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From "Maxim Muzafarov (Jira)" <j...@apache.org>
Subject [jira] [Updated] (IGNITE-11498) SQL: Rework DML data distribution logic
Date Tue, 08 Oct 2019 11:38:00 GMT

     [ https://issues.apache.org/jira/browse/IGNITE-11498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Maxim Muzafarov updated IGNITE-11498:
    Fix Version/s:     (was: 2.8)

> SQL: Rework DML data distribution logic
> ---------------------------------------
>                 Key: IGNITE-11498
>                 URL: https://issues.apache.org/jira/browse/IGNITE-11498
>             Project: Ignite
>          Issue Type: Task
>          Components: sql
>            Reporter: Vladimir Ozerov
>            Priority: Major
>             Fix For: 2.9
> Current DML implementation has a number of problems:
> 1) We fetch the whole data set to originator's node. There is "skipDmlOnReducer" flag
to avoid this in some cases, but it is still in experimental state, and is not enabled by
> 2) Updates are deadlock-prone: we update entries in batches equal to {{SqlFieldsQuery.pageSize}}.
So we can deadlock easily with concurrent cache operations
> 3) We have very strange re-try logic. It is not clear why it is needed in the first place
provided that DML is not transactional and no guarantees are needed.
> Proposal:
> # Implement proper routing logic: if a request could be executed on data nodes bypassing
skipping reducer, do this. Otherwise fetch all data to reducer. This decision should be made
in absolutely the same way as for MVCC (see {{GridNearTxQueryEnlistFuture}} as a starting
> # Distribute updates to primary data node in batches, but apply them one by one, similar
to data streamer with {{allowOverwrite=false}}. Do not do any partition state or {{AffinityTopologyVersion}}
checks, since DML is not transactional. Return and aggregate update counts back.
> # Remove or at least rethink retry logic. Why do we need it in the first place?

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