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Lu, Huayi e6fa411af0 DWS DEV 830.201 version 
Reviewed-by: Pruthi, Vineet <vineet.pruthi@t-systems.com>
Co-authored-by: Lu, Huayi <luhuayi@huawei.com>
Co-committed-by: Lu, Huayi <luhuayi@huawei.com>
2024-05-16 07:24:04 +00:00

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Selecting a Data type

You can use data types with the following features to improve efficiency:

  1. Data types that boost execution efficiency

    Generally, the calculation of integers (including common comparison calculations, such as =, >, <, ≥, ≤, and ≠ and GROUP BY) is more efficient than that of strings and floating point numbers. For example, if you need to perform a point query on a column-store table whose NUMERIC column is used as a filter criterion, the query will take over 10 seconds. If you change the data type from NUMERIC to INT, the query takes only about 1.8 seconds.

  2. Data types with a short length

    Data types with short length reduce both the data file size and the memory used for computing, improving the I/O and computing performance. For example, use SMALLINT instead of INT, and INT instead of BIGINT.

  3. Same data type for a join

    You are advised to use the same data type for a join. To join columns with different data types, the database needs to convert them to the same type, which leads to additional performance overheads.