http://apache-carbondata-dev-mailing-list-archive.168.s1.nabble.com/insert-into-carbon-table-failed-tp9609p9652.html
2、dfs.socket.timeout=1800000 （Exception：aused by: java.io.IOException: Filesystem closed）
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.
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?
>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