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https://issues.apache.org/jira/browse/SPARK-26203?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16717879#comment-16717879
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ASF GitHub Bot commented on SPARK-26203:
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dongjoon-hyun commented on a change in pull request #23291: [SPARK-26203][SQL]
Benchmark performance of In and InSet expressions
URL: https://github.com/apache/spark/pull/23291#discussion_r240766592
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/InSetBenchmark.scala
##########
@@ -0,0 +1,213 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import org.apache.spark.benchmark.Benchmark
+import org.apache.spark.sql.catalyst.expressions.In
+import org.apache.spark.sql.catalyst.expressions.InSet
+import org.apache.spark.sql.execution.benchmark.SqlBasedBenchmark
+import org.apache.spark.sql.functions.{array, struct}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types._
+
+/**
+ * A benchmark that compares the performance of [[In]] and [[InSet]]
expressions.
+ *
+ * To run this benchmark:
+ * {{{
+ * 1. without sbt: bin/spark-submit --class <this class> <spark sql test jar>
+ * 2. build/sbt "sql/test:runMain <this class>"
+ * 3. generate result: SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt
"sql/test:runMain <this class>"
+ * Results will be written to "benchmarks/InSetBenchmark-results.txt".
+ * }}}
+ */
+object InSetBenchmark extends SqlBasedBenchmark {
+
+ import spark.implicits._
+
+ def byteBenchmark(numItems: Int, numRows: Long, minNumIters: Int): Benchmark
= {
Review comment:
`def` -> `private def`
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> Benchmark performance of In and InSet expressions
> -------------------------------------------------
>
> Key: SPARK-26203
> URL: https://issues.apache.org/jira/browse/SPARK-26203
> Project: Spark
> Issue Type: Test
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Anton Okolnychyi
> Priority: Major
>
> {{OptimizeIn}} rule replaces {{In}} with {{InSet}} if the number of possible
> values exceeds "spark.sql.optimizer.inSetConversionThreshold" and all values
> are literals. This was done for performance reasons to avoid O\(n\) time
> complexity for {{In}}.
> The original optimization was done in SPARK-3711. A lot has changed after
> that (e.g., generation of Java code to evaluate expressions), so it is worth
> to measure the performance of this optimization again.
> According to my local benchmarks, {{InSet}} can be up to 10x time slower than
> {{In}} due to autoboxing and other issues.
> The scope of this JIRA is to benchmark every supported data type inside
> {{In}} and {{InSet}} and outline existing bottlenecks. Once we have this
> information, we can come up with solutions.
> Based on my preliminary investigation, we can do quite some optimizations,
> which quite frequently depend on a specific data type.
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