GideonPotok commented on code in PR #45453:
URL: https://github.com/apache/spark/pull/45453#discussion_r1541440974


##########
sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/CollationBenchmark.scala:
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@@ -0,0 +1,165 @@
+/*
+ * 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.execution.benchmark
+
+import scala.concurrent.duration._
+
+import org.apache.spark.benchmark.Benchmark
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.catalyst.util.CollationFactory
+import org.apache.spark.sql.functions._
+import org.apache.spark.unsafe.types.UTF8String
+
+/**
+ * Benchmark to measure performance for comparisons between collated strings. 
To run this benchmark:
+ * {{{
+ *   1. without sbt:
+ *      bin/spark-submit --class <this class>
+ *        --jars <spark core test jar>,<spark catalyst test jar> <spark sql 
test jar>
+ *   2. build/sbt "sql/Test/runMain 
org.apache.spark.sql.execution.benchmark.CollationBenchmark"
+ *   3. generate result:
+ *      SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/Test/runMain <this 
class>"
+ *      Results will be written to "benchmarks/CollationBenchmark-results.txt".
+ * }}}
+ */
+
+object CollationBenchmark extends SqlBasedBenchmark {
+  private val collationTypes = Seq("UTF8_BINARY_LCASE", "UNICODE", 
"UTF8_BINARY", "UNICODE_CI")
+
+  def generateSeqInput(n: Long): Seq[UTF8String] = {
+    val input = Seq("ABC", "ABC", "aBC", "aBC", "abc", "abc", "DEF", "DEF", 
"def", "def",
+      "GHI", "ghi", "JKL", "jkl", "MNO", "mno", "PQR", "pqr", "STU", "stu", 
"VWX", "vwx",
+      "ABC", "ABC", "aBC", "aBC", "abc", "abc", "DEF", "DEF", "def", "def", 
"GHI", "ghi",
+      "JKL", "jkl", "MNO", "mno", "PQR", "pqr", "STU", "stu", "VWX", "vwx", 
"YZ")
+      .map(UTF8String.fromString)
+    val inputLong: Seq[UTF8String] = (0L until n).map(i => input(i.toInt % 
input.size))
+    inputLong
+  }
+
+  private def getDataFrame(strings: Seq[String]): DataFrame = {
+    val asPairs = strings.sliding(2, 1).toSeq.map {
+      case Seq(s1, s2) => (s1, s2)
+    }
+    val d = spark.createDataFrame(asPairs).toDF("s1", "s2")
+    d
+  }
+
+  private def generateDataframeInput(l: Long): DataFrame = {
+    getDataFrame(generateSeqInput(l).map(_.toString))
+  }
+
+  def benchmarkUTFStringEquals(collationTypes: Seq[String], utf8Strings: 
Seq[UTF8String]): Unit = {
+    val sublistStrings = utf8Strings
+
+    val benchmark = new Benchmark(
+      "collation unit benchmarks - equalsFunction",
+      utf8Strings.size * 10,
+      warmupTime = 4.seconds,
+      output = output)
+    collationTypes.foreach(collationType => {
+      val collation = CollationFactory.fetchCollation(collationType)
+      benchmark.addCase(s"$collationType") { _ =>
+        sublistStrings.foreach(s1 =>
+          utf8Strings.foreach(s =>
+            (0 to 10).foreach(_ =>
+              collation.equalsFunction(s, s1).booleanValue())
+          )
+        )
+      }
+    }
+    )
+    benchmark.run()
+  }
+  def benchmarkUTFStringCompare(collationTypes: Seq[String], utf8Strings: 
Seq[UTF8String]): Unit = {
+    val sublistStrings = utf8Strings
+
+    val benchmark = new Benchmark(
+      "collation unit benchmarks - compareFunction",
+      utf8Strings.size * 10,
+      warmupTime = 4.seconds,
+      output = output)
+    collationTypes.foreach(collationType => {
+      val collation = CollationFactory.fetchCollation(collationType)
+      benchmark.addCase(s"$collationType") { _ =>
+        sublistStrings.foreach(s1 =>
+          utf8Strings.foreach(s =>
+            (0 to 10).foreach(_ =>
+              collation.comparator.compare(s, s1)
+            )
+          )
+        )
+      }
+    }
+    )
+    benchmark.run()
+  }
+
+  def benchmarkUTFStringHashFunction(
+      collationTypes: Seq[String],
+      utf8Strings: Seq[UTF8String]): Unit = {
+    val sublistStrings = utf8Strings
+
+    val benchmark = new Benchmark(
+      "collation unit benchmarks - hashFunction",
+      utf8Strings.size * 10,
+      warmupTime = 4.seconds,
+      output = output)
+    collationTypes.foreach(collationType => {
+      val collation = CollationFactory.fetchCollation(collationType)
+      benchmark.addCase(s"$collationType") { _ =>
+        sublistStrings.foreach(_ =>
+          utf8Strings.foreach(s =>
+            (0 to 10).foreach(_ =>
+              collation.hashFunction.applyAsLong(s)
+            )
+          )
+        )
+      }
+    }
+    )
+    benchmark.run()
+  }
+
+  def benchmarkFilterEqual(
+      collationTypes: Seq[String],
+      dfUncollated: DataFrame): Unit = {
+    val benchmark =
+      new Benchmark(
+        "filter df column with collation",
+        dfUncollated.count(),
+        warmupTime = 4.seconds,
+        output = output)
+    collationTypes.foreach(collationType => {
+      val dfCollated = dfUncollated.selectExpr(
+        s"collate(s2, '$collationType') as k2_$collationType",
+        s"collate(s1, '$collationType') as k1_$collationType")
+      benchmark.addCase(s"filter df column with collation - $collationType") { 
_ =>
+        dfCollated.where(col(s"k1_$collationType") === 
col(s"k2_$collationType"))

Review Comment:
   @cloud-fan  Okay. I defer to you and @dbatomic as both of you wanted it 
removed.
   
   so I removed the e2e testing. 



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