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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-6968) Store streaming, updating tables with unique key in queryable state
Date Wed, 23 May 2018 09:18:00 GMT

    [ https://issues.apache.org/jira/browse/FLINK-6968?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16486957#comment-16486957

ASF GitHub Bot commented on FLINK-6968:

Github user fhueske commented on a diff in the pull request:

    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/aggregate/KeyedProcessFunctionWithCleanupState.scala
    @@ -44,8 +45,20 @@ abstract class KeyedProcessFunctionWithCleanupState[K, I, O](queryConfig:
       protected def registerProcessingCleanupTimer(
         ctx: KeyedProcessFunction[K, I, O]#Context,
         currentTime: Long): Unit = {
    -    if (stateCleaningEnabled) {
    +    registerCleanupTimer(ctx, currentTime, TimeDomain.PROCESSING_TIME)
    +  }
    +  protected def registerEventCleanupTimer(
    --- End diff --
    We implemented state cleanup as processing time because it is easier to reason about for
users and doesn't interfere that much with event-time processing (it is not possible to distinguish
timers yet). However, it also has a few short comings such as cleared state when recovering
a query from a savepoint (which we don't really encourage at the moment). 
    Anyway, introducing event-time state cleanup should definitely go into a separate issue
and PR.

> Store streaming, updating tables with unique key in queryable state
> -------------------------------------------------------------------
>                 Key: FLINK-6968
>                 URL: https://issues.apache.org/jira/browse/FLINK-6968
>             Project: Flink
>          Issue Type: New Feature
>          Components: Table API &amp; SQL
>            Reporter: Fabian Hueske
>            Assignee: Renjie Liu
>            Priority: Major
> Streaming tables with unique key are continuously updated. For example queries with a
non-windowed aggregation generate such tables. Commonly, such updating tables are emitted
via an upsert table sink to an external datastore (k-v store, database) to make it accessible
to applications.
> This issue is about adding a feature to store and maintain such a table as queryable
state in Flink. By storing the table in Flnk's queryable state, we do not need an external
data store to access the results of the query but can query the results directly from Flink.

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