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https://issues.apache.org/jira/browse/DRILL-5879?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16210358#comment-16210358
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ASF GitHub Bot commented on DRILL-5879:
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Github user sachouche commented on the issue:
https://github.com/apache/drill/pull/1001
- It was 50% for 1) and 50% for 2)
- Notice this breakdown depends on
o The number of Contains pattern for the same value (impacts 1))
o The pattern length (impacts both 1) and 2))
> Optimize "Like" operator
> ------------------------
>
> Key: DRILL-5879
> URL: https://issues.apache.org/jira/browse/DRILL-5879
> Project: Apache Drill
> Issue Type: Improvement
> Components: Execution - Relational Operators
> Environment: *
> Reporter: salim achouche
> Assignee: salim achouche
> Priority: Minor
> Fix For: 1.12.0
>
>
> Query: select <column-list> from <table> where colA like '%a%' or colA like
> '%xyz%';
> Improvement Opportunities
> # Avoid isAscii computation (full access of the input string) since we're
> dealing with the same column twice
> # Optimize the "contains" for-loop
> Implementation Details
> 1)
> * Added a new integer variable "asciiMode" to the VarCharHolder class
> * The default value is -1 which indicates this info is not known
> * Otherwise this value will be set to either 1 or 0 based on the string being
> in ASCII mode or Unicode
> * The execution plan already shares the same VarCharHolder instance for all
> evaluations of the same column value
> * The asciiMode will be correctly set during the first LIKE evaluation and
> will be reused across other LIKE evaluations
> 2)
> * The "Contains" LIKE operation is quite expensive as the code needs to
> access the input string to perform character based comparisons
> * Created 4 versions of the same for-loop to a) make the loop simpler to
> optimize (Vectorization) and b) minimize comparisons
> Benchmarks
> * Lineitem table 100GB
> * Query: select l_returnflag, count(*) from dfs.`<source>` where l_comment
> not like '%a%' or l_comment like '%the%' group by l_returnflag
> * Before changes: 33sec
> * After changes : 27sec
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