[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 ping @rednaxelafx --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 ping @rednaxelafx --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
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[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 ping @rednaxelafx --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 ping @rednaxelafx --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 @rxin What do you think about this data? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue:
https://github.com/apache/spark/pull/19222
@rxin @cloud-fan I am very sorry for preparing performance data since I was
busy these weeks.
I confirmed that `MemoryBlock` approach is faster for OnHeap and is equal
to for OffHeap compared to `Platform` approach.
I ran [this benchmark
program](https://gist.github.com/kiszk/3d0db455166a7e2835ffdaf15c633f29) that
includes potentially polymorphic call for `MemoryBlock` like
```
def getMB(g: Int): MemoryBlock = {
if (g < mIters) {
byteArrayMB
} else if (g < mIters * 2) {
onHeapMB
} else if (g < mIters * 3) {
offHeapMB
...
} else {
null
}
}
benchmark.addCase("ByteArrayMemoryBlock getInt()") { t: Int =>
val mb = getMB(g)
if (t >= 0) g += 1
var sum = 0
for (_ <- 0L until iters) {
var i = 0
while (i < N / 4) {
sum += mb.getInt(i * 4)
i += 1
}
}
}
```
```
OpenJDK 64-Bit Server VM 1.8.0_151-8u151-b12-0ubuntu0.16.04.2-b12 on Linux
4.4.0-66-generic
Intel(R) Xeon(R) CPU E5-2667 v3 @ 3.20GHz
Memory access benchmarks:Best/Avg Time(ms)Rate(M/s)
Per Row(ns) Relative
Platform getInt(Object byte[])1348 / 1355199.1
5.0 1.0X
ByteArrayMemoryBlock getInt() 375 / 375716.6
1.4 3.6X
OnHeapMemoryBlock getInt() 374 / 376717.1
1.4 3.6X
Platform getInt(Object offHeap)327 / 328820.0
1.2 4.1X
OffHeapMemoryBlock get() 325 / 403827.1
1.2 4.2X
Platform putInt(Object byte[]) 848 / 852316.5
3.2 1.6X
ByteArrayMemoryBlock putInt() 571 / 571470.4
2.1 2.4X
OnHeapMemoryBlock putInt() 575 / 575467.2
2.1 2.3X
Platform putInt(Object offHeap)582 / 584461.0
2.2 2.3X
OffHeapMemoryBlock putInt()583 / 584460.1
2.2 2.3X
```
WDYT?
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[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 I think that one memory block in each iteration is more representative with having possibility of megamorphism. This is because in the typicalusages in Spark, a data structure is actually dominated by one of memory types. For example, `UTF8String` uses only `ByteArrayMemoryBlock` while `OnHeapMemoryBlock` and `ByteArrayMemoryBlock` are loaded In the future, I think that we will use only one of three Memoryblocks for `UnsafeRow` depends on the setting in `SparkConf`. We will not use `OffHeapMemoryBlock` for some of `UnsafeRow` and `OnHeapMemoryBlock` for the rest of `UnsafeRow`. I think that current concern is whether there is performance degradation at possible megamorphic call sites when three MemoryBlock are loaded. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/19222 Instead of round-robin the memory block type across iterations, can we just operate on all the memory blocks in each iteration? Then we can remove the `if-else` and make the benchmark focus more on the memory block? As a comparison, we can create a byte array, a long array, an offheap array, and also operate on them in each iteration. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 @rxin Sorry, I do not have more data now. I will work for this next week. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user rxin commented on the issue: https://github.com/apache/spark/pull/19222 @kiszk do you have more data now? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user rxin commented on the issue: https://github.com/apache/spark/pull/19222 OK thanks please do that. Does TPC-DS even trigger 2 call sites? E.g. ByteArrayMemoryBlock and OnHeapMemoryBlock. Even there it might introduce a conditional branch after JIT that could lead to perf degradation. I also really worry about off-heap mode, in which all three callsites can exist and lead to massive degradation. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 @rxin While I did not perf microbench for megamorphic (up to 3 `ByteArrayMemoryBlock`, `OnHeapMemoryBlock`, and `OffHeapMemoryBlock`) callsites, we confirmed that there is no performance regression in TPC-DS. It seem to be representative regarding real workloads. I will create and perf microbench for megamorphic (up to 3 `ByteArrayMemoryBlock`, `OnHeapMemoryBlock`, and `OffHeapMemoryBlock`) callsites. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user rxin commented on the issue: https://github.com/apache/spark/pull/19222 Sorry this thread is too long for me to follow. I might be bringing up a point that has been brought up before. @kiszk did your perf tests take into account megamorphic callsites? It seems to me from a quick cursory look the benchmark result might not be accurate for real workloads if there are only one implementations of the MemoryBlock loaded. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #19222: [SPARK-10399][SPARK-23879][CORE][SQL] Introduce multiple...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/19222 @cloud-fan yeah, good point. I created a new JIRA entry which has sub-tasks for the following works. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
