn/dli_01_0516.html
new file mode 100644
index 00000000..195139da
--- /dev/null
+++ b/docs/dli/umn/dli_01_0516.html
@@ -0,0 +1,121 @@
+
+
+ Configuring Scaling Policies for Queues
+ ScenarioA company has multiple departments that perform data analysis in different periods during a day.
+ - Department A requires a large number of compute resources from 00:00 a.m. to 09:00 a.m. In other time segments, only small tasks are running.
- Department B requires a large number of compute resources from 10:00 a.m. to 10:00 p.m. Some periodical tasks are running in other time segments during a day.
+ In the preceding scenario, you can add two queues to an elastic resource pool: queue test_a for department A, and queue test_b for department B. You can add scaling policies for 00:00-09:00 and 10:00-23:00 respectively to the test_a and test_b queues. For jobs in other periods, you can modify the default scaling policy.
+
+ Table 1 Scaling policyQueue
+ |
+Period
+ |
+Priority
+ |
+CUs
+ |
+Default Period
+ |
+Default Priority
+ |
+Default CUs
+ |
+Remarks
+ |
+
|---|
+
+test_a
+ |
+[00:00, 09:00)
+ |
+20
+ |
+Minimum CU: 64
+Maximum CU: 128
+ |
+The time segments beyond [00:00, 09:00)
+ |
+5
+ |
+Minimum CU: 16
+Maximum CU: 32
+ |
+Jobs of department A
+ |
+
+test_b
+ |
+[10:00, 23:00)
+ |
+20
+ |
+Minimum CU: 64
+Maximum CU: 128
+ |
+The time segments beyond [10:00, 23:00)
+ |
+5
+ |
+Minimum CU: 32
+Maximum CU: 64
+ |
+Jobs of department B
+ |
+
+
+
+
+
+ Precautions- In any time segment of a day, the total minimum CUs of all queues in an elastic resource pool cannot be more than the minimum CUs of the pool.
- In any time segment of a day, the maximum CUs of any queue in an elastic resource pool cannot be more than the maximum CUs of the pool.
- The periods of scaling policies cannot overlap.
- The period of a scaling policy can only be set by hour and specified by the start time and end time. For example, if you set the period to 00-09, the period when the policy takes effect is [00:00, 09:00). The period of the default scaling policy cannot be modified.
- In any period, compute resources are preferentially allocated to meet the minimum number of CUs of all queues. The remaining CUs (maximum CUs of the elastic resource pool – total minimum CUs of all queues) are allocated in accordance with the scaling policy priorities.
- A scaling policy with a smaller priority value (for example, 1) is prior to those with a bigger priority value (for example, 100).
- If the scaling policies of two queues have the same priority, resources are randomly allocated to a queue. If there are remaining resources, they are randomly allocated until there is no more left.
+
Table 2 CU allocationScenario
+ |
+CUs
+ |
+
|---|
+
+An elastic resource pool has a maximum number of 256 CUs for queue A and queue B. The scaling policies are as follows:
+- Queue A: priority 5; period: 00:00–9:00; minimum CU: 32; maximum CU: 128
- Queue B: priority 10; time period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+From 00:00 a.m. to 09:00 a.m.:
+- The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 160 CUs remaining.
- The remaining CUs are allocated based on the priorities. Queue B is prior to queue A. Therefore, queue B gets 64 CUs, and queue A has 96 CUs.
+ |
+
+An elastic resource pool has a maximum number of 96 CUs for queue A and queue B. The scaling policies are as follows:
+- Queue A: priority 5; period: 00:00–9:00; minimum CU: 32; maximum CU: 64
- Queue B: priority 10; time period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+From 00:00 a.m. to 09:00 a.m.:
+- The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are no remaining CUs.
- The allocation is complete.
+ |
+
+An elastic resource pool has a maximum number of 128 CUs for queue A and queue B. The scaling policies are as follows:
+- Queue A: priority 5; period: 00:00–9:00; minimum CU: 32; maximum CU: 64
- Queue B: priority 10; time period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+From 00:00 a.m. to 09:00 a.m.:
+- The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 32 CUs remaining.
- The remaining 32 CUs are all preferentially allocated to queue B.
+ |
+
+An elastic resource pool has a maximum number of 128 CUs for queue A and queue B. The scaling policies are as follows:
+- Queue A: priority 5; period: 00:00–9:00; minimum CU: 32; maximum CU: 64
- Queue B: priority 5; time period: 00:00–9:00; minimum CU: 64; maximum CU: 128
+ |
+From 00:00 a.m. to 09:00 a.m.:
+- The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 32 CUs remaining.
- The two queues have the same priority, the remaining 32 CUs are randomly allocated to the two queues.
+ |
+
+
+
+
+
+
+ Setting a Scaling Policy- Log in to the DLI management console and create an elastic resource pool. Set the minimum and maximum number of CUs of the pool to 128 and 256 respectively. For details, see Creating an Elastic Resource Pool.
- Choose Resources > Resource Pool. Locate the row that contains the created elastic resource pool, and click Queue MGMT in the Operation column.
- Refer to Adding a Queue to create the test_a queue and set the scaling policy.
- Set the priority of the default scaling policy to 5, Min CU to 16, and Max CU to 32.
- Click create to add a scaling policy. Set the priority to 20, Period to 00--09, Min CU to 64, and Max CU to 128.
+ - View the scaling policy on the Queue Management page of the specific elastic resource pool.
Click  to view graphical statistics of priorities and CU settings for all time segments.
+ - Refer to Adding a Queue to create the test_b queue and set the scaling policy.
- Set the priority of the default scaling policy to 5, Min CU to 32, and Max CU to 64.
- Click create to add a scaling policy. Set the priority to 20, Period to 10--23, Min CU to 64, and Max CU to 128.
+ - View the scaling policy on the Queue Management page of the specific elastic resource pool.
Click  to view graphical statistics on priorities and CU settings of the two queues for all time segments.
+
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0524.html b/docs/dli/umn/dli_01_0524.html
new file mode 100644
index 00000000..bc54155f
--- /dev/null
+++ b/docs/dli/umn/dli_01_0524.html
@@ -0,0 +1,23 @@
+
+
+ Modifying Specifications
+ ScenarioIf CUs of a yearly/monthly elastic resource pool cannot meet your service requirements, you can modify the CUs. In this case, you will be charged based on the number of CUs exceeding that of the yearly/monthly elastic resource pool.
+ For example, you have purchased an elastic resource pool with 64 CUs, and you find that most time data processing needs 128 CUs. You can add 64 CUs to the elastic resource pool and be billed based on a CU/hour basis. To save more, you can scale up your elastic resource pool to 128 CUs and be billed on a yearly/monthly basis for the 128-CU package.
+
+ PrecautionsCurrently, only yearly/monthly elastic resource pools can be scaled.
+
+ Scaling Up- In the navigation pane on the left of the console, choose Resources > Resource Pool.
- Select the elastic resource pool you want and choose More > Modify Specifications in the Operation column.
- In the Modify Specifications dialog page, set Operation to Scale-out and specify the number of CUs you want to add.
- Confirm the changes and click OK.
- Choose Job Management > SQL Jobs to view the status of the SCALE_POOL SQL job.
If the job status is Scaling, the elastic resource pool is scaling up. Wait until the job status changes to Finished.
+
+
+ Scaling Down By default, the minimum number of CUs is 16. That is, when the specifications of an elastic resource pool are 16 CUs, you cannot scale the pool down.
+
+ - In the navigation pane on the left, choose Resources > Resource Pool.
- Select the elastic resource pool you want and choose More > Modify Specifications in the Operation column.
- In the Modify Specifications dialog page, set Operation to Scale-in and specify the number of CUs you want to add.
- Confirm the changes and click OK.
- Choose Job Management > SQL Jobs to view the status of the SCALE_POOL SQL job.
If the job status is Scaling, the elastic resource pool is scaling down. Wait until the job status changes to Finished.
+
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0525.html b/docs/dli/umn/dli_01_0525.html
new file mode 100644
index 00000000..f185f651
--- /dev/null
+++ b/docs/dli/umn/dli_01_0525.html
@@ -0,0 +1,48 @@
+
+
+ Managing Tags
+ Tag ManagementA tag is a key-value pair that you can customize to identify cloud resources. It helps you to classify and search for cloud resources. A tag consists of a tag key and a tag value.
+ If you use tags in other cloud services, you are advised to create the same tag (key-value pairs) for cloud resources used by the same business to keep consistency.
+ DLI supports the following two types of tags:
+ - Resource tags: non-global tags created on DLI
+ - Predefined tags: global tags created on Tag Management Service (TMS).
+
+ DLI allows you to add, modify, or delete tags for queues.
+ - In the left navigation pane of the DLI console, choose Resources > Resource Pool.
- In the Operation column of the queue, choose More > Tags.
- The tag management page is displayed, showing the tag information about the current queue.
- Click Add/Edit Tag. The Add/Edit Tag dialog is displayed. Enter a tag and a value, and click Add.
+ Table 1 Tag parametersParameter
+ |
+Description
+ |
+
|---|
+
+Tag key
+ |
+You can specify the tag key in either of the following ways:
+- Click the text box and select a predefined tag key from the drop-down list.
To add a predefined tag, you need to create one on TMS and then select it from the Tag key drop-down list. You can click View predefined tags to go to the Predefined Tags page of the TMS console. Then, click Create Tag in the upper corner of the page to create a predefined tag.
+
+
+- Enter a tag key in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
+
+
+ |
+
+Tag value
+ |
+You can specify the tag value in either of the following ways:
+- Click the text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+
+
+ |
+
+
+
+ - Click OK.
- (Optional) To delete a tag, locate the row where the tag locates in the tag list and click Delete in the Operation column to delete the tag.
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0526.html b/docs/dli/umn/dli_01_0526.html
new file mode 100644
index 00000000..6716b3c0
--- /dev/null
+++ b/docs/dli/umn/dli_01_0526.html
@@ -0,0 +1,45 @@
+
+
+ Managing Permissions
+ Administrators can assign permissions of different operation scopes to users for each elastic resource pool.
+ Precautions- The administrator and elastic resource pool owner have all permissions, which cannot be set or modified by other users.
+
+ Procedure- In the navigation pane on the left of the DLI console, choose Resources > Resource Pool.
- Select the desired elastic resource pool and choose More > Permissions in the Operation column. The User Permissions area displays the list of users who have permissions of elastic resource pools.
You can assign permissions to new users, modify permissions for users who already have some permissions of elastic resource pools, and revoke all permissions of a user on a pool.
+
+
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0528.html b/docs/dli/umn/dli_01_0528.html
new file mode 100644
index 00000000..c6775822
--- /dev/null
+++ b/docs/dli/umn/dli_01_0528.html
@@ -0,0 +1,19 @@
+
+
+ Before You Start
+
+
+
diff --git a/docs/dli/umn/dli_01_0529.html b/docs/dli/umn/dli_01_0529.html
new file mode 100644
index 00000000..2357a99f
--- /dev/null
+++ b/docs/dli/umn/dli_01_0529.html
@@ -0,0 +1,33 @@
+
+
+ Regular Operations
+
+
+
diff --git a/docs/dli/umn/dli_01_0530.html b/docs/dli/umn/dli_01_0530.html
new file mode 100644
index 00000000..6cab58e6
--- /dev/null
+++ b/docs/dli/umn/dli_01_0530.html
@@ -0,0 +1,21 @@
+
+
+ Binding a Queue
+ ScenarioIf you want a queue to use resources in an elastic resource pool, bind the queue to the pool.
+ You can click Associate Queue on the Resource Pool page to bind a queue to an elastic resource pool, or bind a queue on the Queue Management page.
+ Elastic resource pools support only Flink 1.10 or later. If jobs using Flink 1.7 run on a queue that is bound to an elastic resource pool, errors may occur due to incompatibility.
+
+
+ Prerequisites- Both the elastic resource pool and queue are available.
- The queue you want to bind must be a dedicated queue in pay-per-use billing mode.
- No resources are frozen.
- Only queues under the same enterprise project can be bound to an elastic resource pool.
+
+ Associating a Queue- In the navigation pane on the left, choose Resources > Resource Pool.
- Locate the row that contains the desired elastic resource pool, click More in the Operation column, and select Associate Queue.
- In the displayed dialog box, select the desired queue and click OK.
+
+ Allocating a Queue to an Elastic Resource Pool- In the navigation pane on the left, choose Resources > Queue Management.
- Locate the target queue and choose More > Bind Resource Pool in the Operation column.
- Select the desired elastic resource pool and click OK.
+
+
+
+
diff --git a/docs/dli/umn/dli_01_0531.html b/docs/dli/umn/dli_01_0531.html
index d3431845..d9a30ffd 100644
--- a/docs/dli/umn/dli_01_0531.html
+++ b/docs/dli/umn/dli_01_0531.html
@@ -15,7 +15,7 @@
Step 1: Prepare a Data SourceIn this example, Kafka is the data source.
For more information about Flink job data, see Preparing Flink Job Data.
Enable DIS to import Kafka data to DLI. For details, see "Buying a Kafka Instance" in the Distributed Message Service Kafka User Guide.
- - Create the dependent Kafka resources.
Before creating a Kafka instance, ensure the availability of resources, including a virtual private cloud (VPC), subnet, security group, and security group rules. - For details about how to create a VPC and subnet, see "Creating a VPC and Subnet" in the Virtual Private Cloud User Guide. For details about how to create and use a subnet in an existing VPC, see "Create a subnet for the VPC" in the Virtual Private Cloud User Guide.
- The created VPC and the Kafka instance you will create must be in the same region.
- Retain the default settings unless otherwise specified.
+ - Create the dependent Kafka resources.
Before creating a Kafka instance, ensure the availability of resources, including a virtual private cloud (VPC), subnet, security group, and security group rules. - For details about how to create a VPC and subnet, see "Creating a VPC and Subnet" in Virtual Private Cloud User Guide. For details about how to create and use a subnet in an existing VPC, see "Create a Subnet for the VPC" in Virtual Private Cloud User Guide.
- The created VPC and the Kafka instance you will create must be in the same region.
- Retain the default settings unless otherwise specified.
- For details about how to create a security group, see "Creating a Security Group" in the Virtual Private Cloud User Guide. For details about how to add rules to a security group, see "Creating a Subnet for the VPC" in the Virtual Private Cloud User Guide.
- Create a DMS for Kafka Instance for job input streams.
- Log in to the DMS for Kafka console.
- Select a region in the upper left corner.
- On the DMS for Kafka page, click Buy Instance in the upper right corner and set related parameters. The required instance information is as follows:
- Region: Select the region where DLI is located.
- Project: Keep the default value.
- AZ: Keep the default value.
- Instance Name: kafka-dliflink
- Specifications: Default
- Enterprise Project: default
- Version: Keep the default value.
- CPU Architecture: Keep the default value.
- Broker Flavor: Select a flavor as needed.
- Brokers: Retain the default value.
- Storage Space: Keep the default value.
- Capacity Threshold Policy: Keep the default value.
- VPC and Subnet: Select the VPC and subnet created in 1.
- Security Group: Select the security group created in 1.
- Manager Username: Enter dliflink (used to log in to the instance management page).
- Password: **** (The system cannot detect your password.)
- Confirm Password: ****
- More Settings: Do not configure this parameter.
- Click Buy. The confirmation page is displayed.
- Confirm that the instance information is correct, read and agree to the , and click Submit. It takes about 10 to 15 minutes to create an instance.
- Create a Kafka topic.
- Click the name of the created Kafka instance. The basic information page of the instance is displayed.
- Choose Topics in the navigation pane on the left. On the displayed page, click Create Topic. Configure the following parameters:
- Topic Name: For this example, enter testkafkatopic.
- Partitions: Set the value to 1.
- Replicas: Set the value to 1.
-Retain default values for other parameters.
+Retain the default values for other parameters.
@@ -51,7 +51,7 @@
- In the navigation pane on the OBS management console, choose Object Storage.
- In the upper right corner of the page, click Create Bucket and set bucket parameters.
- Region: Select the region where DLI is located.
- Bucket Name: Enter a bucket name. For this example, enter obstest.
- Default Storage Class: Standard
- Bucket Policy: Private
- Default Encryption: Do not enable
- Direct Reading: Do not enable
- Enterprise Project: default
- Tags: Leave it blank.
- Click Create Now.
-Step 4: Create a QueueFlink OpenSource SQL jobs cannot run on the default queue. You need to create a queue, for example, Flinktest. For details, see Creating a Queue.
+ Step 4: Create a QueueFlink OpenSource SQL jobs cannot run on the default queue. You need to create a queue, for example, Flinktest. For details, see "Creating a Queue".
- Log in to the DLI management console. On the Overview page, click Buy Queue in the upper right corner.
If this is your first time logging in to the DLI management console, you need to be authorized to access OBS.
- Configure the following parameters:
- Name: Flinktest
- Type: For general purpose. Select Dedicated Resource Mode.
- Specifications: 16 CUs
- Enterprise Project: default
- Description: Leave it blank.
- Advanced Settings: Custom
- CIDR Block: Set a CIDR block that does not conflict with the Kafka instance's CIDR block.
- Click Buy and confirm the configuration.
- Submit the request.
It takes 10 to 15 minutes to bind the queue to a cluster after the queue is created.
@@ -60,19 +60,19 @@
Step 5: Create an Enhanced Datasource Connection Between DLI and KafkaYou need to create an enhanced datasource connection for the Flink OpenSource SQL job. For details, see "Creating an Enhanced Datasource Connection".
- The CIDR block of the DLI queue bound with a datasource connection cannot overlap with the CIDR block of the data source.
- Datasource connections cannot be created for the default queue.
- To access a table across data sources, you need to use a queue bound to a datasource connection.
- - Create a Kafka security group rule to allow access from the CIDR block of the DLI queue.
- On the Kafka management console, click an instance name on the DMS for Kafka page. Basic information of the Kafka instance is displayed.
- In the Connection pane, obtain the Instance Address (Private Network). In the Network pane, obtain the VPC and subnet of the instance.
- Click the security group name in the Network pane. On the displayed page, click the Inbound Rules tab and add a rule to allow access from the DLI queue.
For example, if the CIDR block of the queue is 10.0.0.0/16, set Protocol to TCP, Type to IPv4, Source to 10.0.0.0/16, and click OK.
+- Create a Kafka security group rule to allow access from the CIDR block of the DLI queue.
- On the Kafka management console, click an instance name on the DMS for Kafka page. Basic information of the Kafka instance is displayed.
- In the Connection pane, obtain the Instance Address (Private Network). In the Network pane, obtain the VPC and subnet of the instance.
- Click the security group name in the Network pane. On the displayed page, click the Inbound Rules tab and add a rule to allow access from the DLI queue.
For example, if the CIDR block of the queue is 10.0.0.0/16, set Protocol to TCP, Type to IPv4, Source to 10.0.0.0/16, and click OK.
- Create an enhanced datasource connection to Kafka.
- Log in to the DLI management console. In the navigation pane on the left, choose Datasource Connections. On the displayed page, click Create in the Enhanced tab.
- In the displayed dialog box, set the following parameters: For details, see the following section:
- Connection Name: Name of the enhanced datasource connection For this example, enter dli_kafka.
- Resource Pool: Select the name of the queue created in Step 4: Create a Queue.
- VPC: Select the VPC of the Kafka instance.
- Subnet: Select the subnet of Kafka instance.
- Set other parameters as you need.
Click OK. Click the name of the created datasource connection to view its status. You can perform subsequent steps only after the connection status changes to Active.
- - Choose Resources > Queue Management and locate the queue created in Step 4: Create a Queue. In the Operation column, choose More > Test Address Connectivity.
- In the displayed dialog box, enter Kafka instance address (private network):port in the Address box and click Test to check whether the instance is reachable. Note that multiple addresses must be tested separately.
+ - Choose Resources > Queue Management and locate the queue created in Step 4: Create a Queue. In the Operation column, click More and select Test Address Connectivity.
- In the displayed dialog box, enter Kafka instance address (private network):port in the Address box and click Test to check whether the instance is reachable. Note that multiple addresses must be tested separately.
Step 6: Create an Enhanced Datasource Connection Between DLI and RDS- Create an RDS security group rule to allow access from CIDR block of the DLI queue.
If the RDS DB instance and Kafka instance are in the same security group of the same VPC, skip this step. Access from the DLI queue has been allowed in 1. - Go to the RDS console, click the name of the target RDS for MySQL DB instance on the Instances page. Basic information of the instance is displayed.
- In the Connection Information pane, obtain the floating IP address, database port, VPC, and subnet.
- Click the security group name. On the displayed page, click the Inbound Rules tab and add a rule to allow access from the DLI queue. For example, if the CIDR block of the queue is 10.0.0.0/16, set Priority to 1, Action to Allow, Protocol to TCP, Type to IPv4, Source to 10.0.0.0/16, and click OK.
+ Step 6: Create an Enhanced Datasource Connection Between DLI and RDS- Create an RDS security group rule to allow access from CIDR block of the DLI queue.
If the RDS DB instance and Kafka instance are in the same security group of the same VPC, skip this step. Access from the DLI queue has been allowed in 1. - Go to the RDS console, click the name of the target RDS for MySQL DB instance on the Instances page. Basic information of the instance is displayed.
- In the Connection Information pane, obtain the floating IP address, database port, VPC, and subnet.
- Click the security group name. On the displayed page, click the Inbound Rules tab and add a rule to allow access from the DLI queue. For example, if the CIDR block of the queue is 10.0.0.0/16, set Priority to 1, Action to Allow, Protocol to TCP, Type to IPv4, Source to 10.0.0.0/16, and click OK.
- Create an enhanced datasource connection to RDS.
If the RDS DB instance and Kafka instance are in the same VPC and subnet, skip this step. The enhanced datasource connection created in 2 has connected the subnet.
If the two instances are in different VPCs or subnets, perform the following steps to create an enhanced datasource connection: - Log in to the DLI management console. In the navigation pane on the left, choose Datasource Connections. On the displayed page, click Create in the Enhanced tab.
- In the displayed dialog box, set the following parameters: For details, see the following section:
- Connection Name: Name of the enhanced datasource connection For this example, enter dli_rds.
- Resource Pool: Select the name of the queue created in Step 4: Create a Queue.
- VPC: Select the VPC of the RDS DB instance.
- Subnet: Select the subnet of RDS DB instance.
- Set other parameters as you need.
Click OK. Click the name of the created datasource connection to view its status. You can perform subsequent steps only after the connection status changes to Active.
- - Choose Resources > Queue Management and locate the queue created in Step 4: Create a Queue. In the Operation column, choose More > Test Address Connectivity.
- In the displayed dialog box, enter floating IP address:database port of the RDS DB instance in the Address box and click Test to check whether the database is reachable.
+ - Choose Resources > Queue Management and locate the queue created in Step 4: Create a Queue. In the Operation column, click More and select Test Address Connectivity.
- In the displayed dialog box, enter floating IP address:database port of the RDS DB instance in the Address box and click Test to check whether the database is reachable.
@@ -120,7 +120,7 @@ CREATE TABLE jdbcSink (
insert into jdbcSink select * from kafkaSource;
- Click Check Semantics.
- Click Start. On the displayed Start Flink Job page, confirm the job specifications and the price, and click Start Now to start the job.
After the job is started, the system automatically switches to the page, and the created job is displayed in the job list. You can view the job status in the column. After a job is successfully submitted, Status of the job will change from to .
-If Status of a job is or , the job fails to be submitted or fails to run. In this case, you can move the cursor over the status icon to view the error details. You can click  to copy these details. After handling the fault based on the provided information, resubmit the job.
+If Status of a job is or , the job fails to be submitted or fails to run. In this case, you can hover over the status icon to view the error details. You can click to copy these details. After handling the fault based on the provided information, resubmit the job.
- Connect to the Kafka cluster and send the following test data to the Kafka topics:
{"order_id":"202103241000000001", "order_channel":"webShop", "order_time":"2021-03-24 10:00:00", "pay_amount":"100.00", "real_pay":"100.00", "pay_time":"2021-03-24 10:02:03", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
{"order_id":"202103241606060001", "order_channel":"appShop", "order_time":"2021-03-24 16:06:06", "pay_amount":"200.00", "real_pay":"180.00", "pay_time":"2021-03-24 16:10:06", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
diff --git a/docs/dli/umn/dli_01_0532.html b/docs/dli/umn/dli_01_0532.html
new file mode 100644
index 00000000..128c06fe
--- /dev/null
+++ b/docs/dli/umn/dli_01_0532.html
@@ -0,0 +1,20 @@
+
+
+Viewing Scaling History
+ScenarioIf you added a queue to or deleted one from an elastic resource pool, or you scaled an added queue, the CU quantity of the elastic resource pool may be changed. You can view historical CU changes of an elastic resource pool on the console.
+  When scaling in an elastic resource pool, Spark and SQL jobs may automatically retry. However, if the number of retries exceeds the limit, the jobs will fail and need to be manually executed again.
+
+
+ PrerequisitesCurrently, you can only view the historical records generated within the last 30 days on the console.
+
+ Viewing Scaling History of an Elastic Resource Pool- In the navigation pane on the left, choose Resources > Resource Pool.
- Select the desired elastic resource pool and choose More > Expansion History in the Operation column.
- On the displayed page, select a duration to view the CU usage.
You can view the number of CUs before and after a scaling, and the target number of CUs.
+The historical records can be displayed in charts or tables. Click  in the upper right corner to switch the display.
+
+
+ Quotas
-What Is a Quota?A quota limits the quantity of a resource available to users, thereby preventing spikes in the usage of the resource.
- You can also request for an increased quota if your existing quota cannot meet your service requirements.
+ Quota Management
+ What Is a Quota?A quota limits the quantity of a resource available to users, thereby preventing spikes in the usage of the resource.
+ You can also request for an increased quota if your existing quota cannot meet your service requirements.
- How Do I View My Quotas?- Log in to the management console.
- Click
 in the upper left corner and select Region and Project. - Click
 (the My Quotas icon) in the upper right corner.The Service Quota page is displayed.
- - View the used and total quota of each type of resources on the displayed page.
If a quota cannot meet service requirements, increase a quota.
+How Do I View My Quotas?- Log in to the management console.
- Click
 in the upper left corner and select a region and a project. - Click the My Quota icon
 in the upper right corner of the page.The Service Quota page is displayed.
+ - View the used and total quota of each type of resources on the displayed page.
If a quota cannot meet service requirements, increase a quota.
How Do I Apply for a Higher Quota?The system does not support online quota adjustment. To increase a resource quota, dial the hotline or send an email to the customer service. We will process your application and inform you of the progress by phone call or email.
- Before dialing the hotline number or sending an email, ensure that the following information has been obtained:
- - Domain name, project name, and project ID
Log in to the management console using the cloud account, click the username in the upper right corner, select My Credentials from the drop-down list, and obtain the domain name, project name, and project ID on the My Credentials page.
- - Quota information, including:
- Service name
- Quota type
- Required quota
+How Do I Apply for a Higher Quota?The system does not support online quota adjustment. To increase a resource quota, dial the hotline or send an email to the customer service. We will process your application and inform you of the progress by phone call or email.
+ Before dialing the hotline number or sending an email, ensure that the following information has been obtained:
+ - Domain name, project name, and project ID
To obtain the preceding information, log in to the management console, click the username in the upper right corner, and choose My Credentials from the drop-down list.
+ - Quota information, including:
- ServiceName
- Quota type
- Required quota
- Learn how to obtain the service hotline and email address.
+ Learn how to obtain the service hotline and email address.
diff --git a/docs/dli/umn/dli_01_0552.html b/docs/dli/umn/dli_01_0552.html
index 8ded1d7b..e8470cee 100644
--- a/docs/dli/umn/dli_01_0552.html
+++ b/docs/dli/umn/dli_01_0552.html
@@ -29,7 +29,7 @@
Tag value
|
You can specify the tag value in either of the following ways:
-- Click the tag value text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Click the tag value text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
|
@@ -53,7 +53,7 @@
Tag key
|
You can specify the tag key in either of the following ways:
-- Click the text box for tag key and select a predefined tag key from the drop-down list.
To add a predefined tag, you need to create one on TMS and then select it from the Tag key drop-down list. You can click View predefined tags to go to the Predefined Tags page of the TMS console. Then, click Create Tag in the upper corner of the page to create a predefined tag.
+- Click the text box for tag key and select a predefined tag key from the drop-down list.
To add a predefined tag, you need to create one on TMS and then select it from the Tag key drop-down list. You can click View predefined tags to go to the Predefined Tags page of the TMS console. Then, click Create Tag in the upper corner of the page to create a predefined tag.
- Enter a tag key in the text box.
NOTE: A tag key can contain a maximum of 128 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
@@ -64,7 +64,7 @@
Tag value
|
You can specify the tag value in either of the following ways:
-- Click the tag value text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 225 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
+ - Click the tag value text box and select a predefined tag value from the drop-down list.
- Enter a tag value in the text box.
NOTE: A tag value can contain a maximum of 255 characters. Only letters, digits, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
|
diff --git a/docs/dli/umn/dli_01_0563.html b/docs/dli/umn/dli_01_0563.html
new file mode 100644
index 00000000..aac50a18
--- /dev/null
+++ b/docs/dli/umn/dli_01_0563.html
@@ -0,0 +1,51 @@
+
+
+Setting Queue Properties
+ScenarioDLI allows you to set properties for queues.
+ You can set Spark driver parameters to improve the scheduling efficiency of queues.
+ This section describes how to set queue properties on the management console.
+
+ Constraints and Limitations- Only SQL queues of the Spark engine support configuring queue properties.
- Setting queue properties is only supported after the queue has been created.
- Currently, only queue properties related to the Spark driver can be set.
- Queue properties cannot be set in batches.
- For a queue in an elastic resource pool, if the minimum CUs of the queue is less than 16 CUs, both Max. Spark Driver Instances and Max. Prestart Spark Driver Instances set in the queue properties do not apply.
+
+ Procedure- In the navigation pane of the DLI management console, choose Resources > Queue Management.
- In the Operation column of the queue, choose More > Set Property.
- Go to the queue property setting page and set property parameters. For details about the property parameters, see Table 1.
+
Table 1 Queue propertiesProperty
+ |
+Description
+ |
+Value Range
+ |
+
|---|
+
+Max. Spark Driver Instances
+ |
+Maximum number of Spark drivers can be started on this queue, including the Spark driver that is prestarted and the Spark driver that runs jobs.
+ |
+- For a 16-CU queue, the value is 2.
- For a queue that has more than 16 CUs, the value range is [2, queue CUs/16].
- If the minimum CUs of the queue is less than 16 CUs, this configuration item does not apply.
+ |
+
+Max. Prestart Spark Driver Instances
+ |
+Maximum number of Spark drivers can be prestarted on this queue. When the number of Spark drivers that run jobs exceeds the value of Max. Concurrency per Instance, the jobs are allocated to the Spark drivers that are prestarted.
+ |
+- For a 16-CU queue, the value range is 0 to 1.
- For a queue that has more than 16 CUs, the value range is [2, queue CUs/16].
- If the minimum CUs of the queue is less than 16 CUs, this configuration item does not apply.
+ |
+
+Max. Concurrency per Instance
+ |
+Maximum number of jobs can be concurrently executed by a Spark driver. When the number of jobs exceeds the value of this parameter, the jobs are allocated to other Spark drivers.
+ |
+1–32
+ |
+
+
+
+ - Click OK.
+
+ Allocating a Queue to an Enterprise Project
+You can create enterprise projects matching the organizational structure of your enterprises to centrally manage cloud resources across regions by project. Then you can create user groups and users with different permissions and add them to enterprise projects.
+ DLI allows you to select an enterprise project when creating a queue. This section describes how to bind a DLI queue to and modify an enterprise project.
+ Currently, enterprise projects can be modified only for queues that have not been added to elastic resource pools.
+
+ PrerequisitesYou have logged in to the Enterprise Project Management Service console and created an enterprise project.
+
+ Binding an Enterprise ProjectWhen creating a DLI queue, you can select a created enterprise project for Enterprise Project.
+ Alternatively, you can click Create Enterprise Project to go to the Enterprise Project Management Service console to create an enterprise project and view existing ones.
+ For details about how to create a queue, see Creating a Queue.
+
+ Modifying an Enterprise ProjectYou can modify the enterprise project bound to a created cluster as needed.
+ - Log in to the DLI management console.
- In the navigation pane on the left, choose Resources > Queue Management.
- In the queue list, locate the queue for which you want to modify the enterprise project, click More in the Operation column, and select Modify Enterprise Project.
- In the Modify Enterprise Project dialog box displayed, select an enterprise project.
Alternatively, you can click Create Enterprise Project to go to the Enterprise Project Management Service console to create an enterprise project and view existing ones.
+ - After the modification, click OK to save the enterprise project information of the queue.
+
+
+ Allocating to an Enterprise Project
+You can create enterprise projects matching the organizational structure of your enterprises to centrally manage cloud resources across regions by project. Then you can create user groups and users with different permissions and add them to enterprise projects.
+ DLI allows you to select an enterprise project when creating an elastic resource pool. This section describes how to bind an elastic resource pool to and modify an enterprise project.
+ Modifying the enterprise project of an elastic resource pool will modify the enterprise projects of the queues in the elastic resource pool.
+ Only queues under the same enterprise project can be bound to an elastic resource pool.
+
+ PrerequisitesYou have logged in to the Enterprise Project Management Service console and created an enterprise project.
+
+ Binding an Enterprise ProjectWhen creating an elastic resource pool, you can select a created enterprise project for Enterprise Project.
+ Alternatively, you can click Create Enterprise Project to go to the Enterprise Project Management Service console to create an enterprise project and view existing ones.
+ For details about how to create a queue, see Creating an Elastic Resource Pool.
+
+ Modifying an Enterprise ProjectYou can modify the enterprise project bound to a created cluster as needed.
+ - Log in to the DLI management console.
- In the navigation pane on the left, choose Resources > Resource Pool.
- In the elastic resource pool list, locate the elastic resource pool for which you want to modify the enterprise project, click More in the Operation column, and select Allocate to Enterprise Project.
- In the Modify Enterprise Project dialog box displayed, select an enterprise project.
Alternatively, you can click Create Enterprise Project to go to the Enterprise Project Management Service console to create an enterprise project and view existing ones.
+ - After the modification, click OK to save the enterprise project information of the elastic resource pool.
+
+
+
diff --git a/docs/dli/umn/dli_03_0002.html b/docs/dli/umn/dli_03_0002.html
index dce9fdce..e2523026 100644
--- a/docs/dli/umn/dli_03_0002.html
+++ b/docs/dli/umn/dli_03_0002.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0008.html b/docs/dli/umn/dli_03_0008.html
index 5f51cbb4..9d76034f 100644
--- a/docs/dli/umn/dli_03_0008.html
+++ b/docs/dli/umn/dli_03_0008.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0009.html b/docs/dli/umn/dli_03_0009.html
index 94c995e9..ba3dba02 100644
--- a/docs/dli/umn/dli_03_0009.html
+++ b/docs/dli/umn/dli_03_0009.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0010.html b/docs/dli/umn/dli_03_0010.html
index f465fe3b..eedf2334 100644
--- a/docs/dli/umn/dli_03_0010.html
+++ b/docs/dli/umn/dli_03_0010.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0011.html b/docs/dli/umn/dli_03_0011.html
index 463da933..c11ee61e 100644
--- a/docs/dli/umn/dli_03_0011.html
+++ b/docs/dli/umn/dli_03_0011.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0013.html b/docs/dli/umn/dli_03_0013.html
index 13a73692..7733a01b 100644
--- a/docs/dli/umn/dli_03_0013.html
+++ b/docs/dli/umn/dli_03_0013.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0014.html b/docs/dli/umn/dli_03_0014.html
index 210b5533..077f41f0 100644
--- a/docs/dli/umn/dli_03_0014.html
+++ b/docs/dli/umn/dli_03_0014.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0017.html b/docs/dli/umn/dli_03_0017.html
index 806fa011..75b87126 100644
--- a/docs/dli/umn/dli_03_0017.html
+++ b/docs/dli/umn/dli_03_0017.html
@@ -29,7 +29,7 @@ sc.hadoopConfiguration.set("fs.obs.session.token", sts)
diff --git a/docs/dli/umn/dli_03_0020.html b/docs/dli/umn/dli_03_0020.html
index ecf35d99..f2067d07 100644
--- a/docs/dli/umn/dli_03_0020.html
+++ b/docs/dli/umn/dli_03_0020.html
@@ -4,83 +4,13 @@
diff --git a/docs/dli/umn/dli_03_0021.html b/docs/dli/umn/dli_03_0021.html
index e6a0efe6..f220113c 100644
--- a/docs/dli/umn/dli_03_0021.html
+++ b/docs/dli/umn/dli_03_0021.html
@@ -4,37 +4,13 @@
diff --git a/docs/dli/umn/dli_03_0022.html b/docs/dli/umn/dli_03_0022.html
index f93ee993..1fe0c02e 100644
--- a/docs/dli/umn/dli_03_0022.html
+++ b/docs/dli/umn/dli_03_0022.html
@@ -5,43 +5,11 @@
diff --git a/docs/dli/umn/dli_03_0025.html b/docs/dli/umn/dli_03_0025.html
index a73c0333..7e48a1d2 100644
--- a/docs/dli/umn/dli_03_0025.html
+++ b/docs/dli/umn/dli_03_0025.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0028.html b/docs/dli/umn/dli_03_0028.html
index 5ea12f32..2a5ea254 100644
--- a/docs/dli/umn/dli_03_0028.html
+++ b/docs/dli/umn/dli_03_0028.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0029.html b/docs/dli/umn/dli_03_0029.html
index c1f8fa13..09033cc9 100644
--- a/docs/dli/umn/dli_03_0029.html
+++ b/docs/dli/umn/dli_03_0029.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0036.html b/docs/dli/umn/dli_03_0036.html
index e5b6c1ad..a4bff550 100644
--- a/docs/dli/umn/dli_03_0036.html
+++ b/docs/dli/umn/dli_03_0036.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0037.html b/docs/dli/umn/dli_03_0037.html
index 51d2c1ca..a02a1dce 100644
--- a/docs/dli/umn/dli_03_0037.html
+++ b/docs/dli/umn/dli_03_0037.html
@@ -4,81 +4,15 @@
diff --git a/docs/dli/umn/dli_03_0038.html b/docs/dli/umn/dli_03_0038.html
index 7ab46c3a..c3bb6924 100644
--- a/docs/dli/umn/dli_03_0038.html
+++ b/docs/dli/umn/dli_03_0038.html
@@ -47,7 +47,7 @@ StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironm
diff --git a/docs/dli/umn/dli_03_0040.html b/docs/dli/umn/dli_03_0040.html
index 720f221a..e4847d71 100644
--- a/docs/dli/umn/dli_03_0040.html
+++ b/docs/dli/umn/dli_03_0040.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0043.html b/docs/dli/umn/dli_03_0043.html
index 883adca6..c1a4b5d6 100644
--- a/docs/dli/umn/dli_03_0043.html
+++ b/docs/dli/umn/dli_03_0043.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0044.html b/docs/dli/umn/dli_03_0044.html
index 99b8f6a0..98044b55 100644
--- a/docs/dli/umn/dli_03_0044.html
+++ b/docs/dli/umn/dli_03_0044.html
@@ -66,7 +66,7 @@ private void initConf() {
diff --git a/docs/dli/umn/dli_03_0045.html b/docs/dli/umn/dli_03_0045.html
index 9b8ec75e..301889fa 100644
--- a/docs/dli/umn/dli_03_0045.html
+++ b/docs/dli/umn/dli_03_0045.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0046.html b/docs/dli/umn/dli_03_0046.html
index 8ff9bfba..822d7ca9 100644
--- a/docs/dli/umn/dli_03_0046.html
+++ b/docs/dli/umn/dli_03_0046.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0047.html b/docs/dli/umn/dli_03_0047.html
index 71a6e34f..8da071eb 100644
--- a/docs/dli/umn/dli_03_0047.html
+++ b/docs/dli/umn/dli_03_0047.html
@@ -12,7 +12,7 @@
diff --git a/docs/dli/umn/dli_03_0048.html b/docs/dli/umn/dli_03_0048.html
index 6f98e404..91fcb8fa 100644
--- a/docs/dli/umn/dli_03_0048.html
+++ b/docs/dli/umn/dli_03_0048.html
@@ -10,7 +10,7 @@ insert into es2 select * from ssource;
diff --git a/docs/dli/umn/dli_03_0049.html b/docs/dli/umn/dli_03_0049.html
index c3173cdd..21acaedc 100644
--- a/docs/dli/umn/dli_03_0049.html
+++ b/docs/dli/umn/dli_03_0049.html
@@ -4,27 +4,9 @@
diff --git a/docs/dli/umn/dli_03_0054.html b/docs/dli/umn/dli_03_0054.html
index 74e74eb9..18bfcccc 100644
--- a/docs/dli/umn/dli_03_0054.html
+++ b/docs/dli/umn/dli_03_0054.html
@@ -4,21 +4,9 @@
diff --git a/docs/dli/umn/dli_03_0057.html b/docs/dli/umn/dli_03_0057.html
index a02d6647..e9910c00 100644
--- a/docs/dli/umn/dli_03_0057.html
+++ b/docs/dli/umn/dli_03_0057.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0061.html b/docs/dli/umn/dli_03_0061.html
index a66ec3f3..beab1114 100644
--- a/docs/dli/umn/dli_03_0061.html
+++ b/docs/dli/umn/dli_03_0061.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0064.html b/docs/dli/umn/dli_03_0064.html
index cb086139..a8a7300d 100644
--- a/docs/dli/umn/dli_03_0064.html
+++ b/docs/dli/umn/dli_03_0064.html
@@ -10,7 +10,7 @@
diff --git a/docs/dli/umn/dli_03_0065.html b/docs/dli/umn/dli_03_0065.html
index 7171d5a8..b6b9ddc9 100644
--- a/docs/dli/umn/dli_03_0065.html
+++ b/docs/dli/umn/dli_03_0065.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0066.html b/docs/dli/umn/dli_03_0066.html
index 6701df2c..a7e842fb 100644
--- a/docs/dli/umn/dli_03_0066.html
+++ b/docs/dli/umn/dli_03_0066.html
@@ -10,7 +10,7 @@
diff --git a/docs/dli/umn/dli_03_0067.html b/docs/dli/umn/dli_03_0067.html
index f4bd398b..4d9f150a 100644
--- a/docs/dli/umn/dli_03_0067.html
+++ b/docs/dli/umn/dli_03_0067.html
@@ -12,7 +12,7 @@
diff --git a/docs/dli/umn/dli_03_0068.html b/docs/dli/umn/dli_03_0068.html
index b5a5866a..fe77615b 100644
--- a/docs/dli/umn/dli_03_0068.html
+++ b/docs/dli/umn/dli_03_0068.html
@@ -11,7 +11,7 @@ st.execute("set spark.sql.shuffle.partitions=20")
diff --git a/docs/dli/umn/dli_03_0069.html b/docs/dli/umn/dli_03_0069.html
index 77d25473..7bcd07c6 100644
--- a/docs/dli/umn/dli_03_0069.html
+++ b/docs/dli/umn/dli_03_0069.html
@@ -27,7 +27,7 @@ WHERE
diff --git a/docs/dli/umn/dli_03_0071.html b/docs/dli/umn/dli_03_0071.html
index 32f1d276..659ff90c 100644
--- a/docs/dli/umn/dli_03_0071.html
+++ b/docs/dli/umn/dli_03_0071.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0072.html b/docs/dli/umn/dli_03_0072.html
index 00196fa3..754c3551 100644
--- a/docs/dli/umn/dli_03_0072.html
+++ b/docs/dli/umn/dli_03_0072.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0075.html b/docs/dli/umn/dli_03_0075.html
index 04db3484..b059069a 100644
--- a/docs/dli/umn/dli_03_0075.html
+++ b/docs/dli/umn/dli_03_0075.html
@@ -58,7 +58,7 @@
diff --git a/docs/dli/umn/dli_03_0076.html b/docs/dli/umn/dli_03_0076.html
index d103ef63..be60c760 100644
--- a/docs/dli/umn/dli_03_0076.html
+++ b/docs/dli/umn/dli_03_0076.html
@@ -9,7 +9,7 @@
diff --git a/docs/dli/umn/dli_03_0077.html b/docs/dli/umn/dli_03_0077.html
index 5e62d7cc..a60751ac 100644
--- a/docs/dli/umn/dli_03_0077.html
+++ b/docs/dli/umn/dli_03_0077.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0080.html b/docs/dli/umn/dli_03_0080.html
index 856b41f5..0038f27f 100644
--- a/docs/dli/umn/dli_03_0080.html
+++ b/docs/dli/umn/dli_03_0080.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0082.html b/docs/dli/umn/dli_03_0082.html
index 75b57c5e..bfcb9467 100644
--- a/docs/dli/umn/dli_03_0082.html
+++ b/docs/dli/umn/dli_03_0082.html
@@ -10,7 +10,7 @@
diff --git a/docs/dli/umn/dli_03_0083.html b/docs/dli/umn/dli_03_0083.html
index 61b2dbaa..ec783ec2 100644
--- a/docs/dli/umn/dli_03_0083.html
+++ b/docs/dli/umn/dli_03_0083.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0085.html b/docs/dli/umn/dli_03_0085.html
index 6ab75c37..92ede8cc 100644
--- a/docs/dli/umn/dli_03_0085.html
+++ b/docs/dli/umn/dli_03_0085.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0086.html b/docs/dli/umn/dli_03_0086.html
index 2a126246..f67a1c92 100644
--- a/docs/dli/umn/dli_03_0086.html
+++ b/docs/dli/umn/dli_03_0086.html
@@ -9,7 +9,7 @@ select * FROM tablename distribute by rand()
diff --git a/docs/dli/umn/dli_03_0087.html b/docs/dli/umn/dli_03_0087.html
index aca9ae27..c429a6a1 100644
--- a/docs/dli/umn/dli_03_0087.html
+++ b/docs/dli/umn/dli_03_0087.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0088.html b/docs/dli/umn/dli_03_0088.html
index 3e6babb9..26d22ac4 100644
--- a/docs/dli/umn/dli_03_0088.html
+++ b/docs/dli/umn/dli_03_0088.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0089.html b/docs/dli/umn/dli_03_0089.html
index 7ce71038..ab9cf67f 100644
--- a/docs/dli/umn/dli_03_0089.html
+++ b/docs/dli/umn/dli_03_0089.html
@@ -3,7 +3,7 @@
How Do I Create an OBS Partitioned Table for a Flink SQL Job?
ScenarioWhen using a Flink SQL job, you need to create an OBS partition table for subsequent batch processing.
- ProcedureIn the following example, the day field is used as the partition field with the parquet encoding format (only the parquet format is supported currently) to dump car_info data to OBS.
+ ProcedureIn the following example, the day field is used as the partition field with the parquet encoding format to dump car_info data to OBS.
diff --git a/docs/dli/umn/dli_03_0090.html b/docs/dli/umn/dli_03_0090.html
index cb4f81c1..ab404100 100644
--- a/docs/dli/umn/dli_03_0090.html
+++ b/docs/dli/umn/dli_03_0090.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0091.html b/docs/dli/umn/dli_03_0091.html
index b7e0b770..3eaa1067 100644
--- a/docs/dli/umn/dli_03_0091.html
+++ b/docs/dli/umn/dli_03_0091.html
@@ -9,7 +9,7 @@
diff --git a/docs/dli/umn/dli_03_0092.html b/docs/dli/umn/dli_03_0092.html
index 99dcc82c..702a907f 100644
--- a/docs/dli/umn/dli_03_0092.html
+++ b/docs/dli/umn/dli_03_0092.html
@@ -14,7 +14,7 @@ LOCATION 'obs://akc-bigdata/akdc.db'
diff --git a/docs/dli/umn/dli_03_0093.html b/docs/dli/umn/dli_03_0093.html
index afd6ec18..4a8132e4 100644
--- a/docs/dli/umn/dli_03_0093.html
+++ b/docs/dli/umn/dli_03_0093.html
@@ -20,7 +20,7 @@ spark.sql.adaptive.skewedPartitionMaxSplits:10
diff --git a/docs/dli/umn/dli_03_0095.html b/docs/dli/umn/dli_03_0095.html
index 22a0b58f..93dfa7ec 100644
--- a/docs/dli/umn/dli_03_0095.html
+++ b/docs/dli/umn/dli_03_0095.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0096.html b/docs/dli/umn/dli_03_0096.html
index 0d854ca8..b4f4cdbd 100644
--- a/docs/dli/umn/dli_03_0096.html
+++ b/docs/dli/umn/dli_03_0096.html
@@ -10,7 +10,7 @@
diff --git a/docs/dli/umn/dli_03_0098.html b/docs/dli/umn/dli_03_0098.html
index 443e9011..12e37958 100644
--- a/docs/dli/umn/dli_03_0098.html
+++ b/docs/dli/umn/dli_03_0098.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0099.html b/docs/dli/umn/dli_03_0099.html
index 261ba5c7..2a7db5c6 100644
--- a/docs/dli/umn/dli_03_0099.html
+++ b/docs/dli/umn/dli_03_0099.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0100.html b/docs/dli/umn/dli_03_0100.html
index 21a0e117..55859cd2 100644
--- a/docs/dli/umn/dli_03_0100.html
+++ b/docs/dli/umn/dli_03_0100.html
@@ -67,7 +67,7 @@
diff --git a/docs/dli/umn/dli_03_0102.html b/docs/dli/umn/dli_03_0102.html
index 45c51a53..1ff20d94 100644
--- a/docs/dli/umn/dli_03_0102.html
+++ b/docs/dli/umn/dli_03_0102.html
@@ -15,7 +15,7 @@
diff --git a/docs/dli/umn/dli_03_0103.html b/docs/dli/umn/dli_03_0103.html
index 719eed80..bc81825e 100644
--- a/docs/dli/umn/dli_03_0103.html
+++ b/docs/dli/umn/dli_03_0103.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0105.html b/docs/dli/umn/dli_03_0105.html
index 4db45d8a..8673e9d6 100644
--- a/docs/dli/umn/dli_03_0105.html
+++ b/docs/dli/umn/dli_03_0105.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0106.html b/docs/dli/umn/dli_03_0106.html
index 04fd6e26..81ffcbc7 100644
--- a/docs/dli/umn/dli_03_0106.html
+++ b/docs/dli/umn/dli_03_0106.html
@@ -39,7 +39,7 @@
diff --git a/docs/dli/umn/dli_03_0107.html b/docs/dli/umn/dli_03_0107.html
index eeac9832..70a1a79a 100644
--- a/docs/dli/umn/dli_03_0107.html
+++ b/docs/dli/umn/dli_03_0107.html
@@ -30,7 +30,7 @@ counts.saveAsTextFile(out_file_name)
diff --git a/docs/dli/umn/dli_03_0108.html b/docs/dli/umn/dli_03_0108.html
index fbd8f2a1..f62f9c71 100644
--- a/docs/dli/umn/dli_03_0108.html
+++ b/docs/dli/umn/dli_03_0108.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0109.html b/docs/dli/umn/dli_03_0109.html
index bcaec919..171cebec 100644
--- a/docs/dli/umn/dli_03_0109.html
+++ b/docs/dli/umn/dli_03_0109.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0110.html b/docs/dli/umn/dli_03_0110.html
new file mode 100644
index 00000000..d80be8bb
--- /dev/null
+++ b/docs/dli/umn/dli_03_0110.html
@@ -0,0 +1,28 @@
+
+
+Datasource Connections
+
+
+
diff --git a/docs/dli/umn/dli_03_0111.html b/docs/dli/umn/dli_03_0111.html
index 43e8cbcf..76683518 100644
--- a/docs/dli/umn/dli_03_0111.html
+++ b/docs/dli/umn/dli_03_0111.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0112.html b/docs/dli/umn/dli_03_0112.html
new file mode 100644
index 00000000..38193fea
--- /dev/null
+++ b/docs/dli/umn/dli_03_0112.html
@@ -0,0 +1,20 @@
+
+
+Cross-Source Analysis
+
+
+
diff --git a/docs/dli/umn/dli_03_0115.html b/docs/dli/umn/dli_03_0115.html
index 2fa39828..0f4c635a 100644
--- a/docs/dli/umn/dli_03_0115.html
+++ b/docs/dli/umn/dli_03_0115.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0116.html b/docs/dli/umn/dli_03_0116.html
index 88ea396f..763ce600 100644
--- a/docs/dli/umn/dli_03_0116.html
+++ b/docs/dli/umn/dli_03_0116.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0117.html b/docs/dli/umn/dli_03_0117.html
index 8217dff6..3610b8ae 100644
--- a/docs/dli/umn/dli_03_0117.html
+++ b/docs/dli/umn/dli_03_0117.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0118.html b/docs/dli/umn/dli_03_0118.html
index 6da9f2ed..9a8ab5cc 100644
--- a/docs/dli/umn/dli_03_0118.html
+++ b/docs/dli/umn/dli_03_0118.html
@@ -30,7 +30,7 @@ object DliTest {
diff --git a/docs/dli/umn/dli_03_0119.html b/docs/dli/umn/dli_03_0119.html
index 43319121..5e0d016c 100644
--- a/docs/dli/umn/dli_03_0119.html
+++ b/docs/dli/umn/dli_03_0119.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0126.html b/docs/dli/umn/dli_03_0126.html
index b57d1317..67ee6d71 100644
--- a/docs/dli/umn/dli_03_0126.html
+++ b/docs/dli/umn/dli_03_0126.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0127.html b/docs/dli/umn/dli_03_0127.html
index cee710e2..c7ea12d1 100644
--- a/docs/dli/umn/dli_03_0127.html
+++ b/docs/dli/umn/dli_03_0127.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0128.html b/docs/dli/umn/dli_03_0128.html
index fcb0d421..bcf70760 100644
--- a/docs/dli/umn/dli_03_0128.html
+++ b/docs/dli/umn/dli_03_0128.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0129.html b/docs/dli/umn/dli_03_0129.html
index 0a4c3e09..7ec1a4d1 100644
--- a/docs/dli/umn/dli_03_0129.html
+++ b/docs/dli/umn/dli_03_0129.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0130.html b/docs/dli/umn/dli_03_0130.html
index 025ee34b..01cdffd7 100644
--- a/docs/dli/umn/dli_03_0130.html
+++ b/docs/dli/umn/dli_03_0130.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0131.html b/docs/dli/umn/dli_03_0131.html
new file mode 100644
index 00000000..eb34497c
--- /dev/null
+++ b/docs/dli/umn/dli_03_0131.html
@@ -0,0 +1,33 @@
+
+
+Flink SQL
+
+
+
diff --git a/docs/dli/umn/dli_03_0132.html b/docs/dli/umn/dli_03_0132.html
new file mode 100644
index 00000000..7666b9e8
--- /dev/null
+++ b/docs/dli/umn/dli_03_0132.html
@@ -0,0 +1,29 @@
+
+
+Flink Jar Jobs
+
+
+
diff --git a/docs/dli/umn/dli_03_0133.html b/docs/dli/umn/dli_03_0133.html
new file mode 100644
index 00000000..bac2b71a
--- /dev/null
+++ b/docs/dli/umn/dli_03_0133.html
@@ -0,0 +1,20 @@
+
+
+Performance Tuning
+
+
+
diff --git a/docs/dli/umn/dli_03_0135.html b/docs/dli/umn/dli_03_0135.html
new file mode 100644
index 00000000..06cbcf9b
--- /dev/null
+++ b/docs/dli/umn/dli_03_0135.html
@@ -0,0 +1,32 @@
+
+
+O&M Guide
+
+
+
diff --git a/docs/dli/umn/dli_03_0136.html b/docs/dli/umn/dli_03_0136.html
index 51717b4c..f6bad72b 100644
--- a/docs/dli/umn/dli_03_0136.html
+++ b/docs/dli/umn/dli_03_0136.html
@@ -59,7 +59,7 @@
diff --git a/docs/dli/umn/dli_03_0137.html b/docs/dli/umn/dli_03_0137.html
new file mode 100644
index 00000000..505c824d
--- /dev/null
+++ b/docs/dli/umn/dli_03_0137.html
@@ -0,0 +1,30 @@
+
+
+Usage
+
+
+
diff --git a/docs/dli/umn/dli_03_0138.html b/docs/dli/umn/dli_03_0138.html
index 6645c794..9db67a6f 100644
--- a/docs/dli/umn/dli_03_0138.html
+++ b/docs/dli/umn/dli_03_0138.html
@@ -9,7 +9,7 @@
diff --git a/docs/dli/umn/dli_03_0139.html b/docs/dli/umn/dli_03_0139.html
index 868918a9..288393ba 100644
--- a/docs/dli/umn/dli_03_0139.html
+++ b/docs/dli/umn/dli_03_0139.html
@@ -12,7 +12,7 @@
diff --git a/docs/dli/umn/dli_03_0140.html b/docs/dli/umn/dli_03_0140.html
index 5ed3b909..858d0a13 100644
--- a/docs/dli/umn/dli_03_0140.html
+++ b/docs/dli/umn/dli_03_0140.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0145.html b/docs/dli/umn/dli_03_0145.html
index 38a9e0b3..b3e548e2 100644
--- a/docs/dli/umn/dli_03_0145.html
+++ b/docs/dli/umn/dli_03_0145.html
@@ -11,7 +11,7 @@
diff --git a/docs/dli/umn/dli_03_0156.html b/docs/dli/umn/dli_03_0156.html
index de30c37a..9a15efd1 100644
--- a/docs/dli/umn/dli_03_0156.html
+++ b/docs/dli/umn/dli_03_0156.html
@@ -9,7 +9,7 @@
diff --git a/docs/dli/umn/dli_03_0157.html b/docs/dli/umn/dli_03_0157.html
index 1dd9f63b..cc92c3ac 100644
--- a/docs/dli/umn/dli_03_0157.html
+++ b/docs/dli/umn/dli_03_0157.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0159.html b/docs/dli/umn/dli_03_0159.html
index 17965ced..b50ba0ef 100644
--- a/docs/dli/umn/dli_03_0159.html
+++ b/docs/dli/umn/dli_03_0159.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0160.html b/docs/dli/umn/dli_03_0160.html
index 336b0e21..ff120b74 100644
--- a/docs/dli/umn/dli_03_0160.html
+++ b/docs/dli/umn/dli_03_0160.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0161.html b/docs/dli/umn/dli_03_0161.html
index c0f7e55c..8977e505 100644
--- a/docs/dli/umn/dli_03_0161.html
+++ b/docs/dli/umn/dli_03_0161.html
@@ -16,7 +16,7 @@
diff --git a/docs/dli/umn/dli_03_0162.html b/docs/dli/umn/dli_03_0162.html
index 2b7e9456..61db61cb 100644
--- a/docs/dli/umn/dli_03_0162.html
+++ b/docs/dli/umn/dli_03_0162.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0163.html b/docs/dli/umn/dli_03_0163.html
new file mode 100644
index 00000000..0d8e6733
--- /dev/null
+++ b/docs/dli/umn/dli_03_0163.html
@@ -0,0 +1,16 @@
+
+
+Usage
+
+
+
diff --git a/docs/dli/umn/dli_03_0164.html b/docs/dli/umn/dli_03_0164.html
index fe668a6c..986dfcc0 100644
--- a/docs/dli/umn/dli_03_0164.html
+++ b/docs/dli/umn/dli_03_0164.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0165.html b/docs/dli/umn/dli_03_0165.html
index 2d1a21d7..3bd7d1cc 100644
--- a/docs/dli/umn/dli_03_0165.html
+++ b/docs/dli/umn/dli_03_0165.html
@@ -11,7 +11,7 @@
diff --git a/docs/dli/umn/dli_03_0166.html b/docs/dli/umn/dli_03_0166.html
index 23a4a792..e8b1d4e5 100644
--- a/docs/dli/umn/dli_03_0166.html
+++ b/docs/dli/umn/dli_03_0166.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0167.html b/docs/dli/umn/dli_03_0167.html
index 28565b0c..115d4b0b 100644
--- a/docs/dli/umn/dli_03_0167.html
+++ b/docs/dli/umn/dli_03_0167.html
@@ -9,7 +9,7 @@
diff --git a/docs/dli/umn/dli_03_0168.html b/docs/dli/umn/dli_03_0168.html
index 9a2a0412..16f10ff5 100644
--- a/docs/dli/umn/dli_03_0168.html
+++ b/docs/dli/umn/dli_03_0168.html
@@ -34,7 +34,7 @@
diff --git a/docs/dli/umn/dli_03_0169.html b/docs/dli/umn/dli_03_0169.html
index f3f3a3b1..bb473ba3 100644
--- a/docs/dli/umn/dli_03_0169.html
+++ b/docs/dli/umn/dli_03_0169.html
@@ -14,7 +14,7 @@
diff --git a/docs/dli/umn/dli_03_0170.html b/docs/dli/umn/dli_03_0170.html
index a3a6f625..8096c214 100644
--- a/docs/dli/umn/dli_03_0170.html
+++ b/docs/dli/umn/dli_03_0170.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0171.html b/docs/dli/umn/dli_03_0171.html
index 4193548c..64370860 100644
--- a/docs/dli/umn/dli_03_0171.html
+++ b/docs/dli/umn/dli_03_0171.html
@@ -13,7 +13,7 @@
diff --git a/docs/dli/umn/dli_03_0172.html b/docs/dli/umn/dli_03_0172.html
index 8d4d729d..2abde769 100644
--- a/docs/dli/umn/dli_03_0172.html
+++ b/docs/dli/umn/dli_03_0172.html
@@ -19,7 +19,7 @@ at java.lang.Thread.run(Thread.java:748)
diff --git a/docs/dli/umn/dli_03_0173.html b/docs/dli/umn/dli_03_0173.html
index 0e8287f0..31100079 100644
--- a/docs/dli/umn/dli_03_0173.html
+++ b/docs/dli/umn/dli_03_0173.html
@@ -16,7 +16,7 @@ Cause by: ObsException: com.obs.services.exception.ObsException: OBSs servcie Er
diff --git a/docs/dli/umn/dli_03_0174.html b/docs/dli/umn/dli_03_0174.html
index 5f70d0a2..ea0c3b6f 100644
--- a/docs/dli/umn/dli_03_0174.html
+++ b/docs/dli/umn/dli_03_0174.html
@@ -11,7 +11,7 @@
diff --git a/docs/dli/umn/dli_03_0175.html b/docs/dli/umn/dli_03_0175.html
index 01560ca1..c4481786 100644
--- a/docs/dli/umn/dli_03_0175.html
+++ b/docs/dli/umn/dli_03_0175.html
@@ -11,7 +11,7 @@
diff --git a/docs/dli/umn/dli_03_0176.html b/docs/dli/umn/dli_03_0176.html
index 96720398..672d6328 100644
--- a/docs/dli/umn/dli_03_0176.html
+++ b/docs/dli/umn/dli_03_0176.html
@@ -11,7 +11,7 @@
diff --git a/docs/dli/umn/dli_03_0177.html b/docs/dli/umn/dli_03_0177.html
index e446007a..e44a3af9 100644
--- a/docs/dli/umn/dli_03_0177.html
+++ b/docs/dli/umn/dli_03_0177.html
@@ -10,7 +10,7 @@
diff --git a/docs/dli/umn/dli_03_0179.html b/docs/dli/umn/dli_03_0179.html
index 6b386618..c5904560 100644
--- a/docs/dli/umn/dli_03_0179.html
+++ b/docs/dli/umn/dli_03_0179.html
@@ -6,7 +6,7 @@
Fault LocatingThe issues here are described in order of how likely they are to occur.
Troubleshoot the issue by ruling out the causes described here, one by one.
-
+
Check Whether a Port Number Is Added to the End of the Domain Name or IP AddressThe port number is required for the connectivity test.
The following example tests the connectivity between a queue and a specified RDS DB instance. The RDS DB instance uses port 3306.
@@ -15,17 +15,14 @@
Check Whether the Information of the Peer VPC and Subnet Are Correct.When you create an enhanced datasource connection, you need to specify the peer VPC and subnet.
For example, to test the connectivity between a queue and a specified RDS DB instance, you need to specify the RDS VPC and subnet information.
- Check Whether the CIDR Block of the Queue Overlaps That of the Data SourceThe CIDR block of the DLI queue bound with a datasource connection cannot overlap the CIDR block of the data source.
+ Check Whether the CIDR Block of the Queue Overlaps with That of the Data SourceThe CIDR block of the DLI queue bound with a datasource connection cannot overlap the CIDR block of the data source.
You can check whether they overlap by viewing the connection logs.
CIDR block conflicts of queue A and queue B. In this example, queue B is bound to an enhanced datasource connection to data source C. Therefore, a message is displayed, indicating that the network segment of queue A conflicts with that of data source C. As a result, a new enhanced datasource connection cannot be established.
Solution: Modify the CIDR block of the queue or create another queue.
Planing the CIDR blocks for your queues helps you to avoid this problem.
Check Whether the VPC Administrator Permission Is Granted to DLIView the connection logs to check whether there is the required permission.
- Figure 1 and Figure 2 show the logs when subnet ID and route ID of the destination cannot be obtained because there is no permission.
Solution: Grant DLI the VPC Administrator permission and cancel the IAM ReadOnlyAccess authorization.
- Figure 1 Viewing connection logs
- Figure 2 Viewing connection logs
Check Whether the Destination Security Group Allows Access from the CIDR Block of the QueueTo connect to Kafka, GaussDB(DWS), and RDS instances, add security group rules for the DLI CIDR block to the security group where the instances belong. For example, to connect a queue to RDS, perform the following operations: - Log in to the DLI console, choose Resources > Queue Management in the navigation pane on the left. On the displayed page, select the target queue, and click
 to expand the row containing the target queue to view its CIDR block. - On the Instance Management page of the RDS console, click the instance name. In the Connection Information area, locate Database Port to obtain the port number of the RDS DB instance.
- In the Connection Information area locate the Security Group and click the group name to switch to the security group management page. Select the Inbound Rules tab and click Add Rule. Set the priority to 1, protocol to TCP, port to the database port number, and source to the CIDR block of the DLI queue. Click OK.
@@ -39,7 +36,7 @@
diff --git a/docs/dli/umn/dli_03_0180.html b/docs/dli/umn/dli_03_0180.html
index 1e862dfb..c8502d37 100644
--- a/docs/dli/umn/dli_03_0180.html
+++ b/docs/dli/umn/dli_03_0180.html
@@ -9,7 +9,7 @@
diff --git a/docs/dli/umn/dli_03_0181.html b/docs/dli/umn/dli_03_0181.html
index b3c9f3a1..c4c1ba63 100644
--- a/docs/dli/umn/dli_03_0181.html
+++ b/docs/dli/umn/dli_03_0181.html
@@ -18,7 +18,7 @@ bb" null null
Job Development
+
+
+
diff --git a/docs/dli/umn/dli_03_0206.html b/docs/dli/umn/dli_03_0206.html
new file mode 100644
index 00000000..42657827
--- /dev/null
+++ b/docs/dli/umn/dli_03_0206.html
@@ -0,0 +1,40 @@
+
+
+Job O&M Errors
+
+
+
diff --git a/docs/dli/umn/dli_03_0207.html b/docs/dli/umn/dli_03_0207.html
index 2501b1ed..ed8045b0 100644
--- a/docs/dli/umn/dli_03_0207.html
+++ b/docs/dli/umn/dli_03_0207.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0208.html b/docs/dli/umn/dli_03_0208.html
index be2b8906..5859cee2 100644
--- a/docs/dli/umn/dli_03_0208.html
+++ b/docs/dli/umn/dli_03_0208.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0209.html b/docs/dli/umn/dli_03_0209.html
index 22bac4ff..0bdd5b03 100644
--- a/docs/dli/umn/dli_03_0209.html
+++ b/docs/dli/umn/dli_03_0209.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0210.html b/docs/dli/umn/dli_03_0210.html
index 05971e57..ffb212f2 100644
--- a/docs/dli/umn/dli_03_0210.html
+++ b/docs/dli/umn/dli_03_0210.html
@@ -9,7 +9,7 @@
diff --git a/docs/dli/umn/dli_03_0211.html b/docs/dli/umn/dli_03_0211.html
new file mode 100644
index 00000000..811df367
--- /dev/null
+++ b/docs/dli/umn/dli_03_0211.html
@@ -0,0 +1,50 @@
+
+
+O&M Guide
+
+
+
diff --git a/docs/dli/umn/dli_03_0212.html b/docs/dli/umn/dli_03_0212.html
index 04d2fc0f..f21abd78 100644
--- a/docs/dli/umn/dli_03_0212.html
+++ b/docs/dli/umn/dli_03_0212.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0213.html b/docs/dli/umn/dli_03_0213.html
index beda0b22..fa24d027 100644
--- a/docs/dli/umn/dli_03_0213.html
+++ b/docs/dli/umn/dli_03_0213.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0214.html b/docs/dli/umn/dli_03_0214.html
index e77830be..80ec38bf 100644
--- a/docs/dli/umn/dli_03_0214.html
+++ b/docs/dli/umn/dli_03_0214.html
@@ -8,7 +8,7 @@
diff --git a/docs/dli/umn/dli_03_0215.html b/docs/dli/umn/dli_03_0215.html
index c9c80f89..166831ef 100644
--- a/docs/dli/umn/dli_03_0215.html
+++ b/docs/dli/umn/dli_03_0215.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0216.html b/docs/dli/umn/dli_03_0216.html
new file mode 100644
index 00000000..6c45e83b
--- /dev/null
+++ b/docs/dli/umn/dli_03_0216.html
@@ -0,0 +1,16 @@
+
+
+Usage
+
+
+
diff --git a/docs/dli/umn/dli_03_0217.html b/docs/dli/umn/dli_03_0217.html
new file mode 100644
index 00000000..6af3d3a9
--- /dev/null
+++ b/docs/dli/umn/dli_03_0217.html
@@ -0,0 +1,30 @@
+
+
+Job Development
+
+
+
diff --git a/docs/dli/umn/dli_03_0218.html b/docs/dli/umn/dli_03_0218.html
new file mode 100644
index 00000000..215efdd9
--- /dev/null
+++ b/docs/dli/umn/dli_03_0218.html
@@ -0,0 +1,24 @@
+
+
+Job O&M Errors
+
+
+
diff --git a/docs/dli/umn/dli_03_0219.html b/docs/dli/umn/dli_03_0219.html
new file mode 100644
index 00000000..50e85426
--- /dev/null
+++ b/docs/dli/umn/dli_03_0219.html
@@ -0,0 +1,18 @@
+
+
+O&M Guide
+
+
+
diff --git a/docs/dli/umn/dli_03_0220.html b/docs/dli/umn/dli_03_0220.html
index e64c7094..a68060e7 100644
--- a/docs/dli/umn/dli_03_0220.html
+++ b/docs/dli/umn/dli_03_0220.html
@@ -10,7 +10,7 @@
diff --git a/docs/dli/umn/dli_03_0221.html b/docs/dli/umn/dli_03_0221.html
new file mode 100644
index 00000000..46cfdd36
--- /dev/null
+++ b/docs/dli/umn/dli_03_0221.html
@@ -0,0 +1,32 @@
+
+
+Usage
+
+
+
diff --git a/docs/dli/umn/dli_03_0222.html b/docs/dli/umn/dli_03_0222.html
new file mode 100644
index 00000000..1c77d15d
--- /dev/null
+++ b/docs/dli/umn/dli_03_0222.html
@@ -0,0 +1,18 @@
+
+
+Job Management
+
+
+
diff --git a/docs/dli/umn/dli_03_0223.html b/docs/dli/umn/dli_03_0223.html
new file mode 100644
index 00000000..7ec2c8e7
--- /dev/null
+++ b/docs/dli/umn/dli_03_0223.html
@@ -0,0 +1,17 @@
+
+
+Usage
+
+
+
diff --git a/docs/dli/umn/dli_03_0226.html b/docs/dli/umn/dli_03_0226.html
new file mode 100644
index 00000000..c18d1118
--- /dev/null
+++ b/docs/dli/umn/dli_03_0226.html
@@ -0,0 +1,26 @@
+
+
+O&M Guide
+
+
+
diff --git a/docs/dli/umn/dli_03_0227.html b/docs/dli/umn/dli_03_0227.html
index 63056f78..5ad8021c 100644
--- a/docs/dli/umn/dli_03_0227.html
+++ b/docs/dli/umn/dli_03_0227.html
@@ -10,7 +10,7 @@
diff --git a/docs/dli/umn/dli_03_0228.html b/docs/dli/umn/dli_03_0228.html
index e711254a..48e74058 100644
--- a/docs/dli/umn/dli_03_0228.html
+++ b/docs/dli/umn/dli_03_0228.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0229.html b/docs/dli/umn/dli_03_0229.html
new file mode 100644
index 00000000..48993c0e
--- /dev/null
+++ b/docs/dli/umn/dli_03_0229.html
@@ -0,0 +1,22 @@
+
+
+Usage
+
+
+
diff --git a/docs/dli/umn/dli_03_0230.html b/docs/dli/umn/dli_03_0230.html
new file mode 100644
index 00000000..77622dfe
--- /dev/null
+++ b/docs/dli/umn/dli_03_0230.html
@@ -0,0 +1,30 @@
+
+
+O&M Guide
+
+
+
diff --git a/docs/dli/umn/dli_03_0231.html b/docs/dli/umn/dli_03_0231.html
index 00d4db3e..ae0efc8a 100644
--- a/docs/dli/umn/dli_03_0231.html
+++ b/docs/dli/umn/dli_03_0231.html
@@ -18,7 +18,7 @@
diff --git a/docs/dli/umn/dli_03_0232.html b/docs/dli/umn/dli_03_0232.html
index 77bb0950..c1eef455 100644
--- a/docs/dli/umn/dli_03_0232.html
+++ b/docs/dli/umn/dli_03_0232.html
@@ -12,7 +12,7 @@
diff --git a/docs/dli/umn/dli_03_0233.html b/docs/dli/umn/dli_03_0233.html
index d470fb6c..b5329039 100644
--- a/docs/dli/umn/dli_03_0233.html
+++ b/docs/dli/umn/dli_03_0233.html
@@ -11,7 +11,7 @@
diff --git a/docs/dli/umn/dli_03_0234.html b/docs/dli/umn/dli_03_0234.html
index 3d77106b..d86c4e47 100644
--- a/docs/dli/umn/dli_03_0234.html
+++ b/docs/dli/umn/dli_03_0234.html
@@ -28,7 +28,7 @@
diff --git a/docs/dli/umn/dli_03_0235.html b/docs/dli/umn/dli_03_0235.html
index a4f87120..9252b110 100644
--- a/docs/dli/umn/dli_03_0235.html
+++ b/docs/dli/umn/dli_03_0235.html
@@ -10,7 +10,7 @@
diff --git a/docs/dli/umn/dli_03_0236.html b/docs/dli/umn/dli_03_0236.html
index c89f2ae6..424248ee 100644
--- a/docs/dli/umn/dli_03_0236.html
+++ b/docs/dli/umn/dli_03_0236.html
@@ -13,7 +13,7 @@
diff --git a/docs/dli/umn/dli_03_0237.html b/docs/dli/umn/dli_03_0237.html
index 7d8d5960..5275b91a 100644
--- a/docs/dli/umn/dli_03_0237.html
+++ b/docs/dli/umn/dli_03_0237.html
@@ -12,7 +12,7 @@
diff --git a/docs/dli/umn/dli_03_0238.html b/docs/dli/umn/dli_03_0238.html
index 464bd2f5..db83be76 100644
--- a/docs/dli/umn/dli_03_0238.html
+++ b/docs/dli/umn/dli_03_0238.html
@@ -14,7 +14,7 @@
diff --git a/docs/dli/umn/dli_03_0239.html b/docs/dli/umn/dli_03_0239.html
index 35a3643a..7b3890f6 100644
--- a/docs/dli/umn/dli_03_0239.html
+++ b/docs/dli/umn/dli_03_0239.html
@@ -16,7 +16,7 @@
diff --git a/docs/dli/umn/dli_03_0250.html b/docs/dli/umn/dli_03_0250.html
index 73f27613..147e7e44 100644
--- a/docs/dli/umn/dli_03_0250.html
+++ b/docs/dli/umn/dli_03_0250.html
@@ -18,7 +18,7 @@
diff --git a/docs/dli/umn/dli_03_0251.html b/docs/dli/umn/dli_03_0251.html
index 315ef407..ffa64a33 100644
--- a/docs/dli/umn/dli_03_0251.html
+++ b/docs/dli/umn/dli_03_0251.html
@@ -15,7 +15,7 @@
diff --git a/docs/dli/umn/dli_03_0252.html b/docs/dli/umn/dli_03_0252.html
index 52cb8c52..516f3d27 100644
--- a/docs/dli/umn/dli_03_0252.html
+++ b/docs/dli/umn/dli_03_0252.html
@@ -13,7 +13,7 @@
diff --git a/docs/dli/umn/dli_03_0253.html b/docs/dli/umn/dli_03_0253.html
index 9e28195e..af83c943 100644
--- a/docs/dli/umn/dli_03_0253.html
+++ b/docs/dli/umn/dli_03_0253.html
@@ -15,7 +15,7 @@ Detail: Failing row contains (400070309, 9.00, 25, null, 2020-09-22, 2020-09-23
diff --git a/docs/dli/umn/dli_03_0254.html b/docs/dli/umn/dli_03_0254.html
index 110e0911..f7363335 100644
--- a/docs/dli/umn/dli_03_0254.html
+++ b/docs/dli/umn/dli_03_0254.html
@@ -12,7 +12,7 @@
diff --git a/docs/dli/umn/dli_03_0256.html b/docs/dli/umn/dli_03_0256.html
new file mode 100644
index 00000000..f2a1739c
--- /dev/null
+++ b/docs/dli/umn/dli_03_0256.html
@@ -0,0 +1,32 @@
+
+
+Datasource Connection O&M
+
+
+
diff --git a/docs/dli/umn/dli_03_0257.html b/docs/dli/umn/dli_03_0257.html
index 0d252f32..650e62a2 100644
--- a/docs/dli/umn/dli_03_0257.html
+++ b/docs/dli/umn/dli_03_0257.html
@@ -6,7 +6,7 @@
diff --git a/docs/dli/umn/dli_03_0259.html b/docs/dli/umn/dli_03_0259.html
index 619f1243..5fee2c9a 100644
--- a/docs/dli/umn/dli_03_0259.html
+++ b/docs/dli/umn/dli_03_0259.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0260.html b/docs/dli/umn/dli_03_0260.html
index 512f49c7..2b6619b4 100644
--- a/docs/dli/umn/dli_03_0260.html
+++ b/docs/dli/umn/dli_03_0260.html
@@ -5,7 +5,7 @@
diff --git a/docs/dli/umn/dli_03_0261.html b/docs/dli/umn/dli_03_0261.html
new file mode 100644
index 00000000..e7d23c9c
--- /dev/null
+++ b/docs/dli/umn/dli_03_0261.html
@@ -0,0 +1,16 @@
+
+
+Privacy and Security
+
+
+
diff --git a/docs/dli/umn/dli_03_0263.html b/docs/dli/umn/dli_03_0263.html
index 9aa6428c..a552aaab 100644
--- a/docs/dli/umn/dli_03_0263.html
+++ b/docs/dli/umn/dli_03_0263.html
@@ -7,7 +7,7 @@
diff --git a/docs/dli/umn/dli_03_0264.html b/docs/dli/umn/dli_03_0264.html
index 5b527b08..420a8997 100644
--- a/docs/dli/umn/dli_03_0264.html
+++ b/docs/dli/umn/dli_03_0264.html
@@ -7,7 +7,7 @@
How Do I Apply for a Higher Quota?The system does not support online quota adjustment. To increase a resource quota, dial the hotline or send an email to the customer service. We will process your application and inform you of the progress by phone call or email.
Before dialing the hotline number or sending an email, ensure that the following information has been obtained:
- - Domain name, project name, and project ID
Log in to the management console using the cloud account, click the username in the upper right corner, select My Credentials from the drop-down list, and obtain the domain name, project name, and project ID on the My Credentials page.
+- Domain name, project name, and project ID
To obtain the preceding information, log in to the management console, click the username in the upper right corner, and choose My Credentials from the drop-down list.
- Quota information, including:
- ServiceName
- Quota type
- Required quota
Learn how to obtain the service hotline and email address.
@@ -15,7 +15,7 @@
How Can I Check the Actual and Used CUs for an Elastic Resource Pool as Well as the Required CUs for a Job?
+In daily big data analysis work, it is important to allocate and manage compute resources properly to provide a good job execution environment.
+ You can allocate resources and adjust task execution order based on the job's compute needs and data scale, and schedule different elastic resource pools or queues to adapt to different workloads. To ensure normal job execution, the CUs required for the submitted job should be less than or equal to the remaining available CUs in the elastic resource pool.
+ This section describes how to view the usage of compute resources in an elastic resource pool and the required CUs for a job.
+ Checking the Actual and Used CUs for an Elastic Resource Pool- Log in to the DLI management console.
- Choose Resources > Resource Pool.
Locate the target resource pool in the list and check its Actual CUs and Used CUs.
+- Actual CUs: number of CUs that can be allocated in the elastic resource pool.
- Used CUs: CUs that have been allocated to and used by the current elastic resource pool.
+To ensure normal job execution, the CUs required for the submitted job should be less than or equal to the remaining available CUs in the elastic resource pool.
+For details about the number of CUs required by different types of jobs, see Checking the Required CUs for a Job.
+
+
+ Checking the Required CUs for a Job
+
+ Federated Analysis of Heterogeneous Data Sources- Digital service transformation for car companies
In the face of new competition pressures and changes in travel services, car companies build the IoV cloud platform and IVI OS to streamline Internet applications and vehicle use scenarios, completing digital service transformation for car companies. This delivers better travel experience for vehicle owners, increases the competitiveness of car companies, and promotes sales growth. For example, DLI can be used to collect and analyze daily vehicle metric data (such as batteries, engines, tire pressure, and airbags), and give maintenance suggestions to vehicle owners in time.
- - Advantages
- No need for migration in multi-source data analysis: RDS stores the basic information about vehicles and vehicle owners, table store saves real-time vehicle location and health status, and DWS stores periodic metric statistics. DLI allows federated analysis on data from multiple sources without data migration.
- Tiered data storage: Car companies need to retain all historical data to support auditing and other services that require infrequent data access. Warm and cold data is stored in OBS and frequently accessed data is stored in DWS, reducing the overall storage cost.
- Rapid and agile alarm triggering: There are no special requirements for the CPU, memory, hard disk space, and bandwidth.
+ - Advantages
- No need for migration in multi-source data analysis: RDS stores the basic information about vehicles and vehicle owners, table store saves real-time vehicle location and health status, and GaussDB(DWS) stores periodic metric statistics. DLI allows federated analysis on data from multiple sources without data migration.
- Tiered data storage: Car companies need to retain all historical data to support auditing and other services that require infrequent data access. Warm and cold data is stored in OBS and frequently accessed data is stored in GaussDB(DWS), reducing the overall storage cost.
- Rapid and agile alarm triggering: There are no special requirements for the CPU, memory, hard disk space, and bandwidth.
Big Data ETL Processing- Carrier big data analysis
Carriers typically require petabytes, or even exabytes of data storage, for both structured (base station details) and unstructured (messages and communications) data. They need to be able to access the data with extremely low data latency. It is a major challenge to extract value from this data efficiently. DLI provides multi-mode engines such as batch processing and stream processing to break down data silos and perform unified data analysis.
diff --git a/docs/dli/umn/dli_07_0003.html b/docs/dli/umn/dli_07_0003.html
index 2fdeefd4..d9e76c70 100644
--- a/docs/dli/umn/dli_07_0003.html
+++ b/docs/dli/umn/dli_07_0003.html
@@ -10,8 +10,6 @@
MetadataMetadata is used to define data types. It describes information about the data, including the source, size, format, and other data features. In database fields, metadata interprets data content in the data warehouse.
Compute ResourceQueues in DLI are computing resources, which are the basis for using DLI. SQL jobs and Spark jobs performed by users require computing resources.
- Storage ResourceStorage resources in DLI are used to store data of databases and DLI tables. To import data to DLI, storage resources must be prepared. The storage resources reflect the volume of data you are allowed to store in DLI.
SQL JobSQL job refers to the SQL statement executed in the SQL job editor. It serves as the execution entity used for performing operations, such as importing and exporting data, in the SQL job editor.
diff --git a/docs/dli/umn/dli_07_0005.html b/docs/dli/umn/dli_07_0005.html
index 9fd0c057..a96dfde7 100644
--- a/docs/dli/umn/dli_07_0005.html
+++ b/docs/dli/umn/dli_07_0005.html
@@ -11,6 +11,11 @@
For more constraints on using a DLI queue, see Queue Overview.
On Elastic Resource Pools- The region of an elastic resource pool cannot be changed.
- Jobs of Flink 1.10 or later can run in elastic resource pools.
- The network segment of an elastic resource pool cannot be changed after being set.
- You can only view the scaling history of resource pools in the last 30 days.
- Elastic resource pools cannot access the Internet.
+
+
+ For more constraints on elastic resource pools, see Elastic Resource Pool Overview.
+ On Resources- Database
- default is the database built in DLI. You cannot create a database named default.
- DLI supports a maximum of 50 databases.
- Table
- DLI supports a maximum of 5,000 tables.
- DLI supports the following table types:
- MANAGED: Data is stored in a DLI table.
- EXTERNAL: Data is stored in an OBS table.
- View: A view can only be created using SQL statements.
- Datasource table: The table type is also EXTERNAL.
- You cannot specify a storage path when creating a DLI table.
diff --git a/docs/dli/umn/dli_07_0006.html b/docs/dli/umn/dli_07_0006.html
index 0fedc548..732c4d81 100644
--- a/docs/dli/umn/dli_07_0006.html
+++ b/docs/dli/umn/dli_07_0006.html
@@ -645,6 +645,22 @@
√
|
|
+Enhanced datasource connection
+ |
+BIND_QUEUE
+ |
+Binding an enhanced datasource connection to a queue
+It is only used to grant permissions across projects.
+ |
+×
+ |
+×
+ |
+×
+ |
+×
+ |
+
diff --git a/docs/dli/umn/dli_07_0009.html b/docs/dli/umn/dli_07_0009.html
index c834bc96..bc4ad33f 100644
--- a/docs/dli/umn/dli_07_0009.html
+++ b/docs/dli/umn/dli_07_0009.html
@@ -10,7 +10,7 @@
How Do I Apply for a Higher Quota?The system does not support online quota adjustment. To increase a resource quota, dial the hotline or send an email to the customer service. We will process your application and inform you of the progress by phone call or email.
Before dialing the hotline number or sending an email, ensure that the following information has been obtained:
- - Domain name, project name, and project ID
Log in to the management console using the cloud account, click the username in the upper right corner, select My Credentials from the drop-down list, and obtain the domain name, project name, and project ID on the My Credentials page.
+- Domain name, project name, and project ID
To obtain the preceding information, log in to the management console, click the username in the upper right corner, and choose My Credentials from the drop-down list.
- Quota information, including:
- ServiceName
- Quota type
- Required quota
Learn how to obtain the service hotline and email address.
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next to Queues.
in the middle pane to refresh the database list. The new database db1 is displayed in the list.
beside Databases.
on the right to create a table in the current database.
on the right of the database and choose Create Table from the shortcut menu to create a table in the current database.
