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From Azuryy Yu <azury...@gmail.com>
Subject Re: Tajo query scheduler and performance question
Date Thu, 05 Mar 2015 08:36:52 GMT
Thanks Jihoon.

It seems performance is good using your SQL.

1) dfs-dir-aware is set to true
default> select count(*) from (select dvc_id from tds_did_user_targ_day
where dt='20150228' and platform='pc' group by dvc_id) t;
Progress: 0%, response time: 0.681 sec
Progress: 0%, response time: 0.683 sec
Progress: 0%, response time: 1.085 sec
Progress: 0%, response time: 1.886 sec
Progress: 25%, response time: 2.887 sec
Progress: 27%, response time: 3.889 sec
Progress: 32%, response time: 4.89 sec
Progress: 33%, response time: 5.892 sec
Progress: 33%, response time: 6.894 sec
Progress: 50%, response time: 7.895 sec
Progress: 50%, response time: 8.896 sec
Progress: 58%, response time: 9.897 sec
Progress: 58%, response time: 11.379 sec
Progress: 56%, response time: 12.38 sec
Progress: 65%, response time: 13.382 sec
Progress: 100%, response time: 14.135 sec
?count
-------------------------------
35620159
(1 rows, 14.135 sec, 9 B selected)

2) dfs-dir-aware is comment out
default> select count(*) from (select dvc_id from tds_did_user_targ_day
where dt='20150228' and platform='pc' group by dvc_id) t;
Progress: 0%, response time: 0.94 sec
Progress: 0%, response time: 0.941 sec
Progress: 0%, response time: 1.342 sec
Progress: 0%, response time: 2.144 sec
Progress: 0%, response time: 3.145 sec
Progress: 5%, response time: 4.147 sec
Progress: 9%, response time: 5.148 sec
Progress: 12%, response time: 6.15 sec
Progress: 16%, response time: 7.152 sec
Progress: 21%, response time: 8.153 sec
Progress: 23%, response time: 9.154 sec
Progress: 29%, response time: 10.156 sec
Progress: 30%, response time: 11.157 sec
Progress: 32%, response time: 12.158 sec
Progress: 32%, response time: 13.159 sec
Progress: 33%, response time: 14.161 sec
Progress: 33%, response time: 15.164 sec
Progress: 40%, response time: 16.165 sec
Progress: 48%, response time: 17.166 sec
Progress: 54%, response time: 18.167 sec
Progress: 56%, response time: 19.169 sec
Progress: 60%, response time: 20.17 sec
Progress: 61%, response time: 21.171 sec
Progress: 58%, response time: 22.173 sec
Progress: 60%, response time: 23.174 sec
Progress: 66%, response time: 24.175 sec
Progress: 100%, response time: 24.383 sec
?count
-------------------------------
35620159
(1 rows, 24.383 sec, 9 B selected)

So, yes dfs-dir-aware is helpfule. and your SQL using the different logical
plan.



On Thu, Mar 5, 2015 at 4:24 PM, Jihoon Son <ghoonson@gmail.com> wrote:

> Thanks for sharing.
>
> It seems that the distinct query has some problems. Basically, distinct
> aggregation without the group-by clause should be performed with a
> multiple-level aggregation algorithm. But, it does not seem to work in that
> way.
>
> Would you test with the following equivalent query again?
>
> select count(*) from (select dvc_id from tds_did_user_targ_day where
> dt='20150228'
> and platform='pc' group by dvc_id) t;
>
> In addition, the performance will be improved if you enable the '
> tajo.worker.resource.dfs-dir-aware' option which is currently commented
> out.
>
> Best regards,
> Jihoon
>
> On Thu, Mar 5, 2015 at 4:51 PM Azuryy Yu <azuryyyu@gmail.com> wrote:
>
> > Thanks Jihoon.
> >
> > My test dataset has 20 files under one partition with RCFile format. (96
> > columns),  the first column is deviceID.
> > I only test this one partition, if I use all partitions, count(distinct)
> is
> > even slow.
> >
> > I've set HDFS replication to 9.(I have 9 datanodes) , HDFS block size:
> > 64MB,  set dfs.datanode.hdfs-blocks-metadata.enabled=true
> >
> > the following is some test results:
> >
> > 1.
> > default> select count(*) from tds_did_user_targ_day where dt='20150228'
> and
> > platform='pc';
> > Progress: 0%, response time: 0.306 sec
> > Progress: 0%, response time: 0.307 sec
> > Progress: 3%, response time: 0.711 sec
> > Progress: 21%, response time: 1.513 sec
> > Progress: 43%, response time: 2.514 sec
> > Progress: 100%, response time: 3.139 sec
> > ?count
> > -------------------------------
> > 35743711
> > (1 rows, 3.139 sec, 9 B selected)
> >
> > 2. default> select sum(cast(day_movie_vv as bigint)),
> sum(cast(day_movie_cv
> > as bigint)), sum(cast(day_movie_pt as bigint)) from tds_did_user_targ_day
> > where dt= '20150228' and platform='pc';
> > Progress: 0%, response time: 0.299 sec
> > Progress: 0%, response time: 0.299 sec
> > Progress: 0%, response time: 0.7 sec
> > Progress: 6%, response time: 1.502 sec
> > Progress: 21%, response time: 2.503 sec
> > Progress: 32%, response time: 3.504 sec
> > Progress: 44%, response time: 4.505 sec
> > Progress: 50%, response time: 5.506 sec
> > Progress: 100%, response time: 5.568 sec
> > ?sum_3,  ?sum_4,  ?sum_5
> > -------------------------------
> > 7302934,  6453007,  6504000842
> > (1 rows, 5.568 sec, 27 B selected)
> >
> >
> > 3)
> > default> select count(distinct dvc_id) from tds_did_user_targ_day where
> dt=
> > '20150228' and platform='pc';
> > Progress: 0%, response time: 0.3 sec
> > Progress: 0%, response time: 0.301 sec
> > Progress: 0%, response time: 0.702 sec
> > Progress: 2%, response time: 1.503 sec
> > Progress: 3%, response time: 2.504 sec
> > Progress: 4%, response time: 3.506 sec
> > Progress: 10%, response time: 4.507 sec
> > Progress: 14%, response time: 5.508 sec
> > Progress: 17%, response time: 6.509 sec
> > Progress: 21%, response time: 7.51 sec
> > Progress: 25%, response time: 8.511 sec
> > Progress: 27%, response time: 9.512 sec
> > Progress: 28%, response time: 10.513 sec
> > Progress: 33%, response time: 11.514 sec
> > Progress: 33%, response time: 12.516 sec
> > Progress: 33%, response time: 13.52 sec
> > Progress: 50%, response time: 14.523 sec
> > Progress: 50%, response time: 15.525 sec
> > Progress: 50%, response time: 16.527 sec
> > Progress: 50%, response time: 17.529 sec
> > Progress: 50%, response time: 18.53 sec
> > Progress: 50%, response time: 19.531 sec
> > Progress: 50%, response time: 20.533 sec
> > Progress: 51%, response time: 21.534 sec
> > Progress: 51%, response time: 22.535 sec
> > Progress: 51%, response time: 23.536 sec
> > Progress: 52%, response time: 24.538 sec
> > Progress: 52%, response time: 25.539 sec
> > Progress: 54%, response time: 26.54 sec
> > Progress: 54%, response time: 27.542 sec
> > Progress: 54%, response time: 28.543 sec
> > Progress: 54%, response time: 29.545 sec
> > Progress: 55%, response time: 30.546 sec
> > Progress: 56%, response time: 31.547 sec
> > Progress: 57%, response time: 32.549 sec
> > Progress: 60%, response time: 33.55 sec
> > Progress: 60%, response time: 34.551 sec
> > Progress: 63%, response time: 35.552 sec
> > Progress: 64%, response time: 36.554 sec
> > Progress: 65%, response time: 37.555 sec
> > Progress: 66%, response time: 38.556 sec
> > Progress: 66%, response time: 39.559 sec
> > Progress: 66%, response time: 40.563 sec
> > Progress: 66%, response time: 41.567 sec
> > Progress: 66%, response time: 42.571 sec
> > Progress: 66%, response time: 43.575 sec
> > Progress: 66%, response time: 44.579 sec
> > Progress: 66%, response time: 45.584 sec
> > Progress: 66%, response time: 46.588 sec
> > Progress: 66%, response time: 47.592 sec
> > Progress: 66%, response time: 48.596 sec
> > Progress: 66%, response time: 49.6 sec
> > Progress: 66%, response time: 50.601 sec
> > Progress: 83%, response time: 51.602 sec
> > Progress: 83%, response time: 52.603 sec
> > Progress: 83%, response time: 53.604 sec
> > Progress: 83%, response time: 54.605 sec
> > Progress: 84%, response time: 55.606 sec
> > Progress: 84%, response time: 56.607 sec
> > Progress: 84%, response time: 57.608 sec
> > Progress: 84%, response time: 58.609 sec
> > Progress: 84%, response time: 59.61 sec
> > Progress: 85%, response time: 60.612 sec
> > Progress: 85%, response time: 61.613 sec
> > Progress: 85%, response time: 62.614 sec
> > Progress: 86%, response time: 63.615 sec
> > Progress: 86%, response time: 64.616 sec
> > Progress: 86%, response time: 65.617 sec
> > Progress: 88%, response time: 66.618 sec
> > Progress: 88%, response time: 67.619 sec
> > Progress: 88%, response time: 68.62 sec
> > Progress: 89%, response time: 69.621 sec
> > Progress: 89%, response time: 70.622 sec
> > Progress: 89%, response time: 71.623 sec
> > Progress: 89%, response time: 72.624 sec
> > Progress: 90%, response time: 73.625 sec
> > Progress: 90%, response time: 74.627 sec
> > Progress: 90%, response time: 75.628 sec
> > Progress: 90%, response time: 76.629 sec
> > Progress: 90%, response time: 77.63 sec
> > Progress: 90%, response time: 78.632 sec
> > Progress: 90%, response time: 79.633 sec
> > Progress: 90%, response time: 80.634 sec
> > Progress: 90%, response time: 81.636 sec
> > Progress: 86%, response time: 82.637 sec
> > Progress: 86%, response time: 83.638 sec
> > Progress: 86%, response time: 84.64 sec
> > Progress: 86%, response time: 85.641 sec
> > Progress: 86%, response time: 86.642 sec
> > Progress: 86%, response time: 87.643 sec
> > Progress: 88%, response time: 88.645 sec
> > Progress: 88%, response time: 89.646 sec
> > Progress: 88%, response time: 90.647 sec
> > Progress: 92%, response time: 91.648 sec
> > Progress: 92%, response time: 92.649 sec
> > Progress: 92%, response time: 93.65 sec
> > Progress: 92%, response time: 94.651 sec
> > Progress: 93%, response time: 95.652 sec
> > Progress: 93%, response time: 96.653 sec
> > Progress: 94%, response time: 97.654 sec
> > Progress: 94%, response time: 98.655 sec
> > Progress: 95%, response time: 99.656 sec
> > Progress: 95%, response time: 100.657 sec
> > Progress: 95%, response time: 101.658 sec
> > Progress: 95%, response time: 102.659 sec
> > Progress: 96%, response time: 103.66 sec
> > Progress: 96%, response time: 104.661 sec
> > Progress: 97%, response time: 105.662 sec
> > Progress: 97%, response time: 106.663 sec
> > Progress: 99%, response time: 107.665 sec
> > Progress: 99%, response time: 108.666 sec
> > Progress: 100%, response time: 109.074 sec
> > ?count
> > -------------------------------
> > 35620158
> > (1 rows, 109.074 sec, 9 B selected)
> >
> > For the last query, Logic plan:
> > Logical Plan
> >
> > -----------------------------
> > Query Block Graph
> > -----------------------------
> > |-#ROOT
> > -----------------------------
> > Optimization Log:
> > [LogicalPlan]
> >         > ProjectionNode is eliminated.
> >         > PartitionTableRewriter chooses 1 of partitions
> > -----------------------------
> >
> > GROUP_BY(3)()
> >   => exprs: (count( distinct default.tds_did_user_targ_day.dvc_id
> (TEXT)))
> >   => target list: ?count (INT8)
> >   => out schema:{(1) ?count (INT8)}
> >   => in schema:{(1) default.tds_did_user_targ_day.dvc_id (TEXT)}
> >    PARTITIONS_SCAN(5) on default.tds_did_user_targ_day
> >      => target list: default.tds_did_user_targ_day.dvc_id (TEXT)
> >      => num of filtered paths: 1
> >      => out schema: {(1) default.tds_did_user_targ_day.dvc_id (TEXT)}
> >      => in schema: {(91) default.tds_did_user_targ_day.dvc_id
> > (TEXT),default.tds_did_user_targ_day.user_id
> > (TEXT),default.tds_did_user_targ_day.p1
> > (TEXT),default.tds_did_user_targ_day.p2
> > (TEXT),default.tds_did_user_targ_day.p3
> > (TEXT),default.tds_did_user_targ_day.prod_code
> > (TEXT),default.tds_did_user_targ_day.login_ip
> > (TEXT),default.tds_did_user_targ_day.cntry_name
> > (TEXT),default.tds_did_user_targ_day.area_name
> > (TEXT),default.tds_did_user_targ_day.prov_name
> > (TEXT),default.tds_did_user_targ_day.city_name
> > (TEXT),default.tds_did_user_targ_day.chnl_type
> > (TEXT),default.tds_did_user_targ_day.chnl_type_name
> > (TEXT),default.tds_did_user_targ_day.chnl_code
> > (TEXT),default.tds_did_user_targ_day.chnl_name
> > (TEXT),default.tds_did_user_targ_day.login_ref
> > (TEXT),default.tds_did_user_targ_day.net_type
> > (TEXT),default.tds_did_user_targ_day.oper_sys
> > (TEXT),default.tds_did_user_targ_day.oper_sys_ver
> > (TEXT),default.tds_did_user_targ_day.dvc_brand
> > (TEXT),default.tds_did_user_targ_day.dvc_model
> > (TEXT),default.tds_did_user_targ_day.dvc_type
> > (TEXT),default.tds_did_user_targ_day.dev_dpi
> > (TEXT),default.tds_did_user_targ_day.brows_name
> > (TEXT),default.tds_did_user_targ_day.login_ts
> > (TEXT),default.tds_did_user_targ_day.first_login_date
> > (TEXT),default.tds_did_user_targ_day.first_login_ver
> > (TEXT),default.tds_did_user_targ_day.last_login_date
> > (TEXT),default.tds_did_user_targ_day.last_app_ver
> > (TEXT),default.tds_did_user_targ_day.evil_ip
> > (TEXT),default.tds_did_user_targ_day.day_pv
> > (TEXT),default.tds_did_user_targ_day.day_input_pv
> > (TEXT),default.tds_did_user_targ_day.day_ins_pv
> > (TEXT),default.tds_did_user_targ_day.day_qry_pv
> > (TEXT),default.tds_did_user_targ_day.day_outs_pv
> > (TEXT),default.tds_did_user_targ_day.day_coop_pv
> > (TEXT),default.tds_did_user_targ_day.day_vv
> > (TEXT),default.tds_did_user_targ_day.day_cv
> > (TEXT),default.tds_did_user_targ_day.day_pt
> > (TEXT),default.tds_did_user_targ_day.day_vod_vv
> > (TEXT),default.tds_did_user_targ_day.day_vod_cv
> > (TEXT),default.tds_did_user_targ_day.day_vod_pt
> > (TEXT),default.tds_did_user_targ_day.day_live_vv
> > (TEXT),default.tds_did_user_targ_day.day_live_cv
> > (TEXT),default.tds_did_user_targ_day.day_live_pt
> > (TEXT),default.tds_did_user_targ_day.day_ca_vv
> > (TEXT),default.tds_did_user_targ_day.day_ca_cv
> > (TEXT),default.tds_did_user_targ_day.day_ca_pt
> > (TEXT),default.tds_did_user_targ_day.day_try_vv
> > (TEXT),default.tds_did_user_targ_day.day_try_cv
> > (TEXT),default.tds_did_user_targ_day.day_try_pt
> > (TEXT),default.tds_did_user_targ_day.day_pay_vv
> > (TEXT),default.tds_did_user_targ_day.day_pay_cv
> > (TEXT),default.tds_did_user_targ_day.day_pay_pt
> > (TEXT),default.tds_did_user_targ_day.day_off_vv
> > (TEXT),default.tds_did_user_targ_day.day_off_cv
> > (TEXT),default.tds_did_user_targ_day.day_off_pt
> > (TEXT),default.tds_did_user_targ_day.block_ts
> > (TEXT),default.tds_did_user_targ_day.day_drag_ts
> > (TEXT),default.tds_did_user_targ_day.day_drag_ahd_ts
> > (TEXT),default.tds_did_user_targ_day.day_drag_bwd_ts
> > (TEXT),default.tds_did_user_targ_day.day_click_ts
> > (TEXT),default.tds_did_user_targ_day.day_instl_ts
> > (TEXT),default.tds_did_user_targ_day.day_stup_ts
> > (TEXT),default.tds_did_user_targ_day.day_movie_vv
> > (TEXT),default.tds_did_user_targ_day.day_movie_cv
> > (TEXT),default.tds_did_user_targ_day.day_movie_pt
> > (TEXT),default.tds_did_user_targ_day.day_tvp_vv
> > (TEXT),default.tds_did_user_targ_day.day_tvp_cv
> > (TEXT),default.tds_did_user_targ_day.day_tvp_pt
> > (TEXT),default.tds_did_user_targ_day.day_cartn_vv
> > (TEXT),default.tds_did_user_targ_day.day_cartn_cv
> > (TEXT),default.tds_did_user_targ_day.day_cartn_pt
> > (TEXT),default.tds_did_user_targ_day.day_var_vv
> > (TEXT),default.tds_did_user_targ_day.day_var_cv
> > (TEXT),default.tds_did_user_targ_day.day_var_pt
> > (TEXT),default.tds_did_user_targ_day.day_amuse_vv
> > (TEXT),default.tds_did_user_targ_day.day_amuse_cv
> > (TEXT),default.tds_did_user_targ_day.day_amuse_pt
> > (TEXT),default.tds_did_user_targ_day.day_sport_vv
> > (TEXT),default.tds_did_user_targ_day.day_sport_cv
> > (TEXT),default.tds_did_user_targ_day.day_sport_pt
> > (TEXT),default.tds_did_user_targ_day.day_music_vv
> > (TEXT),default.tds_did_user_targ_day.day_music_cv
> > (TEXT),default.tds_did_user_targ_day.day_music_pt
> > (TEXT),default.tds_did_user_targ_day.day_fin_vv
> > (TEXT),default.tds_did_user_targ_day.day_fin_cv
> > (TEXT),default.tds_did_user_targ_day.day_fin_pt
> > (TEXT),default.tds_did_user_targ_day.day_hot_vv
> > (TEXT),default.tds_did_user_targ_day.day_hot_cv
> > (TEXT),default.tds_did_user_targ_day.day_hot_pt (TEXT)}
> >      => 0: hdfs://realtime-cluster/data/basetable/tds_did_user_targ_
> > day/dt=20150228/platform=pc
> >
> >
> >
> >
> >
> >
> >
> >
> > On Thu, Mar 5, 2015 at 3:17 PM, Jihoon Son <ghoonson@gmail.com> wrote:
> >
> > > Hi Azuryy,
> > > truly sorry for late response.
> > > I left some comments below.
> > >
> > > Sincerely,
> > > Jihoon
> > >
> > > On Wed, Mar 4, 2015 at 7:15 PM Azuryy Yu <azuryyyu@gmail.com> wrote:
> > >
> > > > Hi,
> > > >
> > > > I read theTajo-0.9.0  source code, I found Tajo using a simple FIFO
> > > > scheduler,
> > > >
> > > > I accept this in the current stage. but when Tajo peek a query from
> the
> > > > scheduler queue, then allocate workers for this query,
> > > >
> > > > Allocator only consider availale resource on a random worker list,
> > then
> > > > specify a set of workers.
> > > >
> > > > 1)
> > > > so My question is why we don't consider HDFS locatbility? otherwise
> > > network
> > > > will be the bottleneck.
> > > >
> > > > I understand Tajo don't use YARN as a scheduler currently. and write
> a
> > > > temporary simple FIFO scheduler. and I am also looked at
> > > > https://issues.apache.org/jira/browse/TAJO-540 , I hope new Tajo
> > > scheduler
> > > > similar to Sparrow.
> > > >
> > > It seems that there are some misunderstandings on our resource
> > scheduling.
> > > The
> > > FIFO scheduler has a role of the query scheduler. That is, given a list
> > of
> > > submitted queries, it reserves resources required to execute queries
> > > consecutively. The Sparrow-like scheduler can be used for the
> concurrent
> > > execution of multiple queries.
> > >
> > > Once a query is started, the *task scheduler* is responsible for
> > allocating
> > > tasks to workers. As you said, tasks are allocated to workers if they
> > have
> > > enough resources. However when allocating tasks, our task scheduler
> > > considers the physical disk location where the data is stored on as
> well
> > as
> > > the location of the node containing data. For example, with your
> cluster,
> > > each worker can be assigned 12 tasks each of which processes data
> stored
> > on
> > > different 12 disks. Since a worker is generally equipped multiple
> disks,
> > > this approach can utilize the disk bandwidth efficiently.
> > >
> > > You can see the locality information in the Tajo's query master log.
> Here
> > > is an example.
> > > ...
> > > 2015-03-05 15:14:12,662 INFO
> > > org.apache.tajo.querymaster.DefaultTaskScheduler: Assigned
> > > Local/Rack/Total: (9264/1555/10819), Locality: 85.63%, Rack host:
> > > xxx.xxx.xxx.xxx
> > > ...
> > >
> > >
> > > > 2) performance related.
> > > > I setup 10 nodes clusters, (1 master, 9 workers)
> > > >
> > > > 64GB mem, 24CPU, 12*4TB HDD,  1.6GB test data.(160 million records)
> > > >
> > > > It's works good for some agg sql tests except count(distinct)
> > > >
> > > > count(distinct) is very slow - ten minutes.
> > > >
> > > This result looks strange and difficult to find what makes the query
> > > execution slow.
> > > Would you mind sharing some logs and additional information of input
> data
> > > (# of files, the distribution of data on HDFS)?
> > > In addition, it would be great if you share the evaluation results of
> > other
> > > queries which you think the response time is sufficiently short.
> > >
> > > >
> > > > who can give me a simple explanation of how Tajo works with
> > > > count(distinct), I can share my tajo-site here:
> > > >
> > > > <configuration>
> > > >   <property>
> > > >     <name>tajo.rootdir</name>
> > > >     <value>hdfs://realtime-cluster/tajo</value>
> > > >   </property>
> > > >
> > > >   <!-- master -->
> > > >   <property>
> > > >     <name>tajo.master.umbilical-rpc.address</name>
> > > >     <value>xx:26001</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.master.client-rpc.address</name>
> > > >     <value>xx:26002</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.master.info-http.address</name>
> > > >     <value>xx:26080</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.resource-tracker.rpc.address</name>
> > > >     <value>xx:26003</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.catalog.client-rpc.address</name>
> > > >     <value>xx:26005</value>
> > > >   </property>
> > > >   <!--  worker  -->
> > > >   <property>
> > > >     <name>tajo.worker.tmpdir.locations</name>
> > > >
> > > > <value>file:///data/hadoop/data1/tajo,file:///data/hadoop/
> > > > data2/tajo,file:///data/hadoop/data3/tajo,file:///
> > > > data/hadoop/data4/tajo,file:///data/hadoop/data5/tajo,file:/
> > > > //data/hadoop/data6/tajo,file:///data/hadoop/data7/tajo,
> > > >
> file:///data/hadoop/data8/tajo,file:///data/hadoop/data9/tajo,file:///
> > > > data/hadoop/data10/tajo,file:///data/hadoop/data11/tajo,file:/
> > > > //data/hadoop/data12/tajo</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.worker.tmpdir.cleanup-at-startup</name>
> > > >     <value>true</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.worker.history.expire-interval-minutes</name>
> > > >     <value>60</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.worker.resource.tajo.worker.resource.cpu-cores</name>
> > > >     <value>24</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.worker.resource.memory-mb</name>
> > > >     <value>60512</value> <!-- 3584 3 tasks + 1 qm task
 -->
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.task.memory-slot-mb.default</name>
> > > >     <value>3000</value> <!--  default 512 -->
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.task.disk-slot.default</name>
> > > >     <value>1.0f</value> <!--  default 0.5 -->
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.shuffle.fetcher.parallel-execution.max-num</name>
> > > >     <value>5</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.executor.external-sort.thread-num</name>
> > > >     <value>2</value>
> > > >   </property>
> > > >   <!-- client -->
> > > >   <property>
> > > >     <name>tajo.rpc.client.worker-thread-num</name>
> > > >     <value>4</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.cli.print.pause</name>
> > > >     <value>false</value>
> > > >   </property>
> > > > <!--
> > > >   <property>
> > > >     <name>tajo.worker.resource.dfs-dir-aware</name>
> > > >     <value>true</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.worker.resource.dedicated</name>
> > > >     <value>true</value>
> > > >   </property>
> > > >   <property>
> > > >     <name>tajo.worker.resource.dedicated-memory-ratio</name>
> > > >     <value>0.6</value>
> > > >   </property>
> > > > -->
> > > > </configuration>
> > > >
> > > >
> > > > tajo-env:
> > > >
> > > > export TAJO_WORKER_HEAPSIZE=60000
> > > >
> > >
> >
>

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