Sql
Transform plugin : Sql [Spark]
Description
Use SQL to process data and support Spark's rich UDF functions
Options
| name | type | required | default value |
|---|---|---|---|
| sql | string | yes | - |
| common-options | string | no | - |
sql [string]
SQL statement, the table name used in SQL is the result_table_name configured in the Source or Transform plugin
common options [string]
Transform plugin common parameters, please refer to Transform Plugin for details
Examples
sql {
sql = "select username, address from user_info",
}
Use the SQL plugin for field deletion. Only the
usernameandaddressfields are reserved, and the remaining fields will be discarded.user_infois theresult_table_nameconfigured by the previous plugin
sql {
sql = "select substring(telephone, 0, 10) from user_info",
}
Use SQL plugin for data processing, use substring functions to intercept the
telephonefield
sql {
sql = "select avg(age) from user_info",
table_name = "user_info"
}
Use SQL plugin for data aggregation, use avg functions to perform aggregation operations on the original data set, and take out the average value of the
agefield