2018-10-06 11:47:43 -04:00
|
|
|
================================================================================================
|
|
|
|
|
filter & aggregate without group
|
|
|
|
|
================================================================================================
|
|
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
range/filter/sum: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
range/filter/sum wholestage off 45894 47528 2310 45.7 21.9 1.0X
|
|
|
|
|
range/filter/sum wholestage on 3193 3572 213 656.8 1.5 14.4X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
|
|
|
|
|
|
|
|
|
================================================================================================
|
|
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|
range/limit/sum
|
|
|
|
|
================================================================================================
|
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|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
range/limit/sum: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
range/limit/sum wholestage off 202 207 7 2593.1 0.4 1.0X
|
|
|
|
|
range/limit/sum wholestage on 148 161 20 3545.1 0.3 1.4X
|
2018-10-06 11:47:43 -04:00
|
|
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|
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|
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|
================================================================================================
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|
sample
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|
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|
|
================================================================================================
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|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
sample with replacement: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
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|
|
sample with replacement wholestage off 12337 12657 452 10.6 94.1 1.0X
|
|
|
|
|
sample with replacement wholestage on 7355 7368 14 17.8 56.1 1.7X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
sample without replacement: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
sample without replacement wholestage off 3050 3060 14 43.0 23.3 1.0X
|
|
|
|
|
sample without replacement wholestage on 1103 1118 22 118.8 8.4 2.8X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
|
|
|
|
|
|
|
|
|
================================================================================================
|
|
|
|
|
collect
|
|
|
|
|
================================================================================================
|
|
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
collect: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
collect 1 million 324 361 41 3.2 309.4 1.0X
|
|
|
|
|
collect 2 millions 619 700 70 1.7 590.4 0.5X
|
|
|
|
|
collect 4 millions 1214 1293 111 0.9 1158.2 0.3X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
|
|
|
|
|
|
|
|
|
================================================================================================
|
|
|
|
|
collect limit
|
|
|
|
|
================================================================================================
|
|
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
collect limit: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
collect limit 1 million 391 396 5 2.7 373.0 1.0X
|
|
|
|
|
collect limit 2 millions 746 769 26 1.4 711.8 0.5X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
|
|
|
|
|
|
|
|
|
================================================================================================
|
|
|
|
|
generate explode
|
|
|
|
|
================================================================================================
|
|
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
generate explode array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
generate explode array wholestage off 15063 16007 1335 1.1 897.8 1.0X
|
|
|
|
|
generate explode array wholestage on 10909 10932 20 1.5 650.2 1.4X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
generate explode map: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
generate explode map wholestage off 55011 55580 806 0.3 3278.9 1.0X
|
|
|
|
|
generate explode map wholestage on 46009 46445 399 0.4 2742.3 1.2X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
generate posexplode array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
generate posexplode array wholestage off 17987 18866 1244 0.9 1072.1 1.0X
|
|
|
|
|
generate posexplode array wholestage on 11400 11444 38 1.5 679.5 1.6X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
generate inline array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
generate inline array wholestage off 14905 14991 122 1.1 888.4 1.0X
|
|
|
|
|
generate inline array wholestage on 9919 10129 160 1.7 591.2 1.5X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
2018-10-06 11:47:43 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
2019-10-03 11:58:25 -04:00
|
|
|
generate big struct array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
|
|
|
|
generate big struct array wholestage off 508 577 98 0.1 8474.0 1.0X
|
|
|
|
|
generate big struct array wholestage on 451 485 26 0.1 7523.2 1.1X
|
2018-10-06 11:47:43 -04:00
|
|
|
|
2019-10-03 11:58:25 -04:00
|
|
|
OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
|
[SPARK-27707][SQL] Prune unnecessary nested fields from Generate
## What changes were proposed in this pull request?
Performance issue using explode was found when a complex field contains huge array is to get duplicated as the number of exploded array elements. Given example:
```scala
val df = spark.sparkContext.parallelize(Seq(("1",
Array.fill(M)({
val i = math.random
(i.toString, (i + 1).toString, (i + 2).toString, (i + 3).toString)
})))).toDF("col", "arr")
.selectExpr("col", "struct(col, arr) as st")
.selectExpr("col", "st.col as col1", "explode(st.arr) as arr_col")
```
The explode causes `st` to be duplicated as many as the exploded elements.
Benchmarks it:
```
[info] Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
[info] Intel(R) Core(TM) i7-8750H CPU 2.20GHz
[info] generate big nested struct array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
[info] ------------------------------------------------------------------------------------------------------------------------
[info] generate big nested struct array wholestage off 52668 53162 699 0.0 877803.4 1.0X
[info] generate big nested struct array wholestage on 47261 49093 1125 0.0 787690.2 1.1X
[info]
```
The query plan:
```
== Physical Plan ==
Project [col#508, st#512.col AS col1#515, arr_col#519]
+- Generate explode(st#512.arr), [col#508, st#512], false, [arr_col#519]
+- Project [_1#503 AS col#508, named_struct(col, _1#503, arr, _2#504) AS st#512]
+- SerializeFromObject [staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, scala.Tuple2, true]))._1, true, false) AS _1#503, mapobjects(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), if (isnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))) null else named_struct(_1, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))._1, true, false), _2, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))._2, true, false), _3, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))._3, true, false), _4, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))._4, true, false)), knownnotnull(assertnotnull(input[0, scala.Tuple2, true]))._2, None) AS _2#504]
+- Scan[obj#534]
```
This patch takes nested column pruning approach to prune unnecessary nested fields. It adds a projection of the needed nested fields as aliases on the child of `Generate`, and substitutes them by alias attributes on the projection on top of `Generate`.
Benchmarks it after the change:
```
[info] Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
[info] Intel(R) Core(TM) i7-8750H CPU 2.20GHz
[info] generate big nested struct array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
[info] ------------------------------------------------------------------------------------------------------------------------
[info] generate big nested struct array wholestage off 311 331 28 0.2 5188.6 1.0X
[info] generate big nested struct array wholestage on 297 312 15 0.2 4947.3 1.0X
[info]
```
The query plan:
```
== Physical Plan ==
Project [col#592, _gen_alias_608#608 AS col1#599, arr_col#603]
+- Generate explode(st#596.arr), [col#592, _gen_alias_608#608], false, [arr_col#603]
+- Project [_1#587 AS col#592, named_struct(col, _1#587, arr, _2#588) AS st#596, _1#587 AS _gen_alias_608#608]
+- SerializeFromObject [staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(in
put[0, scala.Tuple2, true]))._1, true, false) AS _1#587, mapobjects(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4),
if (isnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))) null else named_struct(_1, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))._1, true, false), _2, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))._2, true, false), _3, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))._3, true, false), _4, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))._4, true, false)), knownnotnull(assertnotnull(input[0, scala.Tuple2, true]))._2, None) AS _2#588]
+- Scan[obj#586]
```
This behavior is controlled by a SQL config `spark.sql.optimizer.expression.nestedPruning.enabled`.
## How was this patch tested?
Added benchmark.
Closes #24637 from viirya/SPARK-27707.
Lead-authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Co-authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2019-07-19 02:32:07 -04:00
|
|
|
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
|
|
|
|
|
generate big nested struct array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
|
|
|
|
|
------------------------------------------------------------------------------------------------------------------------
|
2019-10-03 11:58:25 -04:00
|
|
|
generate big nested struct array wholestage off 537 567 43 0.1 8944.4 1.0X
|
|
|
|
|
generate big nested struct array wholestage on 528 546 24 0.1 8804.2 1.0X
|
[SPARK-27707][SQL] Prune unnecessary nested fields from Generate
## What changes were proposed in this pull request?
Performance issue using explode was found when a complex field contains huge array is to get duplicated as the number of exploded array elements. Given example:
```scala
val df = spark.sparkContext.parallelize(Seq(("1",
Array.fill(M)({
val i = math.random
(i.toString, (i + 1).toString, (i + 2).toString, (i + 3).toString)
})))).toDF("col", "arr")
.selectExpr("col", "struct(col, arr) as st")
.selectExpr("col", "st.col as col1", "explode(st.arr) as arr_col")
```
The explode causes `st` to be duplicated as many as the exploded elements.
Benchmarks it:
```
[info] Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
[info] Intel(R) Core(TM) i7-8750H CPU 2.20GHz
[info] generate big nested struct array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
[info] ------------------------------------------------------------------------------------------------------------------------
[info] generate big nested struct array wholestage off 52668 53162 699 0.0 877803.4 1.0X
[info] generate big nested struct array wholestage on 47261 49093 1125 0.0 787690.2 1.1X
[info]
```
The query plan:
```
== Physical Plan ==
Project [col#508, st#512.col AS col1#515, arr_col#519]
+- Generate explode(st#512.arr), [col#508, st#512], false, [arr_col#519]
+- Project [_1#503 AS col#508, named_struct(col, _1#503, arr, _2#504) AS st#512]
+- SerializeFromObject [staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, scala.Tuple2, true]))._1, true, false) AS _1#503, mapobjects(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), if (isnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))) null else named_struct(_1, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))._1, true, false), _2, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))._2, true, false), _3, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))._3, true, false), _4, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue84, MapObjects_loopIsNull84, ObjectType(class scala.Tuple4), true))._4, true, false)), knownnotnull(assertnotnull(input[0, scala.Tuple2, true]))._2, None) AS _2#504]
+- Scan[obj#534]
```
This patch takes nested column pruning approach to prune unnecessary nested fields. It adds a projection of the needed nested fields as aliases on the child of `Generate`, and substitutes them by alias attributes on the projection on top of `Generate`.
Benchmarks it after the change:
```
[info] Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
[info] Intel(R) Core(TM) i7-8750H CPU 2.20GHz
[info] generate big nested struct array: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
[info] ------------------------------------------------------------------------------------------------------------------------
[info] generate big nested struct array wholestage off 311 331 28 0.2 5188.6 1.0X
[info] generate big nested struct array wholestage on 297 312 15 0.2 4947.3 1.0X
[info]
```
The query plan:
```
== Physical Plan ==
Project [col#592, _gen_alias_608#608 AS col1#599, arr_col#603]
+- Generate explode(st#596.arr), [col#592, _gen_alias_608#608], false, [arr_col#603]
+- Project [_1#587 AS col#592, named_struct(col, _1#587, arr, _2#588) AS st#596, _1#587 AS _gen_alias_608#608]
+- SerializeFromObject [staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(in
put[0, scala.Tuple2, true]))._1, true, false) AS _1#587, mapobjects(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4),
if (isnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))) null else named_struct(_1, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))._1, true, false), _2, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))._2, true, false), _3, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))._3, true, false), _4, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(lambdavariable(MapObjects_loopValue102, MapObjects_loopIsNull102, ObjectType(class scala.Tuple4), true))._4, true, false)), knownnotnull(assertnotnull(input[0, scala.Tuple2, true]))._2, None) AS _2#588]
+- Scan[obj#586]
```
This behavior is controlled by a SQL config `spark.sql.optimizer.expression.nestedPruning.enabled`.
## How was this patch tested?
Added benchmark.
Closes #24637 from viirya/SPARK-27707.
Lead-authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Co-authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2019-07-19 02:32:07 -04:00
|
|
|
|
2018-10-06 11:47:43 -04:00
|
|
|
|
|
|
|
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================================================================================================
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generate regular generator
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2019-10-03 11:58:25 -04:00
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OpenJDK 64-Bit Server VM 1.8.0_222-b10 on Linux 3.10.0-862.3.2.el7.x86_64
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2018-10-06 11:47:43 -04:00
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Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
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2019-10-03 11:58:25 -04:00
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generate stack: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
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generate stack wholestage off 27220 27608 548 0.6 1622.5 1.0X
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generate stack wholestage on 20070 20170 117 0.8 1196.3 1.4X
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2018-10-06 11:47:43 -04:00
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