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[SPARK-25476][SPARK-25510][TEST] Refactor AggregateBenchmark and add a new trait to better support Dataset and DataFrame API #22484

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[SPARK-25476][SPARK-25510][TEST] Refactor AggregateBenchmark and add a new trait to better support Dataset and DataFrame API #22484

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649f296
Refactor AggregateBenchmark
wangyum Sep 20, 2018
e0c6d09
Merge remote-tracking branch 'upstream/master' into SPARK-25476
wangyum Sep 21, 2018
42230b6
Add RunBenchmarkWithCodegen
wangyum Sep 22, 2018
2d778a4
Rename RunBenchmarkWithCodegen to SqlBasedBenchmark
wangyum Sep 24, 2018
536d4e9
Add withSQLConf to SqlBasedBenchmark
wangyum Sep 24, 2018
f783099
true.toString -> "true" and false.toString -> "false"
wangyum Sep 25, 2018
d5fecdc
Fix indentation
wangyum Sep 25, 2018
23f1bd8
Merge remote-tracking branch 'upstream/master' into SPARK-25476
wangyum Sep 26, 2018
0fae54d
use SQLHelper
wangyum Sep 26, 2018
45add92
Update result (#12)
dongjoon-hyun Sep 27, 2018
3439992
Fix string variable
wangyum Sep 27, 2018
6c46ad5
Address comments
wangyum Oct 1, 2018
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154 changes: 154 additions & 0 deletions sql/core/benchmarks/AggregateBenchmark-results.txt
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================================================================================================
aggregate without grouping
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

agg w/o group: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
agg w/o group wholestage off 39650 / 46049 52.9 18.9 1.0X
agg w/o group wholestage on 1224 / 1413 1713.5 0.6 32.4X


================================================================================================
stat functions
================================================================================================

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@davies Do you know how to generate there benchmark:

spark/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/AggregateBenchmark.scala

Lines 70 to 78 in 3c3eebc

Using ImperativeAggregate (as implemented in Spark 1.6):
Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
stddev: Avg Time(ms) Avg Rate(M/s) Relative Rate
-------------------------------------------------------------------------------
stddev w/o codegen 2019.04 10.39 1.00 X
stddev w codegen 2097.29 10.00 0.96 X
kurtosis w/o codegen 2108.99 9.94 0.96 X
kurtosis w codegen 2090.69 10.03 0.97 X

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

stddev: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
stddev wholestage off 6149 / 6366 17.1 58.6 1.0X
stddev wholestage on 871 / 881 120.4 8.3 7.1X

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

kurtosis: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
kurtosis wholestage off 28822 / 29231 3.6 274.9 1.0X
kurtosis wholestage on 929 / 944 112.9 8.9 31.0X


================================================================================================
aggregate with linear keys
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

Aggregate w keys: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
codegen = F 7956 / 7967 10.5 94.8 1.0X
codegen = T hashmap = F 3872 / 4049 21.7 46.2 2.1X
codegen = T hashmap = T 872 / 883 96.3 10.4 9.1X


================================================================================================
aggregate with randomized keys
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

Aggregate w keys: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
codegen = F 9088 / 9240 9.2 108.3 1.0X
codegen = T hashmap = F 5065 / 5238 16.6 60.4 1.8X
codegen = T hashmap = T 1722 / 1768 48.7 20.5 5.3X


================================================================================================
aggregate with string key
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

Aggregate w string key: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
codegen = F 3666 / 3704 5.7 174.8 1.0X
codegen = T hashmap = F 2322 / 2357 9.0 110.7 1.6X
codegen = T hashmap = T 1643 / 1676 12.8 78.3 2.2X


================================================================================================
aggregate with decimal key
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

Aggregate w decimal key: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
codegen = F 2688 / 2704 7.8 128.2 1.0X
codegen = T hashmap = F 1401 / 1430 15.0 66.8 1.9X
codegen = T hashmap = T 394 / 415 53.2 18.8 6.8X


================================================================================================
aggregate with multiple key types
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

Aggregate w multiple keys: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
codegen = F 5380 / 5437 3.9 256.5 1.0X
codegen = T hashmap = F 3554 / 3648 5.9 169.5 1.5X
codegen = T hashmap = T 2687 / 2719 7.8 128.1 2.0X


================================================================================================
max function bytecode size of wholestagecodegen
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

max function bytecode size: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
codegen = F 375 / 416 1.7 572.0 1.0X
codegen = T hugeMethodLimit = 10000 231 / 245 2.8 352.0 1.6X
codegen = T hugeMethodLimit = 1500 383 / 412 1.7 583.7 1.0X


================================================================================================
cube
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

cube: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
cube wholestage off 2250 / 2266 2.3 429.1 1.0X
cube wholestage on 907 / 945 5.8 173.0 2.5X


================================================================================================
hash and BytesToBytesMap
================================================================================================

Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6
Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz

BytesToBytesMap: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
UnsafeRowhash 205 / 215 102.4 9.8 1.0X
murmur3 hash 104 / 111 202.0 4.9 2.0X
fast hash 55 / 60 381.2 2.6 3.7X
arrayEqual 132 / 139 158.9 6.3 1.6X
Java HashMap (Long) 89 / 103 235.9 4.2 2.3X
Java HashMap (two ints) 91 / 107 229.2 4.4 2.2X
Java HashMap (UnsafeRow) 759 / 772 27.6 36.2 0.3X
LongToUnsafeRowMap (opt=false) 384 / 406 54.7 18.3 0.5X
LongToUnsafeRowMap (opt=true) 82 / 88 256.5 3.9 2.5X
BytesToBytesMap (off Heap) 753 / 811 27.8 35.9 0.3X
BytesToBytesMap (on Heap) 765 / 784 27.4 36.5 0.3X
Aggregate HashMap 35 / 39 591.4 1.7 5.8X


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