Thanks for your reply, i can definitely change the underlying compression format. but i am trying to understand the Locality Level, why executor ran on a different node, where the blocks are not present, when Locality Level is RACK_LOCAL
can you shed some light on this. Thanks, Yesh -Yeshwanth Can you Imagine what I would do if I could do all I can - Art of War On Mon, Nov 21, 2016 at 4:59 PM, Jörn Franke <jornfra...@gmail.com> wrote: > Use as a format orc, parquet or avro because they support any compression > type with parallel processing. Alternatively split your file in several > smaller ones. Another alternative would be bzip2 (but slower in general) or > Lzo (usually it is not included by default in many distributions). > > On 21 Nov 2016, at 23:17, yeshwanth kumar <yeshwant...@gmail.com> wrote: > > Hi, > > we are running Hive on Spark, we have an external table over snappy > compressed csv file of size 917.4 M > HDFS block size is set to 256 MB > > as per my Understanding, if i run a query over that external table , it > should launch 4 tasks. one for each block. > but i am seeing one executor and one task processing all the file. > > trying to understand the reason behind, > > i went one step further to understand the block locality > when i get the block locations for that file, i found > > [DatanodeInfoWithStorage[10.11.0.226:50010,DS-bf39d33d- > 48e1-4a8f-be48-b0953fdaad37,DISK], > DatanodeInfoWithStorage[10.11.0.227:50010,DS-a760c1c8- > ce0c-4eb8-8183-8d8ff5f24115,DISK], > DatanodeInfoWithStorage[10.11.0.228:50010,DS-0e5427e2- > b030-43f8-91c9-d8517e68414a,DISK]] > > DatanodeInfoWithStorage[10.11.0.226:50010,DS-f50ddf2f-b827- > 4845-b043-8b91ae4017c0,DISK], > DatanodeInfoWithStorage[10.11.0.228:50010,DS-e8c9785f-c352- > 489b-8209-4307f3296211,DISK], > DatanodeInfoWithStorage[10.11.0.225:50010,DS-6f6a3ffd-334b- > 45fd-ae0f-cc6eb268b0d2,DISK]] > > DatanodeInfoWithStorage[10.11.0.226:50010,DS-f8bea6a8-a433- > 4601-8070-f6c5da840e09,DISK], > DatanodeInfoWithStorage[10.11.0.227:50010,DS-8aa3f249-790e- > 494d-87ee-bcfff2182a96,DISK], > DatanodeInfoWithStorage[10.11.0.228:50010,DS-d06714f4-2fbb- > 48d3-b858-a023b5c44e9c,DISK] > > DatanodeInfoWithStorage[10.11.0.226:50010,DS-b3a00781-c6bd- > 498c-a487-5ce6aaa66f48,DISK], > DatanodeInfoWithStorage[10.11.0.228:50010,DS-fa5aa339-e266- > 4e20-a360-e7cdad5dacc3,DISK], > DatanodeInfoWithStorage[10.11.0.225:50010,DS-9d597d3f-cd4f- > 4c8f-8a13-7be37ce769c9,DISK]] > > and in the spark UI i see the Locality Level is RACK_LOCAL. for that task > > if it is RACK_LOCAL then it should run either in node 10.11.0.226 or > 10.11.0.228, because these 2 nodes has all the four blocks needed for > computation > but the executor is running in 10.11.0.225 > > my theory is not applying anywhere. > > please help me in understanding how spark/yarn calculates number of > executors/tasks. > > Thanks, > -Yeshwanth > >
