That is a good point. The ORC table property is as follows
TBLPROPERTIES ( "orc.compress"="SNAPPY", "orc.stripe.size"="268435456", "orc.row.index.stride"="10000") which puts each stripe at 256MB Just to clarify this is spark running on Hive tables. I don't think the use of TEZ, MR or Spark as execution engines is going to make any difference? This is the same query with Hive on MR select a.prod_id from sales2 a, sales_staging b where a.prod_id = b.prod_id order by a.prod_id; 2016-06-28 23:23:51,203 Stage-1 map = 0%, reduce = 0% 2016-06-28 23:23:59,480 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 7.32 sec 2016-06-28 23:24:08,771 Stage-1 map = 55%, reduce = 0%, Cumulative CPU 18.21 sec 2016-06-28 23:24:11,860 Stage-1 map = 58%, reduce = 0%, Cumulative CPU 22.34 sec 2016-06-28 23:24:18,021 Stage-1 map = 62%, reduce = 0%, Cumulative CPU 30.33 sec 2016-06-28 23:24:21,101 Stage-1 map = 64%, reduce = 0%, Cumulative CPU 33.45 sec 2016-06-28 23:24:24,181 Stage-1 map = 66%, reduce = 0%, Cumulative CPU 37.5 sec 2016-06-28 23:24:27,270 Stage-1 map = 69%, reduce = 0%, Cumulative CPU 42.0 sec 2016-06-28 23:24:30,349 Stage-1 map = 70%, reduce = 0%, Cumulative CPU 45.62 sec 2016-06-28 23:24:33,441 Stage-1 map = 73%, reduce = 0%, Cumulative CPU 49.69 sec 2016-06-28 23:24:36,521 Stage-1 map = 75%, reduce = 0%, Cumulative CPU 52.92 sec 2016-06-28 23:24:39,605 Stage-1 map = 77%, reduce = 0%, Cumulative CPU 56.78 sec 2016-06-28 23:24:42,686 Stage-1 map = 80%, reduce = 0%, Cumulative CPU 60.36 sec 2016-06-28 23:24:45,767 Stage-1 map = 81%, reduce = 0%, Cumulative CPU 63.68 sec 2016-06-28 23:24:48,842 Stage-1 map = 83%, reduce = 0%, Cumulative CPU 66.92 sec 2016-06-28 23:24:51,918 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 70.18 sec 2016-06-28 23:25:52,354 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 127.99 sec 2016-06-28 23:25:57,494 Stage-1 map = 100%, reduce = 67%, Cumulative CPU 134.64 sec 2016-06-28 23:26:57,847 Stage-1 map = 100%, reduce = 67%, Cumulative CPU 141.01 sec which basically sits at 67% all day Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* http://talebzadehmich.wordpress.com *Disclaimer:* Use it at your own risk. Any and all responsibility for any loss, damage or destruction of data or any other property which may arise from relying on this email's technical content is explicitly disclaimed. The author will in no case be liable for any monetary damages arising from such loss, damage or destruction. On 28 June 2016 at 23:07, Jörn Franke <jornfra...@gmail.com> wrote: > > > Bzip2 is splittable for text files. > > Btw in Orc the question of splittable does not matter because each stripe > is compressed individually. > > Have you tried tez? As far as I recall (at least it was in the first > version of Hive) mr uses for order by a single reducer which is a > bottleneck. > > Do you see some errors in the log file? > > On 28 Jun 2016, at 23:53, Mich Talebzadeh <mich.talebza...@gmail.com> > wrote: > > Hi, > > > I have a simple join between table sales2 a compressed (snappy) ORC with > 22 million rows and another simple table sales_staging under a million rows > stored as a text file with no compression. > > The join is very simple > > val s2 = HiveContext.table("sales2").select("PROD_ID") > val s = HiveContext.table("sales_staging").select("PROD_ID") > > val rs = > s2.join(s,"prod_id").orderBy("prod_id").sort(desc("prod_id")).take(5).foreach(println) > > > Now what is happening is it is sitting on SortMergeJoin operation > on ZippedPartitionRDD as shown in the DAG diagram below > > > <image.png> > > > And at this rate only 10% is done and will take for ever to finish :( > > Stage 3:==> (10 + 2) / > 200] > > Ok I understand that zipped files cannot be broken into blocks and > operations on them cannot be parallelized. > > Having said that what are the alternatives? Never use compression and live > with it. I emphasise that any operation on the compressed table itself is > pretty fast as it is a simple table scan. However, a join between two > tables on a column as above suggests seems to be problematic? > > Thanks > > P.S. the same is happening using Hive with MR > > select a.prod_id from sales2 a inner join sales_staging b on a.prod_id = > b.prod_id order by a.prod_id; > > Dr Mich Talebzadeh > > > > LinkedIn * > https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw > <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* > > > > http://talebzadehmich.wordpress.com > > > *Disclaimer:* Use it at your own risk. Any and all responsibility for any > loss, damage or destruction of data or any other property which may arise > from relying on this email's technical content is explicitly disclaimed. > The author will in no case be liable for any monetary damages arising from > such loss, damage or destruction. > > > >
