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Posted to issues@flink.apache.org by "Fabian Hueske (JIRA)" <ji...@apache.org> on 2017/01/26 13:45:24 UTC
[jira] [Updated] (FLINK-5653) Add processing time OVER ROWS BETWEEN
x PRECEDING aggregation to SQL
[ https://issues.apache.org/jira/browse/FLINK-5653?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Fabian Hueske updated FLINK-5653:
---------------------------------
Description:
The goal of this issue is to add support for OVER ROW aggregations on processing time streams to the SQL interface.
Queries similar to the following should be supported:
{code}
SELECT
a,
SUM(b) OVER (PARTITION BY c ORDER BY procTime() ROW BETWEEN 2 PRECEDING AND CURRENT ROW) AS sumB,
MIN(b) OVER (PARTITION BY c ORDER BY procTime() ROW BETWEEN 2 PRECEDING AND CURRENT ROW) AS minB
FROM myStream
{code}
The following restrictions should initially apply:
- All OVER clauses in the same SELECT clause must be exactly the same.
- The PARTITION BY clause is optional (no partitioning results in single threaded execution).
- The ORDER BY clause may only have procTime() as parameter. procTime() is a parameterless scalar function that just indicates processing time mode.
- UNBOUNDED PRECEDING is not supported
- FOLLOWING is not supported.
The restrictions will be resolved in follow up issues. If we find that some of the restrictions are trivial to address, we can add the functionality in this issue as well.
This issue includes:
- Design of the DataStream operator to compute OVER ROW aggregates
- Translation from Calcite's RelNode representation (LogicalProject with RexOver expression).
was:
The goal of this issue is to add support for OVER ROW aggregations on processing time streams to the SQL interface.
Queries similar to the following should be supported:
{code}
SELECT
a,
SUM(b) OVER (PARTITION BY c ROW BETWEEN 2 PRECEDING AND CURRENT ROW) AS sumB,
MIN(b) OVER (PARTITION BY c ROW BETWEEN 2 PRECEDING AND CURRENT ROW) AS minB
FROM myStream
{code}
The following restrictions should initially apply:
- All OVER clauses in the same SELECT clause must be exactly the same.
- The PARTITION BY clause is optional (no partitioning results in single threaded execution).
- The ORDER BY clause may not be used (this distinguishes processing time from event time which requires an ORDER BY clause on a special field).
- UNBOUNDED PRECEDING is not supported
- FOLLOWING is not supported.
The restrictions will be resolved in follow up issues. If we find that some of the restrictions are trivial to address, we can add the functionality in this issue as well.
This issue includes:
- Design of the DataStream operator to compute OVER ROW aggregates
- Translation from Calcite's RelNode representation (LogicalProject with RexOver expression).
> Add processing time OVER ROWS BETWEEN x PRECEDING aggregation to SQL
> --------------------------------------------------------------------
>
> Key: FLINK-5653
> URL: https://issues.apache.org/jira/browse/FLINK-5653
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: Fabian Hueske
>
> The goal of this issue is to add support for OVER ROW aggregations on processing time streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT
> a,
> SUM(b) OVER (PARTITION BY c ORDER BY procTime() ROW BETWEEN 2 PRECEDING AND CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY procTime() ROW BETWEEN 2 PRECEDING AND CURRENT ROW) AS minB
> FROM myStream
> {code}
> The following restrictions should initially apply:
> - All OVER clauses in the same SELECT clause must be exactly the same.
> - The PARTITION BY clause is optional (no partitioning results in single threaded execution).
> - The ORDER BY clause may only have procTime() as parameter. procTime() is a parameterless scalar function that just indicates processing time mode.
> - UNBOUNDED PRECEDING is not supported
> - FOLLOWING is not supported.
> The restrictions will be resolved in follow up issues. If we find that some of the restrictions are trivial to address, we can add the functionality in this issue as well.
> This issue includes:
> - Design of the DataStream operator to compute OVER ROW aggregates
> - Translation from Calcite's RelNode representation (LogicalProject with RexOver expression).
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