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https://issues.apache.org/jira/browse/FLINK-6473?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16411076#comment-16411076
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yinhua.dai edited comment on FLINK-6473 at 3/23/18 9:31 AM:
------------------------------------------------------------
My requirement is to calculate based on an incremental size window for a batch
table.
For example, the first window has 1 row, the second window has 2 rows(including
1 row from the 1st window and a new row), then 3 rows in the 3rd
window(including 2 rows from the 2nd window and a new row), and so on.
For example:
Source table:
||datetime||productId||price||
|3-1|p1|10|
|3-2|p1|20|
|3-3|p1|30|
|3-4|p1|40|
Result table:
||datetime||productId||average||
|3-1|p1|10/1|
|3-2|p1|(10+20)/2|
|3-3|p1|(10+20+30)/3|
|3-4|p1|(10+20+30+40)/4|
I am trying to find a way to implement this requirement with Sql, to me seems
the OVER action can do that but not yet implemented in flink, so I need an
alternative way.
was (Author: yinhua):
My requirement is to calculate based on an incremental size window for a batch
table.
For example, the first window has 1 row, the second window has 2 rows(including
1 row from the 1st window and a new row), then 3 rows(including 2 rows from the
2nd window and a new row), and so on.
Source table:
||datetime||productId||price||
|3-1|p1|10|
|3-2|p1|20|
|3-3|p1|30|
|3-4|p1|40|
Result table:
||datetime||productId||average||
|3-1|p1|10/1|
|3-2|p1|(10+20)/2|
|3-3|p1|(10+20+30)/3|
|3-4|p1|(10+20+30+40)/4|
I am trying to find a way to implement this requirement with Sql, to me seems
the OVER action can do that but not yet implemented in flink, so I need an
alternative way.
> Add OVER window support for batch tables
> ----------------------------------------
>
> Key: FLINK-6473
> URL: https://issues.apache.org/jira/browse/FLINK-6473
> Project: Flink
> Issue Type: New Feature
> Components: Table API & SQL
> Reporter: Fabian Hueske
> Priority: Major
>
> Add support for OVER windows for batch tables.
> Since OVER windows are supported for streaming tables, this issue is not
> about the API (which is available) but about adding the execution strategies
> and translation for OVER windows on batch tables.
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