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Posted to commits@spark.apache.org by do...@apache.org on 2018/10/12 23:08:27 UTC
spark git commit: [SPARK-25664][SQL][TEST] Refactor JoinBenchmark to
use main method
Repository: spark
Updated Branches:
refs/heads/master 4e141a416 -> e965fb55a
[SPARK-25664][SQL][TEST] Refactor JoinBenchmark to use main method
## What changes were proposed in this pull request?
Refactor `JoinBenchmark` to use main method.
1. use `spark-submit`:
```console
bin/spark-submit --class org.apache.spark.sql.execution.benchmark.JoinBenchmark --jars ./core/target/spark-core_2.11-3.0.0-SNAPSHOT-tests.jar ./sql/catalyst/target/spark-sql_2.11-3.0.0-SNAPSHOT-tests.jar
```
2. Generate benchmark result:
```console
SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/test:runMain org.apache.spark.sql.execution.benchmark.JoinBenchmark"
```
## How was this patch tested?
manual tests
Closes #22661 from wangyum/SPARK-25664.
Lead-authored-by: Yuming Wang <yu...@ebay.com>
Co-authored-by: Yuming Wang <wg...@gmail.com>
Co-authored-by: Dongjoon Hyun <do...@apache.org>
Signed-off-by: Dongjoon Hyun <do...@apache.org>
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/e965fb55
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/e965fb55
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/e965fb55
Branch: refs/heads/master
Commit: e965fb55acf714bdd639d13d73f75a7d7b43efca
Parents: 4e141a4
Author: Yuming Wang <yu...@ebay.com>
Authored: Fri Oct 12 16:08:12 2018 -0700
Committer: Dongjoon Hyun <do...@apache.org>
Committed: Fri Oct 12 16:08:12 2018 -0700
----------------------------------------------------------------------
.../org/apache/spark/benchmark/Benchmark.scala | 3 +-
sql/core/benchmarks/JoinBenchmark-results.txt | 75 +++++++
.../sql/execution/benchmark/JoinBenchmark.scala | 216 +++++++------------
3 files changed, 152 insertions(+), 142 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/spark/blob/e965fb55/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala
----------------------------------------------------------------------
diff --git a/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala b/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala
index 7a36b5f..bb389cd 100644
--- a/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala
+++ b/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala
@@ -200,11 +200,12 @@ private[spark] object Benchmark {
def getProcessorName(): String = {
val cpu = if (SystemUtils.IS_OS_MAC_OSX) {
Utils.executeAndGetOutput(Seq("/usr/sbin/sysctl", "-n", "machdep.cpu.brand_string"))
+ .stripLineEnd
} else if (SystemUtils.IS_OS_LINUX) {
Try {
val grepPath = Utils.executeAndGetOutput(Seq("which", "grep")).stripLineEnd
Utils.executeAndGetOutput(Seq(grepPath, "-m", "1", "model name", "/proc/cpuinfo"))
- .stripLineEnd.replaceFirst("model name[\\s*]:[\\s*]", "")
+ .stripLineEnd.replaceFirst("model name[\\s*]:[\\s*]", "")
}.getOrElse("Unknown processor")
} else {
System.getenv("PROCESSOR_IDENTIFIER")
http://git-wip-us.apache.org/repos/asf/spark/blob/e965fb55/sql/core/benchmarks/JoinBenchmark-results.txt
----------------------------------------------------------------------
diff --git a/sql/core/benchmarks/JoinBenchmark-results.txt b/sql/core/benchmarks/JoinBenchmark-results.txt
new file mode 100644
index 0000000..8ceb5e7
--- /dev/null
+++ b/sql/core/benchmarks/JoinBenchmark-results.txt
@@ -0,0 +1,75 @@
+================================================================================================
+Join Benchmark
+================================================================================================
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Join w long: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+Join w long wholestage off 4464 / 4483 4.7 212.9 1.0X
+Join w long wholestage on 289 / 339 72.6 13.8 15.5X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Join w long duplicated: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+Join w long duplicated wholestage off 5662 / 5678 3.7 270.0 1.0X
+Join w long duplicated wholestage on 332 / 345 63.1 15.8 17.0X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Join w 2 ints: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+Join w 2 ints wholestage off 173174 / 173183 0.1 8257.6 1.0X
+Join w 2 ints wholestage on 166350 / 198362 0.1 7932.2 1.0X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Join w 2 longs: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+Join w 2 longs wholestage off 7055 / 7214 3.0 336.4 1.0X
+Join w 2 longs wholestage on 1869 / 1985 11.2 89.1 3.8X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Join w 2 longs duplicated: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+Join w 2 longs duplicated wholestage off 19256 / 20283 1.1 918.2 1.0X
+Join w 2 longs duplicated wholestage on 2467 / 2544 8.5 117.7 7.8X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+outer join w long: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+outer join w long wholestage off 3756 / 3761 5.6 179.1 1.0X
+outer join w long wholestage on 218 / 250 96.2 10.4 17.2X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+semi join w long: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+semi join w long wholestage off 2393 / 2416 8.8 114.1 1.0X
+semi join w long wholestage on 214 / 218 97.9 10.2 11.2X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+sort merge join: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+sort merge join wholestage off 2318 / 2392 0.9 1105.3 1.0X
+sort merge join wholestage on 1669 / 1811 1.3 795.9 1.4X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+sort merge join with duplicates: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+sort merge join with duplicates wholestage off 2966 / 2976 0.7 1414.5 1.0X
+sort merge join with duplicates wholestage on 2413 / 2641 0.9 1150.5 1.2X
+
+OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+shuffle hash join: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
+------------------------------------------------------------------------------------------------
+shuffle hash join wholestage off 1475 / 1479 2.8 351.7 1.0X
+shuffle hash join wholestage on 1209 / 1238 3.5 288.3 1.2X
+
+
http://git-wip-us.apache.org/repos/asf/spark/blob/e965fb55/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/JoinBenchmark.scala
----------------------------------------------------------------------
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/JoinBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/JoinBenchmark.scala
index 37744dc..7bad4cb 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/JoinBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/JoinBenchmark.scala
@@ -19,229 +19,163 @@ package org.apache.spark.sql.execution.benchmark
import org.apache.spark.sql.execution.joins._
import org.apache.spark.sql.functions._
+import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types.IntegerType
/**
- * Benchmark to measure performance for aggregate primitives.
- * To run this:
- * build/sbt "sql/test-only *benchmark.JoinBenchmark"
- *
- * Benchmarks in this file are skipped in normal builds.
+ * Benchmark to measure performance for joins.
+ * To run this benchmark:
+ * {{{
+ * 1. without sbt:
+ * bin/spark-submit --class <this class> --jars <spark core test jar> <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/JoinBenchmark-results.txt".
+ * }}}
*/
-class JoinBenchmark extends BenchmarkWithCodegen {
+object JoinBenchmark extends SqlBasedBenchmark {
- ignore("broadcast hash join, long key") {
+ def broadcastHashJoinLongKey(): Unit = {
val N = 20 << 20
val M = 1 << 16
- val dim = broadcast(sparkSession.range(M).selectExpr("id as k", "cast(id as string) as v"))
- runBenchmark("Join w long", N) {
- val df = sparkSession.range(N).join(dim, (col("id") % M) === col("k"))
+ val dim = broadcast(spark.range(M).selectExpr("id as k", "cast(id as string) as v"))
+ codegenBenchmark("Join w long", N) {
+ val df = spark.range(N).join(dim, (col("id") % M) === col("k"))
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[BroadcastHashJoinExec]).isDefined)
df.count()
}
-
- /*
- Java HotSpot(TM) 64-Bit Server VM 1.7.0_60-b19 on Mac OS X 10.9.5
- Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- Join w long: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- -------------------------------------------------------------------------------------------
- Join w long codegen=false 3002 / 3262 7.0 143.2 1.0X
- Join w long codegen=true 321 / 371 65.3 15.3 9.3X
- */
}
- ignore("broadcast hash join, long key with duplicates") {
+ def broadcastHashJoinLongKeyWithDuplicates(): Unit = {
val N = 20 << 20
val M = 1 << 16
-
- val dim = broadcast(sparkSession.range(M).selectExpr("id as k", "cast(id as string) as v"))
- runBenchmark("Join w long duplicated", N) {
- val dim = broadcast(sparkSession.range(M).selectExpr("cast(id/10 as long) as k"))
- val df = sparkSession.range(N).join(dim, (col("id") % M) === col("k"))
+ val dim = broadcast(spark.range(M).selectExpr("cast(id/10 as long) as k"))
+ codegenBenchmark("Join w long duplicated", N) {
+ val df = spark.range(N).join(dim, (col("id") % M) === col("k"))
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[BroadcastHashJoinExec]).isDefined)
df.count()
}
-
- /*
- *Java HotSpot(TM) 64-Bit Server VM 1.7.0_60-b19 on Mac OS X 10.9.5
- *Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- *Join w long duplicated: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *Join w long duplicated codegen=false 3446 / 3478 6.1 164.3 1.0X
- *Join w long duplicated codegen=true 322 / 351 65.2 15.3 10.7X
- */
}
- ignore("broadcast hash join, two int key") {
+ def broadcastHashJoinTwoIntKey(): Unit = {
val N = 20 << 20
val M = 1 << 16
- val dim2 = broadcast(sparkSession.range(M)
+ val dim2 = broadcast(spark.range(M)
.selectExpr("cast(id as int) as k1", "cast(id as int) as k2", "cast(id as string) as v"))
- runBenchmark("Join w 2 ints", N) {
- val df = sparkSession.range(N).join(dim2,
+ codegenBenchmark("Join w 2 ints", N) {
+ val df = spark.range(N).join(dim2,
(col("id") % M).cast(IntegerType) === col("k1")
&& (col("id") % M).cast(IntegerType) === col("k2"))
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[BroadcastHashJoinExec]).isDefined)
df.count()
}
-
- /*
- *Java HotSpot(TM) 64-Bit Server VM 1.7.0_60-b19 on Mac OS X 10.9.5
- *Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- *Join w 2 ints: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *Join w 2 ints codegen=false 4426 / 4501 4.7 211.1 1.0X
- *Join w 2 ints codegen=true 791 / 818 26.5 37.7 5.6X
- */
}
- ignore("broadcast hash join, two long key") {
+ def broadcastHashJoinTwoLongKey(): Unit = {
val N = 20 << 20
val M = 1 << 16
- val dim3 = broadcast(sparkSession.range(M)
+ val dim3 = broadcast(spark.range(M)
.selectExpr("id as k1", "id as k2", "cast(id as string) as v"))
- runBenchmark("Join w 2 longs", N) {
- val df = sparkSession.range(N).join(dim3,
+ codegenBenchmark("Join w 2 longs", N) {
+ val df = spark.range(N).join(dim3,
(col("id") % M) === col("k1") && (col("id") % M) === col("k2"))
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[BroadcastHashJoinExec]).isDefined)
df.count()
}
-
- /*
- *Java HotSpot(TM) 64-Bit Server VM 1.7.0_60-b19 on Mac OS X 10.9.5
- *Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- *Join w 2 longs: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *Join w 2 longs codegen=false 5905 / 6123 3.6 281.6 1.0X
- *Join w 2 longs codegen=true 2230 / 2529 9.4 106.3 2.6X
- */
}
- ignore("broadcast hash join, two long key with duplicates") {
+ def broadcastHashJoinTwoLongKeyWithDuplicates(): Unit = {
val N = 20 << 20
val M = 1 << 16
- val dim4 = broadcast(sparkSession.range(M)
+ val dim4 = broadcast(spark.range(M)
.selectExpr("cast(id/10 as long) as k1", "cast(id/10 as long) as k2"))
- runBenchmark("Join w 2 longs duplicated", N) {
- val df = sparkSession.range(N).join(dim4,
+ codegenBenchmark("Join w 2 longs duplicated", N) {
+ val df = spark.range(N).join(dim4,
(col("id") bitwiseAND M) === col("k1") && (col("id") bitwiseAND M) === col("k2"))
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[BroadcastHashJoinExec]).isDefined)
df.count()
}
-
- /*
- *Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- *Join w 2 longs duplicated: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *Join w 2 longs duplicated codegen=false 6420 / 6587 3.3 306.1 1.0X
- *Join w 2 longs duplicated codegen=true 2080 / 2139 10.1 99.2 3.1X
- */
}
- ignore("broadcast hash join, outer join long key") {
+ def broadcastHashJoinOuterJoinLongKey(): Unit = {
val N = 20 << 20
val M = 1 << 16
- val dim = broadcast(sparkSession.range(M).selectExpr("id as k", "cast(id as string) as v"))
- runBenchmark("outer join w long", N) {
- val df = sparkSession.range(N).join(dim, (col("id") % M) === col("k"), "left")
+ val dim = broadcast(spark.range(M).selectExpr("id as k", "cast(id as string) as v"))
+ codegenBenchmark("outer join w long", N) {
+ val df = spark.range(N).join(dim, (col("id") % M) === col("k"), "left")
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[BroadcastHashJoinExec]).isDefined)
df.count()
}
-
- /*
- *Java HotSpot(TM) 64-Bit Server VM 1.7.0_60-b19 on Mac OS X 10.9.5
- *Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- *outer join w long: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *outer join w long codegen=false 3055 / 3189 6.9 145.7 1.0X
- *outer join w long codegen=true 261 / 276 80.5 12.4 11.7X
- */
}
- ignore("broadcast hash join, semi join long key") {
+ def broadcastHashJoinSemiJoinLongKey(): Unit = {
val N = 20 << 20
val M = 1 << 16
- val dim = broadcast(sparkSession.range(M).selectExpr("id as k", "cast(id as string) as v"))
- runBenchmark("semi join w long", N) {
- val df = sparkSession.range(N).join(dim, (col("id") % M) === col("k"), "leftsemi")
+ val dim = broadcast(spark.range(M).selectExpr("id as k", "cast(id as string) as v"))
+ codegenBenchmark("semi join w long", N) {
+ val df = spark.range(N).join(dim, (col("id") % M) === col("k"), "leftsemi")
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[BroadcastHashJoinExec]).isDefined)
df.count()
}
-
- /*
- *Java HotSpot(TM) 64-Bit Server VM 1.7.0_60-b19 on Mac OS X 10.9.5
- *Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- *semi join w long: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *semi join w long codegen=false 1912 / 1990 11.0 91.2 1.0X
- *semi join w long codegen=true 237 / 244 88.3 11.3 8.1X
- */
}
- ignore("sort merge join") {
+ def sortMergeJoin(): Unit = {
val N = 2 << 20
- runBenchmark("merge join", N) {
- val df1 = sparkSession.range(N).selectExpr(s"id * 2 as k1")
- val df2 = sparkSession.range(N).selectExpr(s"id * 3 as k2")
+ codegenBenchmark("sort merge join", N) {
+ val df1 = spark.range(N).selectExpr(s"id * 2 as k1")
+ val df2 = spark.range(N).selectExpr(s"id * 3 as k2")
val df = df1.join(df2, col("k1") === col("k2"))
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[SortMergeJoinExec]).isDefined)
df.count()
}
-
- /*
- *Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- *merge join: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *merge join codegen=false 1588 / 1880 1.3 757.1 1.0X
- *merge join codegen=true 1477 / 1531 1.4 704.2 1.1X
- */
}
- ignore("sort merge join with duplicates") {
+ def sortMergeJoinWithDuplicates(): Unit = {
val N = 2 << 20
- runBenchmark("sort merge join", N) {
- val df1 = sparkSession.range(N)
+ codegenBenchmark("sort merge join with duplicates", N) {
+ val df1 = spark.range(N)
.selectExpr(s"(id * 15485863) % ${N*10} as k1")
- val df2 = sparkSession.range(N)
+ val df2 = spark.range(N)
.selectExpr(s"(id * 15485867) % ${N*10} as k2")
val df = df1.join(df2, col("k1") === col("k2"))
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[SortMergeJoinExec]).isDefined)
df.count()
}
-
- /*
- *Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
- *sort merge join: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *sort merge join codegen=false 3626 / 3667 0.6 1728.9 1.0X
- *sort merge join codegen=true 3405 / 3438 0.6 1623.8 1.1X
- */
}
- ignore("shuffle hash join") {
- val N = 4 << 20
- sparkSession.conf.set("spark.sql.shuffle.partitions", "2")
- sparkSession.conf.set("spark.sql.autoBroadcastJoinThreshold", "10000000")
- sparkSession.conf.set("spark.sql.join.preferSortMergeJoin", "false")
- runBenchmark("shuffle hash join", N) {
- val df1 = sparkSession.range(N).selectExpr(s"id as k1")
- val df2 = sparkSession.range(N / 3).selectExpr(s"id * 3 as k2")
- val df = df1.join(df2, col("k1") === col("k2"))
- assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[ShuffledHashJoinExec]).isDefined)
- df.count()
+ def shuffleHashJoin(): Unit = {
+ val N: Long = 4 << 20
+ withSQLConf(
+ SQLConf.SHUFFLE_PARTITIONS.key -> "2",
+ SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "10000000",
+ SQLConf.PREFER_SORTMERGEJOIN.key -> "false") {
+ codegenBenchmark("shuffle hash join", N) {
+ val df1 = spark.range(N).selectExpr(s"id as k1")
+ val df2 = spark.range(N / 3).selectExpr(s"id * 3 as k2")
+ val df = df1.join(df2, col("k1") === col("k2"))
+ assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[ShuffledHashJoinExec]).isDefined)
+ df.count()
+ }
}
+ }
- /*
- *Java HotSpot(TM) 64-Bit Server VM 1.8.0_60-b27 on Windows 7 6.1
- *Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
- *shuffle hash join: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
- *-------------------------------------------------------------------------------------------
- *shuffle hash join codegen=false 2005 / 2010 2.1 478.0 1.0X
- *shuffle hash join codegen=true 1773 / 1792 2.4 422.7 1.1X
- */
+ override def runBenchmarkSuite(): Unit = {
+ runBenchmark("Join Benchmark") {
+ broadcastHashJoinLongKey()
+ broadcastHashJoinLongKeyWithDuplicates()
+ broadcastHashJoinTwoIntKey()
+ broadcastHashJoinTwoLongKey()
+ broadcastHashJoinTwoLongKeyWithDuplicates()
+ broadcastHashJoinOuterJoinLongKey()
+ broadcastHashJoinSemiJoinLongKey()
+ sortMergeJoin()
+ sortMergeJoinWithDuplicates()
+ shuffleHashJoin()
+ }
}
}
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