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Container log : error executor.CoarseGrainedExecutorBackend: RECEIVED SIGNAL 15: SIGTERM。
spark log: 17/03/26 23:40:30 ERROR YarnScheduler: Lost executor 2 on hd25: Container killed by YARN for exceeding memory limits. 49.0 GB of 49 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead.
The test sql
At 2017-03-26 23:34:36, "a" <[hidden email]> wrote:
>
>
>I have set the parameters as follow：
>1、fs.hdfs.impl.disable.cache=true
>2、dfs.socket.timeout=1800000 （Exception：aused by: java.io.IOException: Filesystem closed）
>3、dfs.datanode.socket.write.timeout=3600000
>4、set carbondata property enable.unsafe.sort=true
>5、remove BUCKETCOLUMNS property from the create table sql
>6、set spark job parameter executor-memory=48G （from 20G to 48G）
>
>
>But it still failed, the error is "executor.CoarseGrainedExecutorBackend: RECEIVED SIGNAL 15: SIGTERM。"
>
>
>Then i try to insert 40000 0000 records into carbondata table ,it works success.
>
>
>How can i insert 20 0000 0000 records into carbondata?
>Should me set executor-memory big enough? Or Should me generate the csv file from the hive table first ,then load the csv file into carbon table?
>Any body give me same help?
>
>
>Regards
>fish
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>
>
>
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>
>At 2017-03-26 00:34:18, "a" <[hidden email]> wrote:
>>Thank you Ravindra!
>>Version:
>>My carbondata version is 1.0,spark version is 1.6.3,hadoop version is 2.7.1,hive version is 1.1.0
>>one of the containers log:
>>17/03/25 22:07:09 ERROR executor.CoarseGrainedExecutorBackend: RECEIVED SIGNAL 15: SIGTERM
>>17/03/25 22:07:09 INFO storage.DiskBlockManager: Shutdown hook called
>>17/03/25 22:07:09 INFO util.ShutdownHookManager: Shutdown hook called
>>17/03/25 22:07:09 INFO util.ShutdownHookManager: Deleting directory /data1/hadoop/hd_space/tmp/nm-local-dir/usercache/storm/appcache/application_1490340325187_0042/spark-84b305f9-af7b-4f58-a809-700345a84109
>>17/03/25 22:07:10 ERROR impl.ParallelReadMergeSorterImpl: pool-23-thread-2
>>java.io.IOException: Error reading file: hdfs://xxxx_table_tmp/dt=2017-01-01/pt=ios/000006_0
>> at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.next(RecordReaderImpl.java:1046)
>> at org.apache.hadoop.hive.ql.io.orc.OrcRawRecordMerger$OriginalReaderPair.next(OrcRawRecordMerger.java:263)
>> at org.apache.hadoop.hive.ql.io.orc.OrcRawRecordMerger.next(OrcRawRecordMerger.java:547)
>> at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$1.next(OrcInputFormat.java:1234)
>> at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$1.next(OrcInputFormat.java:1218)
>> at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$NullKeyRecordReader.next(OrcInputFormat.java:1150)
>> at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$NullKeyRecordReader.next(OrcInputFormat.java:1136)
>> at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:249)
>> at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:211)
>> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
>> at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>> at org.apache.carbondata.spark.rdd.NewRddIterator.hasNext(NewCarbonDataLoadRDD.scala:412)
>> at org.apache.carbondata.processing.newflow.steps.InputProcessorStepImpl$InputProcessorIterator.internalHasNext(InputProcessorStepImpl.java:163)
>> at org.apache.carbondata.processing.newflow.steps.InputProcessorStepImpl$InputProcessorIterator.getBatch(InputProcessorStepImpl.java:221)
>> at org.apache.carbondata.processing.newflow.steps.InputProcessorStepImpl$InputProcessorIterator.next(InputProcessorStepImpl.java:183)
>> at org.apache.carbondata.processing.newflow.steps.InputProcessorStepImpl$InputProcessorIterator.next(InputProcessorStepImpl.java:117)
>> at org.apache.carbondata.processing.newflow.steps.DataConverterProcessorStepImpl$1.next(DataConverterProcessorStepImpl.java:80)
>> at org.apache.carbondata.processing.newflow.steps.DataConverterProcessorStepImpl$1.next(DataConverterProcessorStepImpl.java:73)
>> at org.apache.carbondata.processing.newflow.sort.impl.ParallelReadMergeSorterImpl$SortIteratorThread.call(ParallelReadMergeSorterImpl.java:196)
>> at org.apache.carbondata.processing.newflow.sort.impl.ParallelReadMergeSorterImpl$SortIteratorThread.call(ParallelReadMergeSorterImpl.java:177)
>> at java.util.concurrent.FutureTask.run(FutureTask.java:262)
>> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>>Caused by: java.io.IOException: Filesystem closed
>> at org.apache.hadoop.hdfs.DFSClient.checkOpen(DFSClient.java:808)
>> at org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy(DFSInputStream.java:868)
>> at org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:934)
>> at java.io.DataInputStream.readFully(DataInputStream.java:195)
>> at org.apache.hadoop.hive.ql.io.orc.MetadataReader.readStripeFooter(MetadataReader.java:112)
>> at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.readStripeFooter(RecordReaderImpl.java:228)
>> at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.beginReadStripe(RecordReaderImpl.java:805)
>> at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.readStripe(RecordReaderImpl.java:776)
>> at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.advanceStripe(RecordReaderImpl.java:986)
>> at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.advanceToNextRow(RecordReaderImpl.java:1019)
>> at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.next(RecordReaderImpl.java:1042)
>> ... 26 more
>>I will try to set enable.unsafe.sort=true and remove BUCKETCOLUMNS property ,and try again.
>>
>>
>>At 2017-03-25 20:55:03, "Ravindra Pesala" <[hidden email]> wrote:
>>>Hi,
>>>
>>>Carbodata launches one job per each node to sort the data at node level and
>>>avoid shuffling. Internally it uses threads to use parallel load. Please
>>>use carbon.number.of.cores.while.loading property in carbon.properties file
>>>and set the number of cores it should use per machine while loading.
>>>Carbondata sorts the data at each node level to maintain the Btree for
>>>each node per segment. It improves the query performance by filtering
>>>faster if we have Btree at node level instead of each block level.
>>>
>>>1.Which version of Carbondata are you using?
>>>2.There are memory issues in Carbondata-1.0 version and are fixed current
>>>master.
>>>3.And you can improve the performance by enabling enable.unsafe.sort=true in
>>>carbon.properties file. But it is not supported if bucketing of columns are
>>>enabled. We are planning to support unsafe sort load for bucketing also in
>>>next version.
>>>
>>>Please send the executor log to know about the error you are facing.
>>>
>>>
>>>
>>>
>>>
>>>
>>>Regards,
>>>Ravindra
>>>
>>>On 25 March 2017 at 16:18, [hidden email] <[hidden email]> wrote:
>>>
>>>> Hello!
>>>>
>>>> *0、The failure*
>>>> When i insert into carbon table，i encounter failure。The failure is as
>>>> follow:
>>>> Job aborted due to stage failure: Task 0 in stage 2.0 failed 4 times, most
>>>> recent failure: Lost task 0.3 in stage 2.0 (TID 1007, hd26):
>>>> ExecutorLostFailure (executor 1 exited caused by one of the running tasks)
>>>> Reason: Slave lost+details
>>>>
>>>> Job aborted due to stage failure: Task 0 in stage 2.0 failed 4 times, most recent failure: Lost task 0.3 in stage 2.0 (TID 1007, hd26): ExecutorLostFailure (executor 1 exited caused by one of the running tasks) Reason: Slave lost
>>>> Driver stacktrace:
>>>>
>>>> the stage:
>>>>
>>>> *Step:*
>>>> *1、start spark－shell*
>>>> ./bin/spark-shell \
>>>> --master yarn-client \
>>>> --num-executors 5 \ (I tried to set this parameter range from 10 to
>>>> 20,but the second job has only 5 tasks)
>>>> --executor-cores 5 \
>>>> --executor-memory 20G \
>>>> --driver-memory 8G \
>>>> --queue root.default \
>>>> --jars /xxx.jar
>>>>
>>>> //spark-default.conf spark.default.parallelism=320
>>>>
>>>> import org.apache.spark.sql.CarbonContext
>>>> val cc = new CarbonContext(sc, "hdfs://xxxx/carbonData/CarbonStore")
>>>>
>>>> *2、create table*
>>>> cc.sql("CREATE TABLE IF NOT EXISTS xxxx_table (dt String,pt String,lst
>>>> String,plat String,sty String,is_pay String,is_vip String,is_mpack
>>>> String,scene String,status String,nw String,isc String,area String,spttag
>>>> String,province String,isp String,city String,tv String,hwm String,pip
>>>> String,fo String,sh String,mid String,user_id String,play_pv Int,spt_cnt
>>>> Int,prg_spt_cnt Int) row format delimited fields terminated by '|' STORED
>>>> BY 'carbondata' TBLPROPERTIES ('DICTIONARY_EXCLUDE'='pip,sh,
>>>> mid,fo,user_id','DICTIONARY_INCLUDE'='dt,pt,lst,plat,sty,
>>>> is_pay,is_vip,is_mpack,scene,status,nw,isc,area,spttag,
>>>> province,isp,city,tv,hwm','NO_INVERTED_INDEX'='lst,plat,hwm,
>>>> pip,sh,mid','BUCKETNUMBER'='10','BUCKETCOLUMNS'='fo')")
>>>>
>>>> //notes，set "fo" column BUCKETCOLUMNS is to join another table
>>>> //the column distinct values are as follows:
>>>>
>>>>
>>>> *3、insert into table*（xxxx_table_tmp is a hive extenal orc table，has 20
>>>> 0000 0000 records）
>>>> cc.sql("insert into xxxx_table select dt,pt,lst,plat,sty,is_pay,is_
>>>> vip,is_mpack,scene,status,nw,isc,area,spttag,province,isp,
>>>> city,tv,hwm,pip,fo,sh,mid,user_id ,play_pv,spt_cnt,prg_spt_cnt from
>>>> xxxx_table_tmp where dt='2017-01-01'")
>>>>
>>>> *4、spark split sql into two jobs，the first finished succeeded, but the
>>>> second failed:*
>>>>
>>>>
>>>> *5、The second job stage:*
>>>>
>>>>
>>>>
>>>> *Question:*
>>>> 1、Why the second job has only five jobs,but the first job has 994 jobs ?(
>>>> note:My hadoop cluster has 5 datanode）
>>>> I guess it caused the failure
>>>> 2、In the sources,i find DataLoadPartitionCoalescer.class，is it means that
>>>> "one datanode has only one partition ,and then the task is only one on the
>>>> datanode"?
>>>> 3、In the ExampleUtils class,"carbon.table.split.partition.enable" is set
>>>> as follow,but i can not find "carbon.table.split.partition.enable" in
>>>> other parts of the project。
>>>> I set "carbon.table.split.partition.enable" to true, but the second
>>>> job has only five jobs.How to use this property?
>>>> ExampleUtils :
>>>> // whether use table split partition
>>>> // true -> use table split partition, support multiple partition
>>>> loading
>>>> // false -> use node split partition, support data load by host
>>>> partition
>>>> CarbonProperties.getInstance().addProperty("carbon.table.split.partition.enable",
>>>> "false")
>>>> 4、Insert into carbon table takes 3 hours ,but eventually failed 。How can
>>>> i speed it.
>>>> 5、in the spark-shell ,I tried to set this parameter range from 10 to
>>>> 20,but the second job has only 5 tasks
>>>> the other parameter executor-memory = 20G is enough?
>>>>
>>>> I need your help!Thank you very much!
>>>>
>>>> [hidden email]
>>>>
>>>> ------------------------------
>>>> [hidden email]
>>>>
>>>
>>>
>>>
>>>--
>>>Thanks & Regards,
>>>Ravi