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From Vladimir Rodionov <vladrodio...@gmail.com>
Subject Re: RegionTooBusyException
Date Fri, 07 Nov 2014 18:36:17 GMT
>
> With the new stats feature in 3.2/4.2, salting tables is less
> necessary and will likely decrease your overall cluster throughput.

Interesting, where can I get details, James? Is it fast region reassignment
based on load statistics?

-Vladimir Rodionov

On Fri, Nov 7, 2014 at 10:29 AM, James Taylor <jamestaylor@apache.org>
wrote:

> If you salt your table (which pre-splits the table into SALT_BUCKETS
> regions), by default your index will be salted and pre-split the same
> way.
>
> FWIW, you can also presplit your table and index using the SPLIT ON
> (...) syntax: http://phoenix.apache.org/language/index.html#create_table
>
> With the new stats feature in 3.2/4.2, salting tables is less
> necessary and will likely decrease your overall cluster throughput.
>
> Thanks,
> James
>
>
>
> On Fri, Nov 7, 2014 at 10:21 AM, Vladimir Rodionov
> <vladrodionov@gmail.com> wrote:
> > If you see split activity on your index tables, they are either not pre
> > split or region sizes exceeds max limit (you load a lot of data into
> > indexes) or index tables still on default split policy.
> >
> > How do you pre split your index tables?
> >
> > -Vladimir Rodionov
> >
> > On Fri, Nov 7, 2014 at 7:40 AM, Perko, Ralph J <Ralph.Perko@pnnl.gov>
> wrote:
> >>
> >> Salting the table, (gives me pre-splits), and using the split policy of
> >> ConstantSizeRegionSplitPolicy as you suggested worked!
> >>
> >> A question on the index tables – unlike the main table, hbase shows that
> >> each index table has the MAX_FILESIZE attribute set to 344148020 bytes
> which
> >> is well below what is set for the max HStoreFile size property in hbase,
> >> causing a large amount of splitting on all the index tables (which are
> pre
> >> split as well) despite using the same split policy as the main table.
> Why
> >> is this done for just the index tables?  Is it safe to override?
> >>
> >> Thanks,
> >> Ralph
> >> __________________________________________________
> >> Ralph Perko
> >> Pacific Northwest National Laboratory
> >> (509) 375-2272
> >> ralph.perko@pnnl.gov
> >>
> >>
> >> From: Vladimir Rodionov <vladrodionov@gmail.com>
> >> Reply-To: "user@phoenix.apache.org" <user@phoenix.apache.org>
> >> Date: Thursday, November 6, 2014 at 1:04 PM
> >> To: "user@phoenix.apache.org" <user@phoenix.apache.org>
> >> Subject: Re: RegionTooBusyException
> >>
> >> You may want to try different RegionSplitPolicy
> >> (ConstantSizeRegionSplitPolicy), default one
> >> (IncreasingToUpperBoundRegionSplitPolicy)
> >>  does not make sense when table is prespit in advance.
> >>
> >> -Vladimir Rodionov
> >>
> >> On Thu, Nov 6, 2014 at 1:01 PM, Vladimir Rodionov <
> vladrodionov@gmail.com>
> >> wrote:
> >>>
> >>> Too many map task trying concurrently commit (save) data to HBase, I
> bet
> >>> you have compaction hell in your cluster during data loading.
> >>>
> >>> In a few words, you cluster is not able to keep up with data ingestion
> >>> rate. HBase does not do smart update/insert rate throttling for you.
> You may
> >>> try some compaction - related configuration options  :
> >>>    hbase.hstore.blockingWaitTime - Default. 90000
> >>>    hbase.hstore.compaction.min -  Default. 3
> >>>    hbase.hstore.compaction.max - Default. 10
> >>>    hbase.hstore.compaction.min.size - Default: 128 MB expressed in
> bytes.
> >>>
> >>> but I suggest you to pre-split your tables first, than limit # of map
> >>> tasks (if former does not help), than play with compaction config
> values
> >>> (above).
> >>>
> >>>
> >>> -Vladimir Rodionov
> >>>
> >>> On Thu, Nov 6, 2014 at 12:31 PM, Perko, Ralph J <Ralph.Perko@pnnl.gov>
> >>> wrote:
> >>>>
> >>>> Hi, I am using a combination of Pig, Phoenix and HBase to load data
> on a
> >>>> test cluster and I continue to run into an issue with larger, longer
> running
> >>>> jobs (smaller jobs succeed).  After the job has run for several
> hours, the
> >>>> first set of mappers have finished and the second begin, the job dies
> with
> >>>> each mapper failing with the error RegionTooBusyException.  Could
> this be
> >>>> related to how I have my Phoenix tables configured or is this an Hbase
> >>>> configuration issue or something else?  Do you have any suggestions?
> >>>>
> >>>> Thanks for the help,
> >>>> Ralph
> >>>>
> >>>>
> >>>> 2014-11-05 23:08:31,573 INFO [main]
> >>>> org.apache.hadoop.hbase.client.AsyncProcess: #1, waiting for 200
> actions to
> >>>> finish
> >>>> 2014-11-05 23:08:33,729 WARN [phoenix-1-thread-34413]
> >>>> org.apache.hadoop.hbase.client.AsyncProcess: #1, table=T1_CSV_DATA,
> primary,
> >>>> attempt=36/35 failed 200 ops, last exception: null on
> >>>> server1,60020,1415229553858, tracking started Wed Nov 05 22:59:40 PST
> 2014;
> >>>> not retrying 200 - final failure
> >>>> 2014-11-05 23:08:33,736 WARN [main]
> org.apache.hadoop.mapred.YarnChild:
> >>>> Exception running child : java.io.IOException: Exception while
> committing to
> >>>> database.
> >>>> at
> >>>>
> org.apache.phoenix.pig.hadoop.PhoenixRecordWriter.write(PhoenixRecordWriter.java:79)
> >>>> at
> >>>>
> org.apache.phoenix.pig.hadoop.PhoenixRecordWriter.write(PhoenixRecordWriter.java:41)
> >>>> at
> >>>>
> org.apache.phoenix.pig.PhoenixHBaseStorage.putNext(PhoenixHBaseStorage.java:151)
> >>>> at
> >>>>
> org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigOutputFormat$PigRecordWriter.write(PigOutputFormat.java:139)
> >>>> at
> >>>>
> org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigOutputFormat$PigRecordWriter.write(PigOutputFormat.java:98)
> >>>> at
> >>>>
> org.apache.hadoop.mapred.MapTask$NewDirectOutputCollector.write(MapTask.java:635)
> >>>> at
> >>>>
> org.apache.hadoop.mapreduce.task.TaskInputOutputContextImpl.write(TaskInputOutputContextImpl.java:89)
> >>>> at
> >>>>
> org.apache.hadoop.mapreduce.lib.map.WrappedMapper$Context.write(WrappedMapper.java:112)
> >>>> at
> >>>>
> org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigMapOnly$Map.collect(PigMapOnly.java:48)
> >>>> at
> >>>>
> org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapBase.runPipeline(PigGenericMapBase.java:284)
> >>>> at
> >>>>
> org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapBase.map(PigGenericMapBase.java:277)
> >>>> at
> >>>>
> org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapBase.map(PigGenericMapBase.java:64)
> >>>> at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:145)
> >>>> at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:764)
> >>>> at org.apache.hadoop.mapred.MapTask.run(MapTask.java:340)
> >>>> at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:168)
> >>>> at java.security.AccessController.doPrivileged(Native Method)
> >>>> at javax.security.auth.Subject.doAs(Subject.java:396)
> >>>> at
> >>>>
> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1594)
> >>>> at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:163)
> >>>> Caused by: org.apache.phoenix.execute.CommitException:
> >>>> org.apache.hadoop.hbase.client.RetriesExhaustedWithDetailsException:
> Failed
> >>>> 200 actions: RegionTooBusyException: 200 times,
> >>>> at
> >>>>
> org.apache.phoenix.execute.MutationState.commit(MutationState.java:418)
> >>>> at
> >>>>
> org.apache.phoenix.jdbc.PhoenixConnection.commit(PhoenixConnection.java:356)
> >>>> at
> >>>>
> org.apache.phoenix.pig.hadoop.PhoenixRecordWriter.write(PhoenixRecordWriter.java:76)
> >>>> ... 19 more
> >>>> Caused by:
> >>>> org.apache.hadoop.hbase.client.RetriesExhaustedWithDetailsException:
> Failed
> >>>> 200 actions: RegionTooBusyException: 200 times,
> >>>> at
> >>>>
> org.apache.hadoop.hbase.client.AsyncProcess$BatchErrors.makeException(AsyncProcess.java:207)
> >>>> at
> >>>>
> org.apache.hadoop.hbase.client.AsyncProcess$BatchErrors.access$1700(AsyncProcess.java:187)
> >>>> at
> >>>>
> org.apache.hadoop.hbase.client.AsyncProcess$AsyncRequestFutureImpl.getErrors(AsyncProcess.java:1473)
> >>>> at org.apache.hadoop.hbase.client.HTable.batch(HTable.java:855)
> >>>> at org.apache.hadoop.hbase.client.HTable.batch(HTable.java:869)
> >>>> at
> >>>>
> org.apache.phoenix.execute.MutationState.commit(MutationState.java:399)
> >>>> ... 21 more
> >>>>
> >>>> 2014-11-05 23:08:33,739 INFO [main] org.apache.hadoop.mapred.Task:
> >>>> Runnning cleanup for the task
> >>>> 2014-11-05 23:08:33,773 INFO [Thread-11]
> >>>>
> org.apache.hadoop.hbase.client.ConnectionManager$HConnectionImplementation:
> >>>> Closing zookeeper sessionid=0x2497d0ab7e6007e
> >>>>
> >>>> Data size:
> >>>> 75 csv files compressed with bz2
> >>>> 17g compressed – 165g Uncompressed
> >>>>
> >>>> Time-series data, 6 node cluster, 5 region servers.  Hadoop 2.5  (HDP
> >>>> 2.1.5).  Phoenix 4.0, Hbase 0.98,
> >>>>
> >>>> Phoenix Table def:
> >>>>
> >>>> CREATE TABLE IF NOT EXISTS
> >>>> t1_csv_data
> >>>> (
> >>>> timestamp BIGINT NOT NULL,
> >>>> location VARCHAR NOT NULL,
> >>>> fileid VARCHAR NOT NULL,
> >>>> recnum INTEGER NOT NULL,
> >>>> field5 VARCHAR,
> >>>> ...
> >>>> field45 VARCHAR,
> >>>> CONSTRAINT pkey PRIMARY KEY (timestamp,
> >>>> location, fileid,recnum)
> >>>> )
> >>>> IMMUTABLE_ROWS=true,COMPRESSION='SNAPPY',SALT_BUCKETS=10;
> >>>>
> >>>> -- indexes
> >>>> CREATE INDEX t1_csv_data_f1_idx ON t1_csv_data(somefield1)
> >>>> COMPRESSION='SNAPPY';
> >>>> CREATE INDEX t1_csv_data_f2_idx ON t1_csv_data(somefield2)
> >>>> COMPRESSION='SNAPPY';
> >>>> CREATE INDEX t1_csv_data_f3_idx ON t1_csv_data(somefield3)
> >>>> COMPRESSION='SNAPPY';
> >>>>
> >>>> Simple Pig script:
> >>>>
> >>>> register $phoenix_jar;
> >>>> register $udf_jar;
> >>>> Z = load '$data' as (
> >>>> file_id,
> >>>> recnum,
> >>>> dtm:chararray,
> >>>> ...
> >>>> -- lots of other fields
> >>>> );
> >>>> D = foreach Z generate
> >>>> gov.pnnl.pig.TimeStringToPeriod(dtm,'yyyyMMdd
> >>>> HH:mm:ss','yyyyMMddHHmmss'),
> >>>> location,
> >>>> fileid,
> >>>> recnum,
> >>>> ...
> >>>> -- lots of other fields
> >>>> ;
> >>>> STORE D into
> >>>> 'hbase://$table_name' using
> >>>> org.apache.phoenix.pig.PhoenixHBaseStorage('$zookeeper','-batchSize
> >>>> 1000');
> >>>>
> >>>
> >>
> >
>

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