Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/19943#discussion_r160306085
--- 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 10.13.1
+ 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 1180 / 1230
13.3 75.0 1.0X
+ Native ORC Vectorized 159 / 169
98.8 10.1 7.4X
+ Hive built-in ORC 1395 / 1396
11.3 88.7 0.8X
+
+ SQL Single SMALLINT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1216 / 1267
12.9 77.3 1.0X
+ Native ORC Vectorized 163 / 172
96.4 10.4 7.5X
+ Hive built-in ORC 1649 / 1672
9.5 104.8 0.7X
+
+ SQL Single INT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1331 / 1332
11.8 84.6 1.0X
+ Native ORC Vectorized 233 / 245
67.6 14.8 5.7X
+ Hive built-in ORC 1832 / 1839
8.6 116.5 0.7X
+
+ SQL Single BIGINT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1382 / 1389
11.4 87.8 1.0X
+ Native ORC Vectorized 291 / 299
54.1 18.5 4.8X
+ Hive built-in ORC 1926 / 1936
8.2 122.5 0.7X
+
+ SQL Single FLOAT Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1399 / 1478
11.2 88.9 1.0X
+ Native ORC Vectorized 324 / 329
48.6 20.6 4.3X
+ Hive built-in ORC 1938 / 1945
8.1 123.2 0.7X
+
+ SQL Single DOUBLE Column Scan: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1441 / 1470
10.9 91.6 1.0X
+ Native ORC Vectorized 406 / 408
38.8 25.8 3.6X
+ Hive built-in ORC 2031 / 2039
7.7 129.1 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 10.13.1
+ 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 2716 / 2738
3.9 259.0 1.0X
+ Native ORC Vectorized 1325 / 1325
7.9 126.4 2.0X
+ Hive built-in ORC 3607 / 3645
2.9 344.0 0.8X
+ */
+ 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 10.13.1
+ 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 1544 / 1547
10.2 98.1 1.0X
+ Read data column - Native ORC Vectorized 298 / 306
52.7 19.0 5.2X
+ Read data column - Hive built-in ORC 2089 / 2097
7.5 132.8 0.7X
+ Read partition column - Native ORC MR 1050 / 1051
15.0 66.8 1.5X
+ Read partition column - Native ORC Vectorized 54 / 57
290.0 3.4 28.5X
+ Read partition column - Hive built-in ORC 1271 / 1280
12.4 80.8 1.2X
+ Read both columns - Native ORC MR 1572 / 1605
10.0 100.0 1.0X
+ Read both columns - Native ORC Vectorized 332 / 338
47.4 21.1 4.6X
+ Read both columns - Hive built-in ORC 2108 / 2123
7.5 134.0 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 10.13.1
+ 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 1297 / 1327
8.1 123.7 1.0X
+ Native ORC Vectorized 317 / 327
33.1 30.2 4.1X
+ Hive built-in ORC 1970 / 1973
5.3 187.9 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 10.13.1
+ 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 2531 / 2542
4.1 241.4 1.0X
+ Native ORC Vectorized 947 / 952
11.1 90.3 2.7X
+ Hive built-in ORC 4012 / 4034
2.6 382.6 0.6X
+
+ String with Nulls Scan (0.5%): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 2388 / 2407
4.4 227.8 1.0X
+ Native ORC Vectorized 1235 / 1236
8.5 117.8 1.9X
+ Hive built-in ORC 2951 / 2958
3.6 281.4 0.8X
+
+ String with Nulls Scan (0.95%): Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 1325 / 1346
7.9 126.4 1.0X
+ Native ORC Vectorized 460 / 468
22.8 43.9 2.9X
+ Hive built-in ORC 1600 / 1607
6.6 152.6 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 10.13.1
+ 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 / 1118
0.9 1056.1 1.0X
+ Native ORC Vectorized 94 / 100
11.1 89.8 11.8X
+ Hive built-in ORC 382 / 390
2.7 364.0 2.9X
+
+ SQL Single Column Scan from 200 columns: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 2278 / 2287
0.5 2172.0 1.0X
+ Native ORC Vectorized 158 / 165
6.6 150.6 14.4X
+ Hive built-in ORC 585 / 590
1.8 557.7 3.9X
+
+ SQL Single Column Scan from 300 columns: Best/Avg Time(ms)
Rate(M/s) Per Row(ns) Relative
+
------------------------------------------------------------------------------------------------
+ Native ORC MR 3386 / 3394
0.3 3229.1 1.0X
+ Native ORC Vectorized 271 / 281
3.9 258.2 12.5X
+ Hive built-in ORC 843 / 852
1.2 803.6 4.0X
--- End diff --
don't forget this question :)
https://github.com/apache/spark/pull/19943#discussion_r160169481
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