When Spark2x accesses the DataSource table created by Spark1.5, a message is displayed indicating that schema information cannot be obtained. As a result, the table cannot be accessed. Why?
This is because the formats of the DataSource table information stored in Spark2x and Spark1.5 are inconsistent. Spark 1.5 divides schema information into multiple parts and uses path.park.0 as the key for storage. Spark 1.5 reads information from each part and reassembles the information into complete one. Spark2x directly uses the corresponding key to obtain the corresponding information. In this case, when Spark2x reads the DataSource table created by Spark1.5, the information corresponding to the key cannot be read. As a result, the DataSource table information fails to be parsed.
When processing Hive tables, Spark2x and Spark1.5 use the same storage mode. Therefore, Spark2x can directly read tables created by Spark1.5.
In Spark2x, create a foreign table to point to the actual data in the Spark1.5 table. In this way, the DataSource table created by Spark1.5 can be read in Spark2x. In addition, after Spark1.5 updates data, Spark2x can detect the change. The reverse is also true. In this way, Spark2x can access the DataSource table created by Spark1.5.