PS. my Parquet data was generated by Impala: "Insert into a parquet table [SHUFFLE] ... AS select .... from a text table"
On Mon, Mar 16, 2015 at 3:11 PM, Azuryy Yu <[email protected]> wrote: > Hi Jihoon, > > Here is an example: > My data: (Parquet file is 1GB limited) > hadoop fs -ls /data/basetable/par/dt=20150301/pf=pc > > -rw-r--r-- 9 hadoop tajo 1062932057 2015-03-12 15:08 > /data/basetable/par/dt=20150301/pf=pc/cc456c9d427c88a3-3ead7e35ecf0da8_448517166_data.0.parq > -rw-r--r-- 9 hadoop tajo 1063205684 2015-03-12 15:11 > /data/basetable/par/dt=20150301/pf=pc/cc456c9d427c88a3-3ead7e35ecf0da8_448517166_data.1.parq > -rw-r--r-- 9 hadoop tajo 1063236005 2015-03-12 15:14 > /data/basetable/par/dt=20150301/pf=pc/cc456c9d427c88a3-3ead7e35ecf0da8_448517166_data.2.parq > -rw-r--r-- 9 hadoop tajo 543786632 2015-03-12 15:16 > /data/basetable/par/dt=20150301/pf=pc/cc456c9d427c88a3-3ead7e35ecf0da8_448517166_data.3.parq > > hadoop fs -ls /data/basetable/snappy/dt=20150301/pf=pc > > -rw-r--r-- 9 tajo tajo 144059045 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00000 > -rw-r--r-- 9 tajo tajo 144178118 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00001 > -rw-r--r-- 9 tajo tajo 143642438 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00002 > -rw-r--r-- 9 tajo tajo 143553142 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00003 > -rw-r--r-- 9 tajo tajo 143849627 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00004 > -rw-r--r-- 9 tajo tajo 144648456 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00005 > -rw-r--r-- 9 tajo tajo 144647502 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00006 > -rw-r--r-- 9 tajo tajo 144551053 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00007 > -rw-r--r-- 9 tajo tajo 144017287 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00008 > -rw-r--r-- 9 tajo tajo 144205111 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00009 > -rw-r--r-- 9 tajo tajo 145066506 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00010 > -rw-r--r-- 9 tajo tajo 144740791 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00011 > -rw-r--r-- 9 tajo tajo 144198266 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00012 > -rw-r--r-- 9 tajo tajo 143575440 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00013 > -rw-r--r-- 9 tajo tajo 143922343 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00014 > -rw-r--r-- 9 tajo tajo 143930019 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00015 > -rw-r--r-- 9 tajo tajo 144253019 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00016 > -rw-r--r-- 9 tajo tajo 144175506 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00017 > -rw-r--r-- 9 tajo tajo 143072995 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00018 > -rw-r--r-- 9 tajo tajo 143818118 2015-03-16 11:48 > /data/basetable/snappy/dt=20150301/pf=pc/part-r-00019 > > Result: > > default> select sum (cast(movie_vv as bigint)), sum(cast(movie_cv as > bigint)),sum(cast(movie_pt as bigint)) from snappy where pf='pc'; > Progress: 19%, response time: 1.87 sec > Progress: 19%, response time: 1.873 sec > Progress: 19%, response time: 2.276 sec > Progress: 100%, response time: 2.372 sec > ?sum_3, ?sum_4, ?sum_5 > ------------------------------- > 6928463, 6183665, 6055494385 > (1 rows, 2.372 sec, 27 B selected) > default> select sum (cast(movie_vv as bigint)), sum(cast(movie_cv as > bigint)),sum(cast(movie_pt as bigint)) from par where pf='pc'; > Progress: 0%, response time: 0.751 sec > Progress: 0%, response time: 0.753 sec > Progress: 0%, response time: 1.155 sec > Progress: 0%, response time: 1.959 sec > Progress: 0%, response time: 2.962 sec > Progress: 0%, response time: 3.965 sec > Progress: 0%, response time: 4.968 sec > Progress: 0%, response time: 5.97 sec > Progress: 12%, response time: 6.974 sec > Progress: 12%, response time: 7.977 sec > Progress: 12%, response time: 8.979 sec > Progress: 12%, response time: 9.982 sec > Progress: 25%, response time: 10.985 sec > Progress: 100%, response time: 11.14 sec > ?sum_3, ?sum_4, ?sum_5 > ------------------------------- > 6928463, 6183665, 6055494385 > (1 rows, 11.14 sec, 27 B selected) > > On Mon, Mar 16, 2015 at 2:58 PM, Jihoon Son <[email protected]> wrote: > >> Azuryy, thanks for your feedbacks. >> They are very interesting results. >> Would you mind telling me how Tajo with Parquet is slower than Tajo with >> RCFile? >> >> Thanks, >> Jihoon >> >> On Mon, Mar 16, 2015 at 3:39 PM Hyunsik Choi <[email protected]> wrote: >> >> > Hi Azuryy, >> > >> > Thank for sharing the test results. They are very inspiring to us. >> > Also, I'll make some jira about the problems that you found. >> > >> > Best regards, >> > Hyunsik >> > >> > On Sun, Mar 15, 2015 at 10:58 PM, Azuryy Yu <[email protected]> wrote: >> > > Another fix: >> > > My test result is unfair during compare Imapla-2.1.2 and Tajo-0.10.0, >> > > because I used Parquet with Impala and RCFILE snappy with Tajo. I >> should >> > > use the same file format to compare. >> > > >> > > because I've got a clear conclusion that Imapala works better on >> Parquet >> > > than Tajo, so I use RCFILE as the test data. >> > > >> > > *Tajo*: >> > > default> select sum (cast(movie_vv as bigint)), sum(cast(movie_cv as >> > > bigint)),sum(cast(movie_pt as bigint)) from snappy; >> > > Progress: 0%, response time: 1.598 sec >> > > Progress: 0%, response time: 1.6 sec >> > > Progress: 0%, response time: 2.003 sec >> > > Progress: 0%, response time: 2.806 sec >> > > Progress: 37%, response time: 3.808 sec >> > > Progress: 100%, response time: 4.792 sec >> > > ?sum_3, ?sum_4, ?sum_5 >> > > ------------------------------- >> > > 22557920, 19648838, 2005366694576 >> > > (1 rows, 4.792 sec, 32 B selected) >> > > >> > > *Impala*: >> > > > select sum (cast(movie_vv as bigint)), sum(cast(movie_cv as >> > > bigint)),sum(cast(movie_pt as bigint)) from snappy; >> > > +-------------------------------+--------------------------- >> > ----+-------------------------------+ >> > > | sum(cast(movie_vv as bigint)) | sum(cast(movie_cv as bigint)) | >> > > sum(cast(movie_pt as bigint)) | >> > > +-------------------------------+--------------------------- >> > ----+-------------------------------+ >> > > | 22557920 | 19648838 | >> > > 2005366694576 | >> > > +-------------------------------+--------------------------- >> > ----+-------------------------------+ >> > > Fetched 1 row(s) in 11.12s >> > > >> > > >> > > >> > > On Mon, Mar 16, 2015 at 1:49 PM, Azuryy Yu <[email protected]> >> wrote: >> > > >> > >> There is a typo in my Email. I corrected here: >> > >> >> > >> for example: >> > >> >> > >> <property> >> > >> <name>tajo.master.umbilical-rpc.address</name> >> > >> <value>1-1-1-1:26001</value> >> > >> </property> >> > >> >> > >> which does work under tajo-0.9.0, but it complain "1-1-1-1:2601" is >> not >> > a >> > >> valid network address under tajo-0.10.0. >> > >> >> > >> I have to change to: >> > >> <property> >> > >> <name>tajo.master.umbilical-rpc.address</name> >> > >> <value>1.1.1.1:26001</value> >> > >> </property> >> > >> >> > >> >> > >> On Mon, Mar 16, 2015 at 1:44 PM, Azuryy Yu <[email protected]> >> wrote: >> > >> >> > >>> Hi, >> > >>> I compiled tajo-0.10 source based on hadoop-2.6.0, then post some >> > >>> feedback here. >> > >>> >> > >>> My cluster: >> > >>> 1 tajo-master, 9 tajo-worker >> > >>> 24 CPU(logic), 64GB mem, 4TB*12 HDD >> > >>> >> > >>> Feedback: >> > >>> 1) tajo task progress estimate is normal on partitioned table, >> which is >> > >>> incorrect sometimes in tajo-0.9.0 >> > >>> 2) Tajo configuration doesn't support hostname in tajo-site.xml. >> > >>> for example: >> > >>> >> > >>> <property> >> > >>> <name>tajo.master.umbilical-rpc.address</name> >> > >>> <value>1-1-1-1:26001</value> >> > >>> </property> >> > >>> >> > >>> which does work under tajo-0.9.0, but it complain "1-1-1-1:2601" is >> > not a >> > >>> valid network address. >> > >>> >> > >>> I have to change to: >> > >>> <property> >> > >>> <name>tajo.master.umbilical-rpc.address</name> >> > >>> <value>1.1.1.1:26001</value> >> > >>> </property> >> > >>> >> > >>> but we don't use IP in our cluster, only hostname. so I did a >> little in >> > >>> the code: >> > >>> org.apache.tajo.validation.NetworkAddressValidator.java: >> > >>> hostnamePattern = Pattern.compile("\\d*-\\d*-\\d*-\\d"); >> > >>> then It works. >> > >>> >> > >>> 3) I did some test on the parquet, RCFILE(snappy compressed), >> > >>> RCFILE(GZIP compressed) >> > >>> >> > >>> they are the same data, only different from file format. >> > >>> the table has six partitions, 20 RCFILES, each parquet file is 1GB. >> > >>> >> > >>> then rcfile with snappy's performance is similiar to rcfile with >> gzip. >> > >>> but they are all two~three times better than parquet. >> > >>> >> > >>> 4) I compared tajo-0.10 and Impala-2.1.2, >> > >>> Impala can provide very good support for parquet. more better than >> > Tajo. >> > >>> >> > >>> but impala is more *slow *with other format than Tajo. >> > >>> such as(I don't use WHERE because I want query all six partitions >> > >>> together): >> > >>> >> > >>> *Impala*: >> > >>> > select sum (cast(movie_vv as bigint)), sum(cast(movie_cv as >> > >>> bigint)),sum(cast(movie_pt as bigint)) from par; >> > >>> >> > >>> +-------------------------------+--------------------------- >> > ----+-------------------------------+ >> > >>> | sum(cast(movie_vv as bigint)) | sum(cast(movie_cv as bigint)) | >> > >>> sum(cast(movie_pt as bigint)) | >> > >>> >> > >>> +-------------------------------+--------------------------- >> > ----+-------------------------------+ >> > >>> | 22557920 | 19648838 | >> > >>> 2005366694576 | >> > >>> >> > >>> +-------------------------------+--------------------------- >> > ----+-------------------------------+ >> > >>> Fetched 1 row(s) in 6.02s >> > >>> >> > >>> *Tajo:* >> > >>> >> > >>> *default*> select sum (cast(movie_vv as bigint)), sum(cast(movie_cv >> as >> > >>> bigint)),sum(cast(movie_pt as bigint)) from snappy; >> > >>> Progress: 0%, response time: 1.598 sec >> > >>> Progress: 0%, response time: 1.6 sec >> > >>> Progress: 0%, response time: 2.003 sec >> > >>> Progress: 0%, response time: 2.806 sec >> > >>> Progress: 37%, response time: 3.808 sec >> > >>> Progress: 100%, response time: 4.792 sec >> > >>> ?sum_3, ?sum_4, ?sum_5 >> > >>> ------------------------------- >> > >>> 22557920, 19648838, 2005366694576 >> > >>> (1 rows, 4.792 sec, 32 B selected) >> > >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > >> >> > >> > >
