Which Spark release are you using ? Which OS ?
Thanks On Sat, Oct 31, 2015 at 5:18 AM, hotdog <lisend...@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) > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/job-hangs-when-using-pipe-with-reduceByKey-tp25242.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >