Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/20265#discussion_r161672316
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/FilterPushdownBenchmark.scala ---
@@ -0,0 +1,195 @@
+/*
+ * 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 java.io.File
+
+import scala.util.{Random, Try}
+
+import org.apache.spark.SparkConf
+import org.apache.spark.sql.functions.monotonically_increasing_id
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.util.{Benchmark, Utils}
+
+
+/**
+ * Benchmark to measure read performance with Filter pushdown.
+ */
+// scalastyle:off line.size.limit
+object FilterPushdownBenchmark {
+ val conf = new SparkConf()
+ conf.set("orc.compression", "snappy")
+ conf.set("spark.sql.parquet.compression.codec", "snappy")
+
+ private val spark = SparkSession.builder()
+ .master("local[1]")
+ .appName("FilterPushdownBenchmark")
+ .config(conf)
+ .getOrCreate()
+
+ // Set default configs. Individual cases will change them if necessary.
+ spark.conf.set(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key, "true")
+ spark.conf.set(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key, "true")
+
+ def withTempPath(f: File => Unit): Unit = {
+ val path = Utils.createTempDir()
+ path.delete()
+ try f(path) finally Utils.deleteRecursively(path)
+ }
+
+ def withTempTable(tableNames: String*)(f: => Unit): Unit = {
+ try f finally tableNames.foreach(spark.catalog.dropTempView)
+ }
+
+ def withSQLConf(pairs: (String, String)*)(f: => Unit): Unit = {
+ val (keys, values) = pairs.unzip
+ val currentValues = keys.map(key => Try(spark.conf.get(key)).toOption)
+ (keys, values).zipped.foreach(spark.conf.set)
+ try f finally {
+ keys.zip(currentValues).foreach {
+ case (key, Some(value)) => spark.conf.set(key, value)
+ case (key, None) => spark.conf.unset(key)
+ }
+ }
+ }
+
+ private def prepareTable(dir: File, df: DataFrame): Unit = {
+ val dirORC = dir.getCanonicalPath + "/orc"
+ val dirParquet = dir.getCanonicalPath + "/parquet"
+
+ df.write.mode("overwrite").orc(dirORC)
+ df.write.mode("overwrite").parquet(dirParquet)
+
+ spark.read.orc(dirORC).createOrReplaceTempView("orcTable")
+ spark.read.parquet(dirParquet).createOrReplaceTempView("parquetTable")
+ }
+
+ def filterPushDownBenchmark(values: Int, width: Int, expr: String): Unit
= {
+ val benchmark = new Benchmark(s"Filter Pushdown ($expr)", values)
+
+ withTempPath { dir =>
+ withTempTable("t1", "orcTable", "patquetTable") {
+ import spark.implicits._
+ val selectExpr = (1 to width).map(i => s"CAST(value AS STRING)
c$i")
+ val df = spark.range(values).map(_ =>
Random.nextLong).selectExpr(selectExpr: _*)
+ .withColumn("id", monotonically_increasing_id())
+
+ df.createOrReplaceTempView("t1")
+ prepareTable(dir, spark.sql("SELECT * FROM t1"))
+
+ Seq(false, true).foreach { value =>
+ benchmark.addCase(s"Parquet Vectorized ${if (value)
s"(Pushdown)" else ""}") { _ =>
+ withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key ->
s"$value") {
+ spark.sql(s"SELECT * FROM parquetTable WHERE
$expr").collect()
+ }
+ }
+ }
+
+ Seq(false, true).foreach { value =>
+ benchmark.addCase(s"Native ORC Vectorized ${if (value)
s"(Pushdown)" else ""}") { _ =>
+ withSQLConf(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key ->
s"$value") {
+ spark.sql(s"SELECT * FROM orcTable WHERE $expr").collect()
+ }
+ }
+ }
+
+ // Positive cases: Select one or no rows
+ /*
+ Java HotSpot(TM) 64-Bit Server VM 1.8.0_152-b16 on Mac OS X 10.13.2
+ Intel(R) Core(TM) i7-4770HQ CPU @ 2.20GHz
+
+ Filter Pushdown (id = 0): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Parquet Vectorized 2267 / 2287
0.5 2162.0 1.0X
+ Parquet Vectorized (Pushdown) 735 / 803
1.4 701.1 3.1X
+ Native ORC Vectorized 1708 / 1718
0.6 1629.1 1.3X
+ Native ORC Vectorized (Pushdown) 83 / 88
12.7 79.0 27.4X
+
+ Filter Pushdown (id == 0): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Parquet Vectorized 2005 / 2123
0.5 1911.7 1.0X
+ Parquet Vectorized (Pushdown) 701 / 773
1.5 668.1 2.9X
+ Native ORC Vectorized 1618 / 1632
0.6 1543.3 1.2X
+ Native ORC Vectorized (Pushdown) 77 / 80
13.6 73.6 26.0X
+
+ Filter Pushdown (id <= 0): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Parquet Vectorized 2085 / 2165
0.5 1988.0 1.0X
+ Parquet Vectorized (Pushdown) 704 / 769
1.5 671.1 3.0X
+ Native ORC Vectorized 1637 / 1638
0.6 1561.1 1.3X
+ Native ORC Vectorized (Pushdown) 76 / 79
13.8 72.4 27.4X
+
+ Filter Pushdown (id < 1): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Parquet Vectorized 2069 / 2133
0.5 1972.7 1.0X
+ Parquet Vectorized (Pushdown) 705 / 764
1.5 672.7 2.9X
+ Native ORC Vectorized 1637 / 1651
0.6 1561.3 1.3X
+ Native ORC Vectorized (Pushdown) 75 / 77
14.0 71.4 27.6X
+
+ Filter Pushdown (id IS NULL): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Parquet Vectorized 2081 / 2123
0.5 1984.4 1.0X
+ Parquet Vectorized (Pushdown) 36 / 37
29.3 34.1 58.1X
+ Native ORC Vectorized 1616 / 1645
0.6 1540.7 1.3X
+ Native ORC Vectorized (Pushdown) 41 / 43
25.7 39.0 50.9X
+ */
+
+ // Negative cases: Select all rows which means the predicate is
always true.
+ /*
+ Java HotSpot(TM) 64-Bit Server VM 1.8.0_152-b16 on Mac OS X 10.13.2
+ Intel(R) Core(TM) i7-4770HQ CPU @ 2.20GHz
+
+ Filter Pushdown (id > -1): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Parquet Vectorized 8346 / 8516
0.1 7959.8 1.0X
+ Parquet Vectorized (Pushdown) 8611 / 8630
0.1 8212.4 1.0X
+ Native ORC Vectorized 7700 / 7940
0.1 7343.2 1.1X
+ Native ORC Vectorized (Pushdown) 7572 / 7635
0.1 7221.5 1.1X
+
+ Filter Pushdown (id != -1): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Parquet Vectorized 8088 / 8297
0.1 7713.2 1.0X
+ Parquet Vectorized (Pushdown) 7110 / 8674
0.1 6780.8 1.1X
--- End diff --
I'll increase from 2 to 5.
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