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https://issues.apache.org/jira/browse/FLINK-22118?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Flink Jira Bot updated FLINK-22118:
-----------------------------------
Labels: auto-deprioritized-major auto-deprioritized-minor (was:
auto-deprioritized-major stale-minor)
Priority: Not a Priority (was: Minor)
This issue was labeled "stale-minor" 7 days ago and has not received any
updates so it is being deprioritized. If this ticket is actually Minor, please
raise the priority and ask a committer to assign you the issue or revive the
public discussion.
> Always apply projection push down in blink planner
> --------------------------------------------------
>
> Key: FLINK-22118
> URL: https://issues.apache.org/jira/browse/FLINK-22118
> Project: Flink
> Issue Type: Improvement
> Components: Table SQL / Planner
> Affects Versions: 1.13.0
> Reporter: Shengkai Fang
> Priority: Not a Priority
> Labels: auto-deprioritized-major, auto-deprioritized-minor
>
> Please add the case in `TableSourceTest`.
> {code:java}
> s"""
> |CREATE TABLE NestedItemTable (
> | `id` INT,
> | `result` ROW<
> | `data_arr` ROW<`value` BIGINT> ARRAY,
> | `data_map` MAP<STRING, ROW<`value` BIGINT>>>,
> | ) WITH (
> | 'connector' = 'values',
> | 'nested-projection-supported' = 'true',
> | 'bounded' = 'true'
> | )
> |""".stripMargin
> util.tableEnv.executeSql(ddl4)
> util.verifyExecPlan(
> s"""
> |SELECT
> | `result`.`data_arr`[`id`].`value`,
> | `result`.`data_map`['item'].`value`
> |FROM NestedItemTable
> |""".stripMargin
> )
> {code}
> we can get optimized plan
> {code:java}
> Calc(select=[ITEM(result.data_arr, id).value AS EXPR$0, ITEM(result.data_map,
> _UTF-16LE'item').value AS EXPR$1])
> +- TableSourceScan(table=[[default_catalog, default_database,
> NestedItemTable]], fields=[id, result])
> {code}
> but expected is
> {code:java}
> Calc(select=[ITEM(result_data_arr, id).value AS EXPR$0, ITEM(result_data_map,
> _UTF-16LE'item').value AS EXPR$1])
> +- TableSourceScan(table=[[default_catalog, default_database,
> NestedItemTable, project=[result_data_arr, result_data_map, id]]],
> fields=[result_data_arr, result_data_map, id])
> {code}
> It seems the planner doesn't apply the rule to push projection into scan. The
> reason why we have different results is the optimized plan has more fields
> than before.
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