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[GitHub] [spark] c21 opened a new pull request #32357: [SPARK-35235][SQL] Add row-based hash map into aggregate benchmark
c21 opened a new pull request #32357:
URL: https://github.com/apache/spark/pull/32357
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`AggregateBenchmark` is only testing the performance for vectorized fast hash map, but not row-based hash map (which is used by default). We should add the row-based hash map into the benchmark.
java 8 benchmark run - https://github.com/c21/spark/actions/runs/787731549
java 11 benchmark run - https://github.com/c21/spark/actions/runs/787742858
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To have and track a basic sense of benchmarking different fast hash map used in hash aggregate.
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No.
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Existing unit test, as this only touches benchmark code.
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[GitHub] [spark] cloud-fan commented on a change in pull request #32357: [SPARK-35235][SQL] Add row-based hash map into aggregate benchmark
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #32357:
URL: https://github.com/apache/spark/pull/32357#discussion_r620914345
##########
File path: sql/core/benchmarks/AggregateBenchmark-jdk11-results.txt
##########
@@ -2,142 +2,147 @@
aggregate without grouping
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
agg w/o group: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-agg w/o group wholestage off 63666 64021 502 32.9 30.4 1.0X
-agg w/o group wholestage on 882 912 37 2376.9 0.4 72.2X
+agg w/o group wholestage off 82274 82877 853 25.5 39.2 1.0X
+agg w/o group wholestage on 1322 1358 37 1586.7 0.6 62.2X
================================================================================================
stat functions
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
stddev: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-stddev wholestage off 7370 7688 450 14.2 70.3 1.0X
-stddev wholestage on 931 997 50 112.6 8.9 7.9X
+stddev wholestage off 8975 9129 219 11.7 85.6 1.0X
+stddev wholestage on 1424 1444 34 73.6 13.6 6.3X
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
kurtosis: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-kurtosis wholestage off 30901 31209 436 3.4 294.7 1.0X
-kurtosis wholestage on 950 996 33 110.4 9.1 32.5X
+kurtosis wholestage off 42273 42424 213 2.5 403.1 1.0X
+kurtosis wholestage on 1492 1528 27 70.3 14.2 28.3X
================================================================================================
aggregate with linear keys
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
Aggregate w keys: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-codegen = F 8845 8874 41 9.5 105.4 1.0X
-codegen = T hashmap = F 5804 5854 47 14.5 69.2 1.5X
-codegen = T hashmap = T 954 1001 35 87.9 11.4 9.3X
+codegen = F 10873 10998 176 7.7 129.6 1.0X
+codegen = T, hashmap = F 5906 6005 95 14.2 70.4 1.8X
+codegen = T, row-based hashmap = T 2325 2410 94 36.1 27.7 4.7X
+codegen = T, vectorized hashmap = T 1185 1259 78 70.8 14.1 9.2X
Review comment:
interesting, we should probably pick vectorized hashmap under certain conditions.
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[GitHub] [spark] cloud-fan closed pull request #32357: [SPARK-35235][SQL][TEST] Add row-based hash map into aggregate benchmark
Posted by GitBox <gi...@apache.org>.
cloud-fan closed pull request #32357:
URL: https://github.com/apache/spark/pull/32357
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[GitHub] [spark] c21 commented on a change in pull request #32357: [SPARK-35235][SQL][TEST] Add row-based hash map into aggregate benchmark
Posted by GitBox <gi...@apache.org>.
c21 commented on a change in pull request #32357:
URL: https://github.com/apache/spark/pull/32357#discussion_r620945924
##########
File path: sql/core/benchmarks/AggregateBenchmark-jdk11-results.txt
##########
@@ -2,142 +2,147 @@
aggregate without grouping
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
agg w/o group: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-agg w/o group wholestage off 63666 64021 502 32.9 30.4 1.0X
-agg w/o group wholestage on 882 912 37 2376.9 0.4 72.2X
+agg w/o group wholestage off 82274 82877 853 25.5 39.2 1.0X
+agg w/o group wholestage on 1322 1358 37 1586.7 0.6 62.2X
================================================================================================
stat functions
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
stddev: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-stddev wholestage off 7370 7688 450 14.2 70.3 1.0X
-stddev wholestage on 931 997 50 112.6 8.9 7.9X
+stddev wholestage off 8975 9129 219 11.7 85.6 1.0X
+stddev wholestage on 1424 1444 34 73.6 13.6 6.3X
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
kurtosis: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-kurtosis wholestage off 30901 31209 436 3.4 294.7 1.0X
-kurtosis wholestage on 950 996 33 110.4 9.1 32.5X
+kurtosis wholestage off 42273 42424 213 2.5 403.1 1.0X
+kurtosis wholestage on 1492 1528 27 70.3 14.2 28.3X
================================================================================================
aggregate with linear keys
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
Aggregate w keys: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-codegen = F 8845 8874 41 9.5 105.4 1.0X
-codegen = T hashmap = F 5804 5854 47 14.5 69.2 1.5X
-codegen = T hashmap = T 954 1001 35 87.9 11.4 9.3X
+codegen = F 10873 10998 176 7.7 129.6 1.0X
+codegen = T, hashmap = F 5906 6005 95 14.2 70.4 1.8X
+codegen = T, row-based hashmap = T 2325 2410 94 36.1 27.7 4.7X
+codegen = T, vectorized hashmap = T 1185 1259 78 70.8 14.1 9.2X
Review comment:
@cloud-fan - this sounds interesting to me. Created SPARK-35241 for followup, thanks.
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[GitHub] [spark] SparkQA commented on pull request #32357: [SPARK-35235][SQL] Add row-based hash map into aggregate benchmark
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #32357:
URL: https://github.com/apache/spark/pull/32357#issuecomment-827322010
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[GitHub] [spark] c21 commented on pull request #32357: [SPARK-35235][SQL] Add row-based hash map into aggregate benchmark
Posted by GitBox <gi...@apache.org>.
c21 commented on pull request #32357:
URL: https://github.com/apache/spark/pull/32357#issuecomment-827355552
@cloud-fan could you help take a look when you have time? Thanks.
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[GitHub] [spark] cloud-fan commented on a change in pull request #32357: [SPARK-35235][SQL] Add row-based hash map into aggregate benchmark
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #32357:
URL: https://github.com/apache/spark/pull/32357#discussion_r620914581
##########
File path: sql/core/benchmarks/AggregateBenchmark-jdk11-results.txt
##########
@@ -2,142 +2,147 @@
aggregate without grouping
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
agg w/o group: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-agg w/o group wholestage off 63666 64021 502 32.9 30.4 1.0X
-agg w/o group wholestage on 882 912 37 2376.9 0.4 72.2X
+agg w/o group wholestage off 82274 82877 853 25.5 39.2 1.0X
+agg w/o group wholestage on 1322 1358 37 1586.7 0.6 62.2X
================================================================================================
stat functions
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
stddev: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-stddev wholestage off 7370 7688 450 14.2 70.3 1.0X
-stddev wholestage on 931 997 50 112.6 8.9 7.9X
+stddev wholestage off 8975 9129 219 11.7 85.6 1.0X
+stddev wholestage on 1424 1444 34 73.6 13.6 6.3X
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
kurtosis: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-kurtosis wholestage off 30901 31209 436 3.4 294.7 1.0X
-kurtosis wholestage on 950 996 33 110.4 9.1 32.5X
+kurtosis wholestage off 42273 42424 213 2.5 403.1 1.0X
+kurtosis wholestage on 1492 1528 27 70.3 14.2 28.3X
================================================================================================
aggregate with linear keys
================================================================================================
-OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
-Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
+OpenJDK 64-Bit Server VM 11.0.11+9-LTS on Linux 5.4.0-1046-azure
+Intel(R) Xeon(R) CPU E5-2673 v3 @ 2.40GHz
Aggregate w keys: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
-codegen = F 8845 8874 41 9.5 105.4 1.0X
-codegen = T hashmap = F 5804 5854 47 14.5 69.2 1.5X
-codegen = T hashmap = T 954 1001 35 87.9 11.4 9.3X
+codegen = F 10873 10998 176 7.7 129.6 1.0X
+codegen = T, hashmap = F 5906 6005 95 14.2 70.4 1.8X
+codegen = T, row-based hashmap = T 2325 2410 94 36.1 27.7 4.7X
+codegen = T, vectorized hashmap = T 1185 1259 78 70.8 14.1 9.2X
Review comment:
e.g. single group key.
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[GitHub] [spark] c21 commented on pull request #32357: [SPARK-35235][SQL][TEST] Add row-based hash map into aggregate benchmark
Posted by GitBox <gi...@apache.org>.
c21 commented on pull request #32357:
URL: https://github.com/apache/spark/pull/32357#issuecomment-827931841
Thank you @cloud-fan for review!
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[GitHub] [spark] cloud-fan commented on pull request #32357: [SPARK-35235][SQL][TEST] Add row-based hash map into aggregate benchmark
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on pull request #32357:
URL: https://github.com/apache/spark/pull/32357#issuecomment-827360883
thanks, merging to master!
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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #32357:
URL: https://github.com/apache/spark/pull/32357#issuecomment-827441888
**[Test build #137981 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/137981/testReport)** for PR 32357 at commit [`469ac63`](https://github.com/apache/spark/commit/469ac63f7df8ae1c7cd0457fc8027c6d6bff82e3).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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SparkQA commented on pull request #32357:
URL: https://github.com/apache/spark/pull/32357#issuecomment-827304353
**[Test build #137981 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/137981/testReport)** for PR 32357 at commit [`469ac63`](https://github.com/apache/spark/commit/469ac63f7df8ae1c7cd0457fc8027c6d6bff82e3).
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