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From 李森栋 <lisend...@163.com>
Subject Re:Re: job hangs when using pipe() with reduceByKey()
Date Sat, 31 Oct 2015 17:11:55 GMT
spark 1.4.1
hadoop 2.6.0
centos 6.6






At 2015-10-31 23:14:46, "Ted Yu" <yuzhihong@gmail.com> wrote:

Which Spark release are you using ?


Which OS ?


Thanks


On Sat, Oct 31, 2015 at 5:18 AM, hotdog <lisendong@163.com> wrote:
I meet a situation:
When I use
val a = rdd.pipe("./my_cpp_program").persist()
a.count()  // just use it to persist a
val b = a.map(s => (s, 1)).reduceByKey().count()
it 's so fast

but when I use
val b = rdd.pipe("./my_cpp_program").map(s => (s, 1)).reduceByKey().count()
it is so slow....
and there are many such log in my executors:
15/10/31 19:53:58 INFO collection.ExternalSorter: Thread 78 spilling
in-memory map of 633.1 MB to disk (8 times so far)
15/10/31 19:54:14 INFO collection.ExternalSorter: Thread 74 spilling
in-memory map of 633.1 MB to disk (8 times so far)
15/10/31 19:54:17 INFO collection.ExternalSorter: Thread 79 spilling
in-memory map of 633.1 MB to disk (8 times so far)
15/10/31 19:54:29 INFO collection.ExternalSorter: Thread 77 spilling
in-memory map of 633.1 MB to disk (8 times so far)
15/10/31 19:54:50 INFO collection.ExternalSorter: Thread 76 spilling
in-memory map of 633.1 MB to disk (9 times so far)



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