{"action":"closed","number":14847,"pull_request":{"url":"https://api.github.com/repos/apache/spark/pulls/14847","id":82979241,"html_url":"https://github.com/apache/spark/pull/14847","diff_url":"https://github.com/apache/spark/pull/14847.diff","patch_url":"https://github.com/apache/spark/pull/14847.patch","issue_url":"https://api.github.com/repos/apache/spark/issues/14847","number":14847,"state":"closed","locked":false,"title":"[SPARK-17254][SQL] Filter can stop when the condition is false if the child output is sorted","user":{"login":"viirya","id":68855,"avatar_url":"https://avatars.githubusercontent.com/u/68855?v=3","gravatar_id":"","url":"https://api.github.com/users/viirya","html_url":"https://github.com/viirya","followers_url":"https://api.github.com/users/viirya/followers","following_url":"https://api.github.com/users/viirya/following{/other_user}","gists_url":"https://api.github.com/users/viirya/gists{/gist_id}","starred_url":"https://api.github.com/users/viirya/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/viirya/subscriptions","organizations_url":"https://api.github.com/users/viirya/orgs","repos_url":"https://api.github.com/users/viirya/repos","events_url":"https://api.github.com/users/viirya/events{/privacy}","received_events_url":"https://api.github.com/users/viirya/received_events","type":"User","site_admin":false},"body":"## What changes were proposed in this pull request?\r\n\r\nFrom https://issues.apache.org/jira/secure/attachment/12778890/BucketedTables.pdf:\r\n\r\nFilter on sorted data\r\n\r\nIf the data is sorted by a key, filters on the key could stop as soon as the data is out of range. For example, WHERE ticker_id < “F” should stop as soon as the first row starting with “F” is seen. This can be done adding a Filter operator that has “stop if false” semantics. This is generally useful.\r\n\r\n### Benchmark\r\n\r\n    val N = 500L << 18\r\n    val df = sparkSession.range(N).sort(\"id\").persist()\r\n    runBenchmark(\"range/sort/filter/sum\", N) {\r\n      df.filter(\"id < 10\").groupBy().sum().collect()\r\n    }\r\n\r\nBefore this patch:\r\n\r\n    Java HotSpot(TM) 64-Bit Server VM 1.8.0_71-b15 on Linux 3.19.0-64-generic\r\n    Intel(R) Core(TM) i7-5557U CPU @ 3.10GHz\r\n    range/sort/filter/sum:                   Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative\r\n    ------------------------------------------------------------------------------------------------\r\n    range/sort/filter/sum wholestage off           573 /  665        228.6           4.4       1.0X\r\n    range/sort/filter/sum wholestage on            273 /  363        479.6           2.1       2.1X\r\n\r\nAfter this patch:\r\n\r\n    Java HotSpot(TM) 64-Bit Server VM 1.8.0_71-b15 on Linux 3.19.0-64-generic\r\n    Intel(R) Core(TM) i7-5557U CPU @ 3.10GHz\r\n    range/sort/filter/sum:                   Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative\r\n    ------------------------------------------------------------------------------------------------\r\n    range/sort/filter/sum wholestage off           325 /  424        403.7           2.5       1.0X\r\n    range/sort/filter/sum wholestage on            254 /  289        516.2           1.9       1.3X\r\n\r\nThis patch can improve the wholestage off case significantly. For the wholestage on case, looks like no significant difference. It might due to that in wholestage on case we use `continue` to skip the filtering, but it still needs to iterate all the rows.\r\n\r\n## How was this patch tested?\r\n\r\nJenkins tests. Manually 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