ding created SPARK-17951:
----------------------------
Summary: BlockFetch with multiple threads slows down after spark
1.6
Key: SPARK-17951
URL: https://issues.apache.org/jira/browse/SPARK-17951
Project: Spark
Issue Type: Bug
Components: Block Manager, Spark Core
Affects Versions: 1.6.2
Environment: cluster with 8 node, each node has 28 cores. 10Gb network
Reporter: ding
The following code demonstrates the issue:
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName(s"BMTest")
val size = 3344570
val sc = new SparkContext(conf)
val data = sc.parallelize(1 to 100, 8)
var accum = sc.accumulator(0.0, "get remote bytes")
var i = 0
while(i < 91) {
accum = sc.accumulator(0.0, "get remote bytes")
val test = data.mapPartitionsWithIndex { (pid, iter) =>
val N = size
val bm = SparkEnv.get.blockManager
val blockId = TaskResultBlockId(10*i + pid)
val test = new Array[Byte](N)
Random.nextBytes(test)
val buffer = ByteBuffer.allocate(N)
buffer.limit(N)
buffer.put(test)
bm.putBytes(blockId, buffer, StorageLevel.MEMORY_ONLY_SER)
Iterator(1)
}.count()
data.mapPartitionsWithIndex { (pid, iter) =>
val before = System.nanoTime()
val bm = SparkEnv.get.blockManager
(1 to 8).map(s => {
Future {
val result = bm.getRemoteBytes(TaskResultBlockId(10*i + s))
}
}).map(Await.result(_, Duration.Inf))
accum.add((System.nanoTime() - before) / 1e9)
Iterator(1)
}.count()
println("get remote bytes take: " + accum.value/8)
i += 1
}
}
In spark1.6.2, average of "getting remote bytes" time is: 0.16s while
in spark 1.5.1 average of "getting remote bytes" time is: 0.07s
However if fetch block in single thread, the gap is much smaller.
spark1.6.2 get remote bytes: 0.191421s
spark1.5.1 get remote bytes: 0.181312s
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