spark-instrumented-optimizer/core
Kazuaki Ishizaki 4807d381bb [SPARK-10399][CORE][SQL] Introduce multiple MemoryBlocks to choose several types of memory block
## What changes were proposed in this pull request?

This PR allows us to use one of several types of `MemoryBlock`, such as byte array, int array, long array, or `java.nio.DirectByteBuffer`. To use `java.nio.DirectByteBuffer` allows to have off heap memory which is automatically deallocated by JVM. `MemoryBlock`  class has primitive accessors like `Platform.getInt()`, `Platform.putint()`, or `Platform.copyMemory()`.

This PR uses `MemoryBlock` for `OffHeapColumnVector`, `UTF8String`, and other places. This PR can improve performance of operations involving memory accesses (e.g. `UTF8String.trim`) by 1.8x.

For now, this PR does not use `MemoryBlock` for `BufferHolder` based on cloud-fan's [suggestion](https://github.com/apache/spark/pull/11494#issuecomment-309694290).

Since this PR is a successor of #11494, close #11494. Many codes were ported from #11494. Many efforts were put here. **I think this PR should credit to yzotov.**

This PR can achieve **1.1-1.4x performance improvements** for  operations in `UTF8String` or `Murmur3_x86_32`. Other operations are almost comparable performances.

Without this PR
```
OpenJDK 64-Bit Server VM 1.8.0_121-8u121-b13-0ubuntu1.16.04.2-b13 on Linux 4.4.0-22-generic
Intel(R) Xeon(R) CPU E5-2667 v3  3.20GHz
OpenJDK 64-Bit Server VM 1.8.0_121-8u121-b13-0ubuntu1.16.04.2-b13 on Linux 4.4.0-22-generic
Intel(R) Xeon(R) CPU E5-2667 v3  3.20GHz
Hash byte arrays with length 268435487:  Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
Murmur3_x86_32                                 526 /  536          0.0   131399881.5       1.0X

UTF8String benchmark:                    Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
hashCode                                       525 /  552       1022.6           1.0       1.0X
substring                                      414 /  423       1298.0           0.8       1.3X
```

With this PR
```
OpenJDK 64-Bit Server VM 1.8.0_121-8u121-b13-0ubuntu1.16.04.2-b13 on Linux 4.4.0-22-generic
Intel(R) Xeon(R) CPU E5-2667 v3  3.20GHz
Hash byte arrays with length 268435487:  Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
Murmur3_x86_32                                 474 /  488          0.0   118552232.0       1.0X

UTF8String benchmark:                    Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
hashCode                                       476 /  480       1127.3           0.9       1.0X
substring                                      287 /  291       1869.9           0.5       1.7X
```

Benchmark program
```
test("benchmark Murmur3_x86_32") {
  val length = 8192 * 32768 + 31
  val seed = 42L
  val iters = 1 << 2
  val random = new Random(seed)
  val arrays = Array.fill[MemoryBlock](numArrays) {
    val bytes = new Array[Byte](length)
    random.nextBytes(bytes)
    new ByteArrayMemoryBlock(bytes, Platform.BYTE_ARRAY_OFFSET, length)
  }

  val benchmark = new Benchmark("Hash byte arrays with length " + length,
    iters * numArrays, minNumIters = 20)
  benchmark.addCase("HiveHasher") { _: Int =>
    var sum = 0L
    for (_ <- 0L until iters) {
      sum += HiveHasher.hashUnsafeBytesBlock(
        arrays(i), Platform.BYTE_ARRAY_OFFSET, length)
    }
  }
  benchmark.run()
}

test("benchmark UTF8String") {
  val N = 512 * 1024 * 1024
  val iters = 2
  val benchmark = new Benchmark("UTF8String benchmark", N, minNumIters = 20)
  val str0 = new java.io.StringWriter() { { for (i <- 0 until N) { write(" ") } } }.toString
  val s0 = UTF8String.fromString(str0)
  benchmark.addCase("hashCode") { _: Int =>
    var h: Int = 0
    for (_ <- 0L until iters) { h += s0.hashCode }
  }
  benchmark.addCase("substring") { _: Int =>
    var s: UTF8String = null
    for (_ <- 0L until iters) { s = s0.substring(N / 2 - 5, N / 2 + 5) }
  }
  benchmark.run()
}
```

I run [this benchmark program](https://gist.github.com/kiszk/94f75b506c93a663bbbc372ffe8f05de) using [the commit](ee5a79861c). I got the following results:

```
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
------------------------------------------------------------------------------------------------
ByteArrayMemoryBlock get/putInt()              220 /  221        609.3           1.6       1.0X
Platform get/putInt(byte[])                    220 /  236        610.9           1.6       1.0X
Platform get/putInt(Object)                    492 /  494        272.8           3.7       0.4X
OnHeapMemoryBlock get/putLong()                322 /  323        416.5           2.4       0.7X
long[]                                         221 /  221        608.0           1.6       1.0X
Platform get/putLong(long[])                   321 /  321        418.7           2.4       0.7X
Platform get/putLong(Object)                   561 /  563        239.2           4.2       0.4X
```

I also run [this benchmark program](https://gist.github.com/kiszk/5fdb4e03733a5d110421177e289d1fb5) for comparing performance of `Platform.copyMemory()`.
```
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
Platform copyMemory:                     Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
Object to Object                              1961 / 1967          8.6         116.9       1.0X
System.arraycopy Object to Object             1917 / 1921          8.8         114.3       1.0X
byte array to byte array                      1961 / 1968          8.6         116.9       1.0X
System.arraycopy byte array to byte array      1909 / 1937          8.8         113.8       1.0X
int array to int array                        1921 / 1990          8.7         114.5       1.0X
double array to double array                  1918 / 1923          8.7         114.3       1.0X
Object to byte array                          1961 / 1967          8.6         116.9       1.0X
Object to short array                         1965 / 1972          8.5         117.1       1.0X
Object to int array                           1910 / 1915          8.8         113.9       1.0X
Object to float array                         1971 / 1978          8.5         117.5       1.0X
Object to double array                        1919 / 1944          8.7         114.4       1.0X
byte array to Object                          1959 / 1967          8.6         116.8       1.0X
int array to Object                           1961 / 1970          8.6         116.9       1.0X
double array to Object                        1917 / 1924          8.8         114.3       1.0X
```

These results show three facts:
1. According to the second/third or sixth/seventh results in the first experiment, if we use `Platform.get/putInt(Object)`, we achieve more than 2x worse performance than `Platform.get/putInt(byte[])` with concrete type (i.e. `byte[]`).
2. According to the second/third or fourth/fifth/sixth results in the first experiment, the fastest way to access an array element on Java heap is `array[]`. **Cons of `array[]` is that it is not possible to support unaligned-8byte access.**
3. According to the first/second/third or fourth/sixth/seventh results in the first experiment, `getInt()/putInt() or getLong()/putLong()` in subclasses of `MemoryBlock` can achieve comparable performance to `Platform.get/putInt()` or `Platform.get/putLong()` with concrete type (second or sixth result). There is no overhead regarding virtual call.
4. According to results in the second experiment, for `Platform.copy()`, to pass `Object` can achieve the same performance as to pass any type of primitive array as source or destination.
5. According to second/fourth results in the second experiment, `Platform.copy()` can achieve the same performance as `System.arrayCopy`. **It would be good to use `Platform.copy()` since `Platform.copy()` can take any types for src and dst.**

We are incrementally replace `Platform.get/putXXX` with `MemoryBlock.get/putXXX`. This is because we have two advantages.
1) Achieve better performance due to having a concrete type for an array.
2) Use simple OO design instead of passing `Object`
It is easy to use `MemoryBlock` in `InternalRow`, `BufferHolder`, `TaskMemoryManager`, and others that are already abstracted. It is not easy to use `MemoryBlock` in utility classes related to hashing or others.

Other candidates are
- UnsafeRow, UnsafeArrayData, UnsafeMapData, SpecificUnsafeRowJoiner
- UTF8StringBuffer
- BufferHolder
- TaskMemoryManager
- OnHeapColumnVector
- BytesToBytesMap
- CachedBatch
- classes for hash
- others.

## How was this patch tested?

Added `UnsafeMemoryAllocator`

Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>

Closes #19222 from kiszk/SPARK-10399.
2018-04-06 10:13:59 +08:00
..
src [SPARK-10399][CORE][SQL] Introduce multiple MemoryBlocks to choose several types of memory block 2018-04-06 10:13:59 +08:00
pom.xml [SPARK-23028] Bump master branch version to 2.4.0-SNAPSHOT 2018-01-13 00:37:59 +08:00