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From Hyunsik Choi <hyun...@apache.org>
Subject Re: Some Tajo-0.9.0 questions
Date Thu, 22 Jan 2015 14:47:30 GMT
Hi Azuryy,

I just know more the best practices. Since the resource model of Tajo
is being evolved rapidly, the current model is not completed and is
not intuitive in my opinion. So, you may be hard to set the best
resources configs to Tajo.

Even though the resource model includes the number of CPU cores,
memory size, and disk resources, its essential thing is to determine
the number of concurrent tasks in each machine.

The proper number of concurrent tasks can be derived from hardware
resource capacity. The followings come from my experiences:

 * (Disk) Performance has been the best when each SATA disk takes 2
concurrent tasks at the same time.
 * (CPU) Performance has been the best in most cases when the
concurrent tasks = the number of cores
 * (Memory) Each task consumes 2 ~ 4 GB. Memory consumption for each
task varies in workloads. More than 2 GB has been showed stable and
efficient performance even in heavy workloads and long time workloads.

Note that the smallest number of concurrent tasks derived from tree
kinds of hardware capacity determines the best concurrent tasks in the
machine. For example, consider one machine which is equipped with 2
CPU cores and 12 disks. In this cases, 2 CPU will determine the best
number of concurrent tasks in the machine because 2 concurrent tasks
of CPU cores is fewer than 24 concurrent tasks of 12 disks.

Let's get back to the discussion of your machine. If we assume that
the entire resources of your physical node (24cpu, 64G mem,  4T*12
HDD) are used for a Tajo, I would think as follows:

 * 24 concurrent tasks is the best in 24 cores.
 * 24 tasks would be the best in 12 disks if the disks are SATA. If
they are SAS disks, each disk can accept more than 2. 36 may be the
best for 12 disks.
 * Memory seems to be most scarce resource in all resources. OS and
other daemons should use few GBs. So, I assume only 60 GBs may be
available for Tajo. I think that 3GB seems to be the best for each
task. In terms of memory size, 20 concurrent tasks (60 GB / 3GB) in
the machine seems to be proper number.

The lowest concurrency number is 20 by 64GB memory. So, the following
configs may be proper to your physical node.

tajo-site.xml
<!--  worker  -->
<property>
  <name>tajo.worker.resource.memory-mb</name>
  <value>60512</value> <!--  20 tasks + 1 qm (i.e, 3000 * 20 + 512 * 1)  -->
</property>
<property>
  <name>tajo.worker.resource.disks</name>
  <value>20</value> <!--  20 tasks (20 * 1.0f)  -->
</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>


tajo-env.sh
TAJO_WORKER_HEAPSIZE=60000

The above config is for a single physical node dedicated for a Tajo
worker. The configs for virtual machine may be different because each
of them use OS and other daemons.

I hope that my suggestion would be helpful to you.

Best regards,
Hyunsik

On Mon, Jan 19, 2015 at 5:07 PM, Azuryy Yu <azuryyyu@gmail.com> wrote:
> Yes Hyunsik,
>
> but that's all I know from the Tajo website. I guess there are more default
> configurations but not showed on the Tajo wiki, right?
>
>
>
>
> On Mon, Jan 19, 2015 at 4:52 PM, Hyunsik Choi <hyunsik@apache.org> wrote:
>
>> Thank you for sharing the machine information.
>>
>> In my opinion, we can boost up Tajo performance very much in the
>> machine with proper configuration if the server is dedicated for Tajo.
>> I think that the configuration that we mentioned above only uses some
>> of the physical resources in the machine :)
>>
>> Warm regards,
>> Hyunsik
>>
>> On Sun, Jan 18, 2015 at 8:10 PM, Azuryy Yu <azuryyyu@gmail.com> wrote:
>> > Thanks Tyunsik.
>> >
>> > I asked our infra team, my 6 nodes Tajo cluster were visulized from one
>> > host. that's mean I run 6 nodes Tajo cluster on one phisical host.(24cpu,
>> > 64G mem,  4T*12 HDD)
>> >
>> > so I think this was the real performance bottle neck.
>> >
>> >
>> >
>> > On Mon, Jan 19, 2015 at 11:12 AM, Hyunsik Choi <hyunsik@apache.org>
>> wrote:
>> >
>> >> Hi Azuryy,
>> >>
>> >> Tajo automatically rewrites distinct aggregation queries into
>> >> multi-level aggregations. The query rewrite that Jinho suggested may
>> >> be already involved.
>> >>
>> >> I think that your query response times (12 ~ 15 secs) for distinct
>> >> count seems to be reasonable because just count aggregation takes 5
>> >> secs. Usually, distinct aggregation queries are much more slower than
>> >> just aggregation queries because distinct aggregation involves sort,
>> >> large intermediate data, and only distinct value handling.
>> >>
>> >> In addition, I have a question for more better configuration guide.
>> >> Could you share available CPU, memory and disks for Tajo?
>> >>
>> >> Even though Jinho suggested one, there is still room to set exact and
>> >> better configurations. Since the resource configuration determines the
>> >> number of concurrent tasks, it may be main cause of your performance
>> >> problem.
>> >>
>> >> Best regards,
>> >> Hyunsik
>> >>
>> >> On Sun, Jan 18, 2015 at 6:54 PM, Jinho Kim <jhkim@apache.org> wrote:
>> >> >  Sorry for my mistake example query.
>> >> > Can you change to “select count(a.auid) from ( select auid from
>> >> > test_pl_00_0 group by auid ) a;” ?
>> >> >
>> >> > -Jinho
>> >> > Best regards
>> >> >
>> >> > 2015-01-19 11:44 GMT+09:00 Azuryy Yu <azuryyyu@gmail.com>:
>> >> >
>> >> >> Sorry for no response during weekend.
>> >> >> I changed hdfs-site.xml and restart hdfs and tajo.but  It's more
slow
>> >> than
>> >> >> before.
>> >> >>
>> >> >> default> select count(a.auid) from ( select auid from test_pl_00_0
)
>> a;
>> >> >> Progress: 0%, response time: 1.132 sec
>> >> >> Progress: 0%, response time: 1.134 sec
>> >> >> Progress: 0%, response time: 1.536 sec
>> >> >> Progress: 0%, response time: 2.338 sec
>> >> >> Progress: 0%, response time: 3.341 sec
>> >> >> Progress: 3%, response time: 4.343 sec
>> >> >> Progress: 4%, response time: 5.346 sec
>> >> >> Progress: 9%, response time: 6.35 sec
>> >> >> Progress: 11%, response time: 7.352 sec
>> >> >> Progress: 16%, response time: 8.354 sec
>> >> >> Progress: 18%, response time: 9.362 sec
>> >> >> Progress: 24%, response time: 10.364 sec
>> >> >> Progress: 27%, response time: 11.366 sec
>> >> >> Progress: 29%, response time: 12.368 sec
>> >> >> Progress: 32%, response time: 13.37 sec
>> >> >> Progress: 37%, response time: 14.373 sec
>> >> >> Progress: 40%, response time: 15.377 sec
>> >> >> Progress: 42%, response time: 16.379 sec
>> >> >> Progress: 42%, response time: 17.382 sec
>> >> >> Progress: 43%, response time: 18.384 sec
>> >> >> Progress: 43%, response time: 19.386 sec
>> >> >> Progress: 45%, response time: 20.388 sec
>> >> >> Progress: 45%, response time: 21.391 sec
>> >> >> Progress: 46%, response time: 22.393 sec
>> >> >> Progress: 46%, response time: 23.395 sec
>> >> >> Progress: 48%, response time: 24.398 sec
>> >> >> Progress: 48%, response time: 25.401 sec
>> >> >> Progress: 50%, response time: 26.403 sec
>> >> >> Progress: 100%, response time: 26.95 sec
>> >> >> ?count
>> >> >> -------------------------------
>> >> >> 4487999
>> >> >> (1 rows, 26.95 sec, 8 B selected)
>> >> >> default> select count(distinct auid) from test_pl_00_0;
>> >> >> Progress: 0%, response time: 0.88 sec
>> >> >> Progress: 0%, response time: 0.881 sec
>> >> >> Progress: 0%, response time: 1.283 sec
>> >> >> Progress: 0%, response time: 2.086 sec
>> >> >> Progress: 0%, response time: 3.088 sec
>> >> >> Progress: 0%, response time: 4.09 sec
>> >> >> Progress: 25%, response time: 5.092 sec
>> >> >> Progress: 33%, response time: 6.094 sec
>> >> >> Progress: 50%, response time: 7.096 sec
>> >> >> Progress: 50%, response time: 8.098 sec
>> >> >> Progress: 50%, response time: 9.099 sec
>> >> >> Progress: 66%, response time: 10.101 sec
>> >> >> Progress: 66%, response time: 11.103 sec
>> >> >> Progress: 83%, response time: 12.105 sec
>> >> >> Progress: 100%, response time: 12.268 sec
>> >> >> ?count
>> >> >> -------------------------------
>> >> >> 1222356
>> >> >> (1 rows, 12.268 sec, 8 B selected)
>> >> >>
>> >> >> On Sat, Jan 17, 2015 at 11:00 PM, Jinho Kim <jhkim@apache.org>
>> wrote:
>> >> >>
>> >> >> >  Thank you for your sharing
>> >> >> >
>> >> >> > Can you enable the dfs.datanode.hdfs-blocks-metadata.enabled
in
>> >> >> > hdfs-site.xml ?
>> >> >> > If you enable the block-metadata, tajo-cluster can use the
volume
>> load
>> >> >> > balancing. You should restart the datanode and tajo cluster.
I will
>> >> >> > investigate performance of count-distinct operator. and You
can
>> >> change to
>> >> >> > “select count(a.auid) from ( select auid from test_pl_00_0
) a”
>> >> >> >
>> >> >> >
>> >> >> > -Jinho
>> >> >> > Best regards
>> >> >> >
>> >> >> > 2015-01-16 18:05 GMT+09:00 Azuryy Yu <azuryyyu@gmail.com>:
>> >> >> >
>> >> >> > > default> select count(*) from test_pl_00_0;
>> >> >> > > Progress: 0%, response time: 0.718 sec
>> >> >> > > Progress: 0%, response time: 0.72 sec
>> >> >> > > Progress: 0%, response time: 1.121 sec
>> >> >> > > Progress: 12%, response time: 1.923 sec
>> >> >> > > Progress: 28%, response time: 2.925 sec
>> >> >> > > Progress: 41%, response time: 3.927 sec
>> >> >> > > Progress: 50%, response time: 4.931 sec
>> >> >> > > Progress: 100%, response time: 5.323 sec
>> >> >> > > 2015-01-16T17:04:41.116+0800: [GC2015-01-16T17:04:41.116+0800:
>> >> [ParNew:
>> >> >> > > 26543K->6211K(31488K), 0.0079770 secs] 26543K->6211K(115456K),
>> >> >> 0.0080700
>> >> >> > > secs] [Times: user=0.02 sys=0.00, real=0.01 secs]
>> >> >> > > 2015-01-16T17:04:41.303+0800: [GC2015-01-16T17:04:41.303+0800:
>> >> [ParNew:
>> >> >> > > 27203K->7185K(31488K), 0.0066950 secs] 27203K->7185K(115456K),
>> >> >> 0.0068130
>> >> >> > > secs] [Times: user=0.02 sys=0.00, real=0.01 secs]
>> >> >> > > 2015-01-16T17:04:41.504+0800: [GC2015-01-16T17:04:41.504+0800:
>> >> [ParNew:
>> >> >> > > 28177K->5597K(31488K), 0.0091630 secs] 28177K->6523K(115456K),
>> >> >> 0.0092430
>> >> >> > > secs] [Times: user=0.02 sys=0.00, real=0.01 secs]
>> >> >> > > 2015-01-16T17:04:41.778+0800: [GC2015-01-16T17:04:41.778+0800:
>> >> [ParNew:
>> >> >> > > 26589K->6837K(31488K), 0.0067280 secs] 27515K->7764K(115456K),
>> >> >> 0.0068160
>> >> >> > > secs] [Times: user=0.02 sys=0.00, real=0.01 secs]
>> >> >> > > ?count
>> >> >> > > -------------------------------
>> >> >> > > 4487999
>> >> >> > > (1 rows, 5.323 sec, 8 B selected)
>> >> >> > >
>> >> >> > > On Fri, Jan 16, 2015 at 5:03 PM, Azuryy Yu <azuryyyu@gmail.com>
>> >> wrote:
>> >> >> > >
>> >> >> > > > Hi,
>> >> >> > > > There is no big improvement, sometimes more slower
than
>> before. I
>> >> >> also
>> >> >> > > try
>> >> >> > > > to increase worker's heap size and parallel, nothing
improve.
>> >> >> > > >
>> >> >> > > > default> select count(distinct auid) from test_pl_00_0;
>> >> >> > > > Progress: 0%, response time: 0.963 sec
>> >> >> > > > Progress: 0%, response time: 0.964 sec
>> >> >> > > > Progress: 0%, response time: 1.366 sec
>> >> >> > > > Progress: 0%, response time: 2.168 sec
>> >> >> > > > Progress: 0%, response time: 3.17 sec
>> >> >> > > > Progress: 0%, response time: 4.172 sec
>> >> >> > > > Progress: 16%, response time: 5.174 sec
>> >> >> > > > Progress: 16%, response time: 6.176 sec
>> >> >> > > > Progress: 16%, response time: 7.178 sec
>> >> >> > > > Progress: 33%, response time: 8.18 sec
>> >> >> > > > Progress: 50%, response time: 9.181 sec
>> >> >> > > > Progress: 50%, response time: 10.183 sec
>> >> >> > > > Progress: 50%, response time: 11.185 sec
>> >> >> > > > Progress: 50%, response time: 12.187 sec
>> >> >> > > > Progress: 66%, response time: 13.189 sec
>> >> >> > > > Progress: 66%, response time: 14.19 sec
>> >> >> > > > Progress: 100%, response time: 15.003 sec
>> >> >> > > > 2015-01-16T17:00:56.410+0800: [GC2015-01-16T17:00:56.410+0800:
>> >> >> [ParNew:
>> >> >> > > > 26473K->6582K(31488K), 0.0105030 secs] 26473K->6582K(115456K),
>> >> >> > 0.0105720
>> >> >> > > > secs] [Times: user=0.04 sys=0.00, real=0.01 secs]
>> >> >> > > > 2015-01-16T17:00:56.593+0800: [GC2015-01-16T17:00:56.593+0800:
>> >> >> [ParNew:
>> >> >> > > > 27574K->6469K(31488K), 0.0086300 secs] 27574K->6469K(115456K),
>> >> >> > 0.0086940
>> >> >> > > > secs] [Times: user=0.02 sys=0.00, real=0.01 secs]
>> >> >> > > > 2015-01-16T17:00:56.800+0800: [GC2015-01-16T17:00:56.800+0800:
>> >> >> [ParNew:
>> >> >> > > > 27461K->5664K(31488K), 0.0122560 secs] 27461K->6591K(115456K),
>> >> >> > 0.0123210
>> >> >> > > > secs] [Times: user=0.02 sys=0.01, real=0.01 secs]
>> >> >> > > > 2015-01-16T17:00:57.065+0800: [GC2015-01-16T17:00:57.065+0800:
>> >> >> [ParNew:
>> >> >> > > > 26656K->6906K(31488K), 0.0070520 secs] 27583K->7833K(115456K),
>> >> >> > 0.0071470
>> >> >> > > > secs] [Times: user=0.03 sys=0.00, real=0.01 secs]
>> >> >> > > > ?count
>> >> >> > > > -------------------------------
>> >> >> > > > 1222356
>> >> >> > > > (1 rows, 15.003 sec, 8 B selected)
>> >> >> > > >
>> >> >> > > >
>> >> >> > > > On Fri, Jan 16, 2015 at 4:09 PM, Azuryy Yu <azuryyyu@gmail.com
>> >
>> >> >> wrote:
>> >> >> > > >
>> >> >> > > >> Thanks Kim, I'll try and post back.
>> >> >> > > >>
>> >> >> > > >> On Fri, Jan 16, 2015 at 4:02 PM, Jinho Kim <jhkim@apache.org>
>> >> >> wrote:
>> >> >> > > >>
>> >> >> > > >>> Thanks Azuryy Yu
>> >> >> > > >>>
>> >> >> > > >>> Your parallel running tasks of tajo-worker
is 10 but heap
>> >> memory is
>> >> >> > > 3GB.
>> >> >> > > >>> It
>> >> >> > > >>> cause a long JVM pause
>> >> >> > > >>> I recommend following :
>> >> >> > > >>>
>> >> >> > > >>> tajo-env.sh
>> >> >> > > >>> TAJO_WORKER_HEAPSIZE=3000 or more
>> >> >> > > >>>
>> >> >> > > >>> tajo-site.xml
>> >> >> > > >>> <!--  worker  -->
>> >> >> > > >>> <property>
>> >> >> > > >>>   <name>tajo.worker.resource.memory-mb</name>
>> >> >> > > >>>   <value>3512</value> <!--
 3 tasks + 1 qm task  -->
>> >> >> > > >>> </property>
>> >> >> > > >>> <property>
>> >> >> > > >>>   <name>tajo.task.memory-slot-mb.default</name>
>> >> >> > > >>>   <value>1000</value> <!--
 default 512 -->
>> >> >> > > >>> </property>
>> >> >> > > >>> <property>
>> >> >> > > >>>    <name>tajo.worker.resource.dfs-dir-aware</name>
>> >> >> > > >>>    <value>true</value>
>> >> >> > > >>> </property>
>> >> >> > > >>> <!--  end  -->
>> >> >> > > >>>
>> >> >> > >
>> >> >> >
>> >> >>
>> >>
>> http://tajo.apache.org/docs/0.9.0/configuration/worker_configuration.html
>> >> >> > > >>>
>> >> >> > > >>> -Jinho
>> >> >> > > >>> Best regards
>> >> >> > > >>>
>> >> >> > > >>> 2015-01-16 16:02 GMT+09:00 Azuryy Yu <azuryyyu@gmail.com>:
>> >> >> > > >>>
>> >> >> > > >>> > Thanks Kim.
>> >> >> > > >>> >
>> >> >> > > >>> > The following is my tajo-env and tajo-site
>> >> >> > > >>> >
>> >> >> > > >>> > *tajo-env.sh:*
>> >> >> > > >>> > export HADOOP_HOME=/usr/local/hadoop
>> >> >> > > >>> > export JAVA_HOME=/usr/local/java
>> >> >> > > >>> > _TAJO_OPTS="-server -verbose:gc
>> >> >> > > >>> >   -XX:+PrintGCDateStamps
>> >> >> > > >>> >   -XX:+PrintGCDetails
>> >> >> > > >>> >   -XX:+UseGCLogFileRotation
>> >> >> > > >>> >   -XX:NumberOfGCLogFiles=9
>> >> >> > > >>> >   -XX:GCLogFileSize=256m
>> >> >> > > >>> >   -XX:+DisableExplicitGC
>> >> >> > > >>> >   -XX:+UseCompressedOops
>> >> >> > > >>> >   -XX:SoftRefLRUPolicyMSPerMB=0
>> >> >> > > >>> >   -XX:+UseFastAccessorMethods
>> >> >> > > >>> >   -XX:+UseParNewGC
>> >> >> > > >>> >   -XX:+UseConcMarkSweepGC
>> >> >> > > >>> >   -XX:+CMSParallelRemarkEnabled
>> >> >> > > >>> >   -XX:CMSInitiatingOccupancyFraction=70
>> >> >> > > >>> >   -XX:+UseCMSCompactAtFullCollection
>> >> >> > > >>> >   -XX:CMSFullGCsBeforeCompaction=0
>> >> >> > > >>> >   -XX:+CMSClassUnloadingEnabled
>> >> >> > > >>> >   -XX:CMSMaxAbortablePrecleanTime=300
>> >> >> > > >>> >   -XX:+CMSScavengeBeforeRemark
>> >> >> > > >>> >   -XX:PermSize=160m
>> >> >> > > >>> >   -XX:GCTimeRatio=19
>> >> >> > > >>> >   -XX:SurvivorRatio=2
>> >> >> > > >>> >   -XX:MaxTenuringThreshold=60"
>> >> >> > > >>> > _TAJO_MASTER_OPTS="$_TAJO_OPTS -Xmx512m
-Xms512m -Xmn256m"
>> >> >> > > >>> > _TAJO_WORKER_OPTS="$_TAJO_OPTS -Xmx3g
-Xms3g -Xmn1g"
>> >> >> > > >>> > _TAJO_QUERYMASTER_OPTS="$_TAJO_OPTS
-Xmx512m -Xms512m
>> >> -Xmn256m"
>> >> >> > > >>> > export TAJO_OPTS=$_TAJO_OPTS
>> >> >> > > >>> > export TAJO_MASTER_OPTS=$_TAJO_MASTER_OPTS
>> >> >> > > >>> > export TAJO_WORKER_OPTS=$_TAJO_WORKER_OPTS
>> >> >> > > >>> > export TAJO_QUERYMASTER_OPTS=$_TAJO_QUERYMASTER_OPTS
>> >> >> > > >>> > export TAJO_LOG_DIR=${TAJO_HOME}/logs
>> >> >> > > >>> > export TAJO_PID_DIR=${TAJO_HOME}/pids
>> >> >> > > >>> > export TAJO_WORKER_STANDBY_MODE=true
>> >> >> > > >>> >
>> >> >> > > >>> > *tajo-site.xml:*
>> >> >> > > >>> >
>> >> >> > > >>> > <configuration>
>> >> >> > > >>> >   <property>
>> >> >> > > >>> >     <name>tajo.rootdir</name>
>> >> >> > > >>> >     <value>hdfs://test-cluster/tajo</value>
>> >> >> > > >>> >   </property>
>> >> >> > > >>> >   <property>
>> >> >> > > >>> >     <name>tajo.master.umbilical-rpc.address</name>
>> >> >> > > >>> >     <value>10-0-86-51:26001</value>
>> >> >> > > >>> >   </property>
>> >> >> > > >>> >   <property>
>> >> >> > > >>> >     <name>tajo.master.client-rpc.address</name>
>> >> >> > > >>> >     <value>10-0-86-51:26002</value>
>> >> >> > > >>> >   </property>
>> >> >> > > >>> >   <property>
>> >> >> > > >>> >     <name>tajo.resource-tracker.rpc.address</name>
>> >> >> > > >>> >     <value>10-0-86-51:26003</value>
>> >> >> > > >>> >   </property>
>> >> >> > > >>> >   <property>
>> >> >> > > >>> >     <name>tajo.catalog.client-rpc.address</name>
>> >> >> > > >>> >     <value>10-0-86-51:26005</value>
>> >> >> > > >>> >   </property>
>> >> >> > > >>> >   <property>
>> >> >> > > >>> >     <name>tajo.worker.tmpdir.locations</name>
>> >> >> > > >>> >     <value>/test/tajo1,/test/tajo2,/test/tajo3</value>
>> >> >> > > >>> >   </property>
>> >> >> > > >>> >   <!--  worker  -->
>> >> >> > > >>> >   <property>
>> >> >> > > >>> >
>> >> >> >  <name>tajo.worker.resource.tajo.worker.resource.cpu-cores</name>
>> >> >> > > >>> >     <value>4</value>
>> >> >> > > >>> >   </property>
>> >> >> > > >>> >  <property>
>> >> >> > > >>> >    <name>tajo.worker.resource.memory-mb</name>
>> >> >> > > >>> >    <value>5120</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>
>> >> >> > > >>> >
>> >> >> > > >>> > On Fri, Jan 16, 2015 at 2:50 PM, Jinho
Kim <
>> jhkim@apache.org>
>> >> >> > wrote:
>> >> >> > > >>> >
>> >> >> > > >>> > > Hello Azuyy yu
>> >> >> > > >>> > >
>> >> >> > > >>> > > I left some comments.
>> >> >> > > >>> > >
>> >> >> > > >>> > > -Jinho
>> >> >> > > >>> > > Best regards
>> >> >> > > >>> > >
>> >> >> > > >>> > > 2015-01-16 14:37 GMT+09:00 Azuryy
Yu <azuryyyu@gmail.com
>> >:
>> >> >> > > >>> > >
>> >> >> > > >>> > > > Hi,
>> >> >> > > >>> > > >
>> >> >> > > >>> > > > I tested Tajo before half
a year, then not focus on
>> Tajo
>> >> >> > because
>> >> >> > > >>> some
>> >> >> > > >>> > > other
>> >> >> > > >>> > > > works.
>> >> >> > > >>> > > >
>> >> >> > > >>> > > > then I setup a small dev
Tajo cluster this week.(six
>> >> nodes,
>> >> >> VM)
>> >> >> > > >>> based
>> >> >> > > >>> > on
>> >> >> > > >>> > > > Hadoop-2.6.0.
>> >> >> > > >>> > > >
>> >> >> > > >>> > > > so my questions is:
>> >> >> > > >>> > > >
>> >> >> > > >>> > > > 1) From I know half a yea
ago, Tajo is work on Yarn,
>> using
>> >> >> Yarn
>> >> >> > > >>> > scheduler
>> >> >> > > >>> > > > to manage  job resources.
but now I found it doesn't
>> rely
>> >> on
>> >> >> > > Yarn,
>> >> >> > > >>> > > because
>> >> >> > > >>> > > > I only start HDFS daemons,
no yarn daemons. so Tajo has
>> >> his
>> >> >> own
>> >> >> > > job
>> >> >> > > >>> > > > sheduler ?
>> >> >> > > >>> > > >
>> >> >> > > >>> > > >
>> >> >> > > >>> > > Now, tajo does using own task
scheduler. and  You can
>> start
>> >> >> tajo
>> >> >> > > >>> without
>> >> >> > > >>> > > Yarn daemons
>> >> >> > > >>> > > Please refer to
>> >> >> > > http://tajo.apache.org/docs/0.9.0/configuration.html
>> >> >> > > >>> > >
>> >> >> > > >>> > >
>> >> >> > > >>> > > >
>> >> >> > > >>> > > > 2) Does that we need to put
the file replications on
>> every
>> >> >> > nodes
>> >> >> > > on
>> >> >> > > >>> > Tajo
>> >> >> > > >>> > > > cluster?
>> >> >> > > >>> > > >
>> >> >> > > >>> > >
>> >> >> > > >>> > > No, tajo does not need more replication.
 if you set more
>> >> >> > > >>> replication,
>> >> >> > > >>> > data
>> >> >> > > >>> > > locality can be increased
>> >> >> > > >>> > >
>> >> >> > > >>> > > such as I have a six nodes Tajo
cluster, then should I
>> set
>> >> HDFS
>> >> >> > > block
>> >> >> > > >>> > > > replication to six? because:
>> >> >> > > >>> > > >
>> >> >> > > >>> > > > I noticed when I run Tajo
query, some nodes are busy,
>> but
>> >> >> some
>> >> >> > is
>> >> >> > > >>> free.
>> >> >> > > >>> > > > because the file's blocks
are only located on these
>> nodes.
>> >> >> non
>> >> >> > > >>> others.
>> >> >> > > >>> > > >
>> >> >> > > >>> > > >
>> >> >> > > >>> > > In my opinion, you need to run
balancer
>> >> >> > > >>> > >
>> >> >> > > >>> > >
>> >> >> > > >>> >
>> >> >> > > >>>
>> >> >> > >
>> >> >> >
>> >> >>
>> >>
>> http://hadoop.apache.org/docs/r2.6.0/hadoop-project-dist/hadoop-hdfs/HDFSCommands.html#balancer
>> >> >> > > >>> > >
>> >> >> > > >>> > >
>> >> >> > > >>> > > 3)the test data set is 4 million
rows. nearly several GB.
>> >> but
>> >> >> > it's
>> >> >> > > >>> very
>> >> >> > > >>> > > > slow when I runing: select
count(distinct ID) from
>> ****;
>> >> >> > > >>> > > > Any possible problems here?
>> >> >> > > >>> > > >
>> >> >> > > >>> > >
>> >> >> > > >>> > > Could you share tajo-env.sh, tajo-site.xml
?
>> >> >> > > >>> > >
>> >> >> > > >>> > >
>> >> >> > > >>> > > >
>> >> >> > > >>> > > >
>> >> >> > > >>> > > > Thanks
>> >> >> > > >>> > > >
>> >> >> > > >>> > >
>> >> >> > > >>> >
>> >> >> > > >>>
>> >> >> > > >>
>> >> >> > > >>
>> >> >> > > >
>> >> >> > >
>> >> >> >
>> >> >>
>> >>
>>

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