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https://issues.apache.org/jira/browse/FLINK-5658?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Fabian Hueske updated FLINK-5658:
---------------------------------
Description:
The goal of this issue is to add support for OVER RANGE aggregations on event
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 rowTime() ROWS BETWEEN UNBOUNDED
PRECEDING AND CURRENT ROW) AS sumB,
MIN(b) OVER (PARTITION BY c ORDER BY rowTime() ROWS BETWEEN UNBOUNDED
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 rowTime() as parameter. rowTime() is a
parameterless scalar function that just indicates processing time mode.
- bounded PRECEDING is not supported (see FLINK-5655)
- 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.
An event-time OVER ROWS window will not be able to handle late data, because
this would mean in insert a row into a sorted order shift all other
computations. This would be too expensive to maintain. Therefore, we will throw
an error if a user tries to use an event-time OVER ROWS window with late data
handling.
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 RANGE aggregations on event
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 rowTime() RANGE BETWEEN UNBOUNDED
PRECEDING AND CURRENT ROW) AS sumB,
MIN(b) OVER (PARTITION BY c ORDER BY rowTime() RANGE BETWEEN UNBOUNDED
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 rowTime() as parameter. rowTime() is a
parameterless scalar function that just indicates processing time mode.
- bounded PRECEDING is not supported (see FLINK-5655)
- 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 event time OVER ROWS BETWEEN UNBOUNDED PRECEDING aggregation to SQL
> -----------------------------------------------------------------------
>
> Key: FLINK-5658
> URL: https://issues.apache.org/jira/browse/FLINK-5658
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: Fabian Hueske
> Assignee: hongyuhong
> Fix For: 1.3.0
>
>
> The goal of this issue is to add support for OVER RANGE aggregations on event
> 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 rowTime() ROWS BETWEEN UNBOUNDED
> PRECEDING AND CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY rowTime() ROWS BETWEEN UNBOUNDED
> 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 rowTime() as parameter. rowTime() is a
> parameterless scalar function that just indicates processing time mode.
> - bounded PRECEDING is not supported (see FLINK-5655)
> - 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.
> An event-time OVER ROWS window will not be able to handle late data, because
> this would mean in insert a row into a sorted order shift all other
> computations. This would be too expensive to maintain. Therefore, we will
> throw an error if a user tries to use an event-time OVER ROWS window with
> late data handling.
> 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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