Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/19943#discussion_r160317124
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcReadBenchmark.scala ---
@@ -0,0 +1,435 @@
+/*
+ * 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.hive.orc
+
+import java.io.File
+
+import scala.util.{Random, Try}
+
+import org.apache.spark.SparkConf
+import org.apache.spark.sql.{DataFrame, SparkSession}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types._
+import org.apache.spark.util.{Benchmark, Utils}
+
+
+/**
+ * Benchmark to measure ORC read performance.
+ *
+ * This is in `sql/hive` module in order to compare `sql/core` and
`sql/hive` ORC data sources.
+ */
+// scalastyle:off line.size.limit
+object OrcReadBenchmark {
+ val conf = new SparkConf()
+ conf.set("orc.compression", "snappy")
+
+ private val spark = SparkSession.builder()
+ .master("local[1]")
+ .appName("OrcReadBenchmark")
+ .config(conf)
+ .getOrCreate()
+
+ // Set default configs. Individual cases will change them if necessary.
+ spark.conf.set(SQLConf.ORC_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 val NATIVE_ORC_FORMAT =
classOf[org.apache.spark.sql.execution.datasources.orc.OrcFileFormat].getCanonicalName
+ private val HIVE_ORC_FORMAT =
classOf[org.apache.spark.sql.hive.orc.OrcFileFormat].getCanonicalName
+
+ private def prepareTable(dir: File, df: DataFrame, partition:
Option[String] = None): Unit = {
+ val dirORC = dir.getCanonicalPath
+
+ if (partition.isDefined) {
+ df.write.partitionBy(partition.get).orc(dirORC)
+ } else {
+ df.write.orc(dirORC)
+ }
+
+
spark.read.format(NATIVE_ORC_FORMAT).load(dirORC).createOrReplaceTempView("nativeOrcTable")
+
spark.read.format(HIVE_ORC_FORMAT).load(dirORC).createOrReplaceTempView("hiveOrcTable")
+ }
+
+ def numericScanBenchmark(values: Int, dataType: DataType): Unit = {
+ val sqlBenchmark = new Benchmark(s"SQL Single ${dataType.sql} Column
Scan", values)
+
+ withTempPath { dir =>
+ withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
+ import spark.implicits._
+ spark.range(values).map(_ =>
Random.nextLong).createOrReplaceTempView("t1")
+
+ prepareTable(dir, spark.sql(s"SELECT CAST(value as
${dataType.sql}) id FROM t1"))
+
+ sqlBenchmark.addCase("Native ORC MR") { _ =>
+ withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key ->
"false") {
+ spark.sql("SELECT sum(id) FROM nativeOrcTable").collect()
+ }
+ }
+
+ sqlBenchmark.addCase("Native ORC Vectorized") { _ =>
+ spark.sql("SELECT sum(id) FROM nativeOrcTable").collect()
+ }
+
+ sqlBenchmark.addCase("Hive built-in ORC") { _ =>
+ spark.sql("SELECT sum(id) FROM hiveOrcTable").collect()
+ }
+
+ /*
+ 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
+
+ SQL Single TINYINT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1202 / 1265
13.1 76.4 1.0X
+ Native ORC Vectorized 162 / 172
97.1 10.3 7.4X
+ Hive built-in ORC 1410 / 1428
11.2 89.6 0.9X
+
+ SQL Single SMALLINT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1266 / 1286
12.4 80.5 1.0X
+ Native ORC Vectorized 165 / 174
95.2 10.5 7.7X
+ Hive built-in ORC 1701 / 1704
9.2 108.2 0.7X
+
+ SQL Single INT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1307 / 1307
12.0 83.1 1.0X
+ Native ORC Vectorized 232 / 248
67.9 14.7 5.6X
+ Hive built-in ORC 1793 / 1793
8.8 114.0 0.7X
+
+ SQL Single BIGINT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1360 / 1372
11.6 86.5 1.0X
+ Native ORC Vectorized 293 / 303
53.8 18.6 4.7X
+ Hive built-in ORC 1913 / 1933
8.2 121.6 0.7X
+
+ SQL Single FLOAT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1389 / 1488
11.3 88.3 1.0X
+ Native ORC Vectorized 340 / 346
46.2 21.6 4.1X
+ Hive built-in ORC 1976 / 1997
8.0 125.6 0.7X
+
+ SQL Single DOUBLE Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1461 / 1465
10.8 92.9 1.0X
+ Native ORC Vectorized 395 / 406
39.8 25.1 3.7X
+ Hive built-in ORC 2127 / 2146
7.4 135.2 0.7X
+ */
+ sqlBenchmark.run()
+ }
+ }
+ }
+
+ def intStringScanBenchmark(values: Int): Unit = {
+ val benchmark = new Benchmark("Int and String Scan", values)
+
+ withTempPath { dir =>
+ withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
+ import spark.implicits._
+ spark.range(values).map(_ =>
Random.nextLong).createOrReplaceTempView("t1")
+
+ prepareTable(
+ dir,
+ spark.sql("SELECT CAST(value AS INT) AS c1, CAST(value as
STRING) AS c2 FROM t1"))
+
+ benchmark.addCase("Native ORC MR") { _ =>
+ withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key ->
"false") {
+ spark.sql("SELECT sum(c1), sum(length(c2)) FROM
nativeOrcTable").collect()
+ }
+ }
+
+ benchmark.addCase("Native ORC Vectorized") { _ =>
+ spark.sql("SELECT sum(c1), sum(length(c2)) FROM
nativeOrcTable").collect()
+ }
+
+ benchmark.addCase("Hive built-in ORC") { _ =>
+ spark.sql("SELECT sum(c1), sum(length(c2)) FROM
hiveOrcTable").collect()
+ }
+
+ /*
+ 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
+
+ Int and String Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 2843 / 2935
3.7 271.1 1.0X
+ Native ORC Vectorized 1349 / 1359
7.8 128.6 2.1X
+ Hive built-in ORC 3862 / 3881
2.7 368.3 0.7X
+ */
+ benchmark.run()
+ }
+ }
+ }
+
+ def partitionTableScanBenchmark(values: Int): Unit = {
+ val benchmark = new Benchmark("Partitioned Table", values)
+
+ withTempPath { dir =>
+ withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
+ import spark.implicits._
+ spark.range(values).map(_ =>
Random.nextLong).createOrReplaceTempView("t1")
+
+ prepareTable(dir, spark.sql("SELECT value % 2 AS p, value AS id
FROM t1"), Some("p"))
+
+ benchmark.addCase("Read data column - Native ORC MR") { _ =>
+ withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key ->
"false") {
+ spark.sql("SELECT sum(id) FROM nativeOrcTable").collect()
+ }
+ }
+
+ benchmark.addCase("Read data column - Native ORC Vectorized") { _
=>
+ spark.sql("SELECT sum(id) FROM nativeOrcTable").collect()
+ }
+
+ benchmark.addCase("Read data column - Hive built-in ORC") { _ =>
+ spark.sql("SELECT sum(id) FROM hiveOrcTable").collect()
+ }
+
+ benchmark.addCase("Read partition column - Native ORC MR") { _ =>
+ withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key ->
"false") {
+ spark.sql("SELECT sum(p) FROM nativeOrcTable").collect()
+ }
+ }
+
+ benchmark.addCase("Read partition column - Native ORC Vectorized")
{ _ =>
+ spark.sql("SELECT sum(p) FROM nativeOrcTable").collect()
+ }
+
+ benchmark.addCase("Read partition column - Hive built-in ORC") { _
=>
+ spark.sql("SELECT sum(p) FROM hiveOrcTable").collect()
+ }
+
+ benchmark.addCase("Read both columns - Native ORC MR") { _ =>
+ withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key ->
"false") {
+ spark.sql("SELECT sum(p), sum(id) FROM
nativeOrcTable").collect()
+ }
+ }
+
+ benchmark.addCase("Read both columns - Native ORC Vectorized") { _
=>
+ spark.sql("SELECT sum(p), sum(id) FROM nativeOrcTable").collect()
+ }
+
+ benchmark.addCase("Read both columns - Hive built-in ORC") { _ =>
+ spark.sql("SELECT sum(p), sum(id) FROM hiveOrcTable").collect()
+ }
+
+ /*
+ 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
+
+ Partitioned Table: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Read data column - Native ORC MR 1545 / 1568
10.2 98.2 1.0X
+ Read data column - Native ORC Vectorized 300 / 304
52.4 19.1 5.1X
+ Read data column - Hive built-in ORC 2097 / 2117
7.5 133.3 0.7X
+ Read partition column - Native ORC MR 1023 / 1026
15.4 65.1 1.5X
+ Read partition column - Native ORC Vectorized 54 / 56
292.3 3.4 28.7X
+ Read partition column - Hive built-in ORC 1285 / 1289
12.2 81.7 1.2X
+ Read both columns - Native ORC MR 1564 / 1565
10.1 99.4 1.0X
+ Read both columns - Native ORC Vectorized 336 / 340
46.8 21.4 4.6X
+ Read both columns - Hive built-in ORC 2100 / 2123
7.5 133.5 0.7X
+ */
+ benchmark.run()
+ }
+ }
+ }
+
+ def repeatedStringScanBenchmark(values: Int): Unit = {
+ val benchmark = new Benchmark("Repeated String", values)
+
+ withTempPath { dir =>
+ withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
+ spark.range(values).createOrReplaceTempView("t1")
+
+ prepareTable(dir, spark.sql("SELECT CAST((id % 200) + 10000 as
STRING) AS c1 FROM t1"))
+
+ benchmark.addCase("Native ORC MR") { _ =>
+ withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key ->
"false") {
+ spark.sql("SELECT sum(length(c1)) FROM
nativeOrcTable").collect()
+ }
+ }
+
+ benchmark.addCase("Native ORC Vectorized") { _ =>
+ spark.sql("SELECT sum(length(c1)) FROM nativeOrcTable").collect()
+ }
+
+ benchmark.addCase("Hive built-in ORC") { _ =>
+ spark.sql("SELECT sum(length(c1)) FROM hiveOrcTable").collect()
+ }
+
+ /*
+ 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
+
+ Repeated String: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1338 / 1340
7.8 127.6 1.0X
+ Native ORC Vectorized 342 / 350
30.6 32.6 3.9X
+ Hive built-in ORC 2036 / 2117
5.2 194.2 0.7X
+ */
+ benchmark.run()
+ }
+ }
+ }
+
+ def stringWithNullsScanBenchmark(values: Int, fractionOfNulls: Double):
Unit = {
+ withTempPath { dir =>
+ withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
+ spark.range(values).createOrReplaceTempView("t1")
+
+ prepareTable(
+ dir,
+ spark.sql(
+ s"SELECT IF(RAND(1) < $fractionOfNulls, NULL, CAST(id as
STRING)) AS c1, " +
+ s"IF(RAND(2) < $fractionOfNulls, NULL, CAST(id as STRING)) AS
c2 FROM t1"))
+
+ val benchmark = new Benchmark(s"String with Nulls Scan
($fractionOfNulls%)", values)
+
+ benchmark.addCase("Native ORC MR") { _ =>
+ withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key ->
"false") {
+ spark.sql("SELECT SUM(LENGTH(c2)) FROM nativeOrcTable " +
+ "WHERE c1 IS NOT NULL AND c2 IS NOT NULL").collect()
+ }
+ }
+
+ benchmark.addCase("Native ORC Vectorized") { _ =>
+ spark.sql("SELECT SUM(LENGTH(c2)) FROM nativeOrcTable " +
+ "WHERE c1 IS NOT NULL AND c2 IS NOT NULL").collect()
+ }
+
+ benchmark.addCase("Hive built-in ORC") { _ =>
+ spark.sql("SELECT SUM(LENGTH(c2)) FROM hiveOrcTable " +
+ "WHERE c1 IS NOT NULL AND c2 IS NOT NULL").collect()
+ }
+
+ /*
+ 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
+
+ String with Nulls Scan (0.0%): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 2510 / 2527
4.2 239.3 1.0X
+ Native ORC Vectorized 1012 / 1012
10.4 96.5 2.5X
+ Hive built-in ORC 3967 / 3984
2.6 378.3 0.6X
+
+ String with Nulls Scan (0.5%): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 2374 / 2388
4.4 226.4 1.0X
+ Native ORC Vectorized 1269 / 1275
8.3 121.0 1.9X
+ Hive built-in ORC 2994 / 2998
3.5 285.5 0.8X
+
+ String with Nulls Scan (0.95%): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1285 / 1312
8.2 122.6 1.0X
+ Native ORC Vectorized 500 / 508
21.0 47.7 2.6X
+ Hive built-in ORC 1630 / 1638
6.4 155.5 0.8X
+ */
+ benchmark.run()
+ }
+ }
+ }
+
+ def columnsBenchmark(values: Int, width: Int): Unit = {
+ val sqlBenchmark = new Benchmark(s"SQL Single Column Scan from $width
columns", values)
+
+ withTempPath { dir =>
+ withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
+ import spark.implicits._
+ val middle = width / 2
+ val selectExpr = (1 to width).map(i => s"value as c$i")
+ spark.range(values).map(_ => Random.nextLong).toDF()
+ .selectExpr(selectExpr: _*).createOrReplaceTempView("t1")
+
+ prepareTable(dir, spark.sql("SELECT * FROM t1"))
+
+ sqlBenchmark.addCase("Native ORC MR") { _ =>
+ withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key ->
"false") {
+ spark.sql(s"SELECT sum(c$middle) FROM
nativeOrcTable").collect()
+ }
+ }
+
+ sqlBenchmark.addCase("Native ORC Vectorized") { _ =>
+ spark.sql(s"SELECT sum(c$middle) FROM nativeOrcTable").collect()
+ }
+
+ sqlBenchmark.addCase("Hive built-in ORC") { _ =>
+ spark.sql(s"SELECT sum(c$middle) FROM hiveOrcTable").collect()
+ }
+
+ /*
+ 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
+
+ SQL Single Column Scan from 100 columns: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1107 / 1111
0.9 1055.4 1.0X
+ Native ORC Vectorized 93 / 102
11.3 88.8 11.9X
+ Hive built-in ORC 377 / 389
2.8 359.6 2.9X
+
+ SQL Single Column Scan from 200 columns: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 2258 / 2270
0.5 2153.8 1.0X
+ Native ORC Vectorized 160 / 168
6.6 152.6 14.1X
+ Hive built-in ORC 591 / 597
1.8 563.7 3.8X
+
+ SQL Single Column Scan from 300 columns: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 3364 / 3391
0.3 3208.3 1.0X
+ Native ORC Vectorized 273 / 284
3.8 260.1 12.3X
+ Hive built-in ORC 831 / 842
1.3 792.8 4.0X
--- End diff --
don't forget this question :)
https://github.com/apache/spark/pull/19943#discussion_r160169481
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