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https://issues.apache.org/jira/browse/CALCITE-3594?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17015682#comment-17015682
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Rui Wang commented on CALCITE-3594:
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To reduce the complexity of this Jira, we might can ignore the parameter, but
just focus on how to provide a list of values in hint item.
The version should be working now is identifier:string pair, in such case
identifier is used for column names, and string pair for list of value(e.g.
comma separated. in implementation string will be converted to column types
accordingly).
The ideal version can be identifier:list(literal). It should be general
literal as columns types will not limit to string.
> Support hot Groupby keys hint
> -----------------------------
>
> Key: CALCITE-3594
> URL: https://issues.apache.org/jira/browse/CALCITE-3594
> Project: Calcite
> Issue Type: Sub-task
> Reporter: Rui Wang
> Assignee: Rui Wang
> Priority: Major
> Labels: pull-request-available
> Time Spent: 20m
> Remaining Estimate: 0h
>
> It will be useful for Apache Beam if we support the following SqlHint:
> SELECT * FROM t
> GROUP BY t.key_column /* + hot_key(key1=fanout_factor, ...) */)
> The hot key strategy works on aggregation and it provides a list of hot keys
> with fanout factor for a column. The fanout factor says how many partition
> should be created for that specific key, such that we can have a per
> partition aggregate and then have a final aggregate. One example to explain
> it:
> SELECT * FROM t
> GROUP BY t.key_column /* + hot_key("value1"=2) */)
> // for the key_column, there is a "value1" which appear so many times (so
> it's hot), please consider split it into two partition and process separately.
> Such problem is common for big data processing, where hot key creates slowest
> machine which either slow down the whole pipeline or make retries. In such
> case, one common resolution is to split data to multiple partition and
> aggregate per partition, and then have a final combine.
> Usually execution engine won't know what is the hot key(s). SqlHint provides
> a good way to tell the engine which key is useful to deal with it.
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