[
https://issues.apache.org/jira/browse/CALCITE-2979?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16844641#comment-16844641
]
Khawla Mouhoubi commented on CALCITE-2979:
------------------------------------------
After discussing the matter with [~zabetak] and [~rubenql], a good way to start
would be implementing a block based version of the
EnumerableDefaults.correlateJoin or EnumerableDefaults.thetaJoin. There needs
to be a new operator which implementation will be close to EnumerableCorrelate
but with blocks of correlation variables and bloom filters applied to the inner
table. A new rule will do the following:
{code:java}
Join(A.id = B.id)
Scan(A)
Scan(B){code}
Will be turned into:
{code:java}
NestedLoop(blockSize=3)
Scan(A)
Filter(OR(=(cor0[0],B.id), =(cor0[1],B.id), =(cor0[2],B.id))
Scan(B)
{code}
> Add a block-based nested loop join algorithm
> --------------------------------------------
>
> Key: CALCITE-2979
> URL: https://issues.apache.org/jira/browse/CALCITE-2979
> Project: Calcite
> Issue Type: Improvement
> Components: core
> Affects Versions: 1.19.0
> Reporter: Stamatis Zampetakis
> Assignee: Khawla Mouhoubi
> Priority: Major
> Labels: performance
>
> Currently, Calcite provides a tuple-based nested loop join algorithm
> implemented through EnumerableCorrelate and EnumerableDefaults.correlateJoin.
> This means that for each tuple of the outer relation we probe (set variables)
> in the inner relation.
> The goal of this issue is to add new algorithm (or extend the correlateJoin
> method) which first gathers blocks (batches) of tuples from the outer
> relation and then probes the inner relation once per block.
> There are cases (eg., indexes) where the inner relation can be accessed by
> more than one value which can greatly improve the performance in particular
> when the outer relation is big.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
