SQL

SQL transform plugin

Description

Use SQL to transform given input row.

SQL transform use memory SQL engine, we can via SQL functions and ability of SQL engine to implement the transform task.

Options

name	type	required	default value
plugin_input	string	yes	-
plugin_output	string	yes	-
query	string	yes	-

plugin_input [string]

The source table name, the query SQL table name must match this field.

query [string]

The query SQL, it's a simple SQL supported base function and criteria filter operation. But the complex SQL unsupported yet, include: multi source table/rows JOIN and AGGREGATE operation and the like.

the query expression can be select [table_name.]column_a to query the column that named column_a. and the table name is optional.
or select c_row.c_inner_row.column_b to query the inline struct column that named column_b within c_row column and c_inner_row column. In this query expression, can't have table name.

Example

The data read from source is a table like this:

id	name	age
1	Joy Ding	20
2	May Ding	21
3	Kin Dom	24
4	Joy Dom	22

We use SQL query to transform the source data like this:

transform {
  Sql {
    plugin_input = "fake"
    plugin_output = "fake1"
    query = "select id, concat(name, '_') as name, age+1 as age from dual where id>0"
  }
}

Then the data in result table fake1 will update to

id	name	age
1	Joy Ding_	21
2	May Ding_	22
3	Kin Dom_	25
4	Joy Dom_	23

Struct query

if your upstream data schema is like this:

source {
  FakeSource {
    plugin_output = "fake"
    row.num = 100
    string.template = ["innerQuery"]
    schema = {
      fields {
        name = "string"
        c_date = "date"
        c_row = {
          c_inner_row = {
            c_inner_int = "int"
            c_inner_string = "string"
            c_inner_timestamp = "timestamp"
            c_map_1 = "map<string, string>"
            c_map_2 = "map<string, map<string,string>>"
          }
          c_string = "string"
        }
      }
    }
  }
}

Those query all are valid:

select 
name,
c_date,
c_row,
c_row.c_inner_row,
c_row.c_string,
c_row.c_inner_row.c_inner_int,
c_row.c_inner_row.c_inner_string,
c_row.c_inner_row.c_inner_timestamp,
c_row.c_inner_row.c_map_1,
c_row.c_inner_row.c_map_1.some_key

But this query are not valid:

select 
c_row.c_inner_row.c_map_2.some_key.inner_map_key

The map must be the latest struct, can't query the nesting map.

Job Config Example

env {
  job.mode = "BATCH"
}

source {
  FakeSource {
    plugin_output = "fake"
    row.num = 100
    schema = {
      fields {
        id = "int"
        name = "string"
        age = "int"
      }
    }
  }
}

transform {
  Sql {
    plugin_input = "fake"
    plugin_output = "fake1"
    query = "select id, concat(name, '_') as name, age+1 as age from dual where id>0"
  }
}

sink {
  Console {
    plugin_input = "fake1"
  }
}

Changelog

• Support struct query

new version

• Add SQL Transform Connector