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Title | Views | Posted |
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3187 | 03-20-2017 03:06 PM |
06-21-2017
04:39 PM
hello we installed HDP 2.6.1 and would like to setup ssl for zeppelin. on the server that zeppelin is installed, the port 8443 is already been used by other service, how do I change the ssl port for zeppelin?
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Apache Zeppelin
06-19-2017
08:15 PM
Hello @Dominika Bialek thanks for the reponse. that was the issue. After adding S3 location, the issue resolved
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06-19-2017
04:31 PM
1 Kudo
Hello, When I tried running the following command, I am getting the error: alter table btest.testtable add IF NOT EXISTS partition (load_date='2017-06-19') location 's3a://testbucket/data/xxx/load_date=2017-06-19'; I am getting the following error: Error while compiling statement: FAILED: HiveAccessControlException Permission denied: user [hive] does not have [READ] privilege on [s3a://testbucket/data/xxx/load_date=2017-06-19] FYI: Select statement works fine. I can run select statement having data located in S3. it is just that insert statement is failing. We are using ranger for authorization but hive user has full permission on all the databases, tables
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Apache Hive
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Apache Ranger
04-19-2017
08:23 PM
Thank you for the response. I did it using creating the temp hive table
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04-17-2017
04:09 AM
Hello, is there a way to split 2 GB ORC file in to 50MB files? We have many ORC files (larger than 1GB) in HDFS. We are planning to move those files to S3 and configure Hive external table to S3. The performance has been significantly affected by copying the larger files. If I split those files in to multiple files of 50MB or less and copy to S3 than the performance is comparable to HDFS (to test I created another table stored as ORC and insert the existing table data which created multiple files but that is not a viable solution as I have tables with multiple partition and many tables). Is it possible to split the ORC files in to multiple files?
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Apache Hadoop
03-26-2017
10:30 PM
for e.g.
I have a table in my source database having columns monthid (int),
monthshort (string). I copy the data of the table daily using nifi and store in hdfs.
I have created external table in hive:
CREATE external table if not exists test.s3amonths(
monthid int,
monthshort string )
PARTITIONED BY (load_date string)
ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.orc.OrcSerde'
STORED AS INPUTFORMAT 'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat'
LOCATION 'hdfs://xxx/bshah-s3hdptest/test/months';
daily loading the data using following statement: alter table test.s3amonths add IF NOT EXISTS partition (load_date='2016-12-10') location 'hdfs://xxx/bshah-s3hdptest/test/months/load_date=2016-12-10';
alter table teset.s3amonths add IF NOT EXISTS partition (load_date='2016-12-11') location 'hdfs://xxx/bshah-s3hdptest/test/months/load_date=2016-10-11'; Now the schema in the source table change to : monthid (int), monthlong (string),monthshort (string) when loading the new partition how do I ensure that the existing data will not be affected and the new data having additional column information will also be loaded successfully
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Apache Hadoop
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Apache Hive
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Apache NiFi
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HDFS
03-20-2017
03:06 PM
Thanks for the reply. I am on HDP 2.4.2 and Hive 1.2.1.2.4 version. The cluster is created using EC2 instances. I found the solution for the proxy issue. When setup initially, it was setup with fs.s3a.proxy.host and fs.s3a.proxy.port variable. Now we setup the S3 endpoint in route table so it does not use the proxy any more to connect to s3. I removed those two variable from hdfs xml file and that has resolved the performance issue
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03-20-2017
03:06 PM
Thanks for the reply. I am on HDP 2.4.2 and Hive 1.2.1.2.4 version. The cluster is created using EC2 instances. I found the solution for the proxy issue. When setup initially, it was setup with fs.s3a.proxy.host and fs.s3a.proxy.port variable. Now we setup the S3 endpoint in route table so it does not use the proxy any more to connect to s3. I removed those two variable from hdfs xml file and that has resolved the performance issue
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03-16-2017
03:47 AM
Hello, I have created an external table pointing to s3 location. when I run a query using hive or beeline it is taking a lot of time to retrieve the result. The file format that I use is orc. just to give you some perspective: external table created using HDFS ORC object gives results in less than 30 sec while the same takes more than 30 min when the object in S3. Also I see lot of below error in task logs (and I think that's taking a lot of time to retrieve the result as I see in the log for more than 30 mins the same error constantly. 2017-03-16 02:41:28,153 [INFO] [TezChild] |http.AmazonHttpClient|: Unable to execute HTTP request: Read timed out
java.net.SocketTimeoutException: Read timed out
at java.net.SocketInputStream.socketRead0(Native Method)
at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
at java.net.SocketInputStream.read(SocketInputStream.java:170)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at org.apache.http.impl.io.AbstractSessionInputBuffer.fillBuffer(AbstractSessionInputBuffer.java:166)
at org.apache.http.impl.io.SocketInputBuffer.fillBuffer(SocketInputBuffer.java:90)
at org.apache.http.impl.io.AbstractSessionInputBuffer.readLine(AbstractSessionInputBuffer.java:281)
at org.apache.http.impl.conn.DefaultHttpResponseParser.parseHead(DefaultHttpResponseParser.java:92)
at org.apache.http.impl.conn.DefaultHttpResponseParser.parseHead(DefaultHttpResponseParser.java:62)
at org.apache.http.impl.io.AbstractMessageParser.parse(AbstractMessageParser.java:254)
at org.apache.http.impl.AbstractHttpClientConnection.receiveResponseHeader(AbstractHttpClientConnection.java:289)
at org.apache.http.impl.conn.DefaultClientConnection.receiveResponseHeader(DefaultClientConnection.java:252)
at org.apache.http.impl.conn.ManagedClientConnectionImpl.receiveResponseHeader(ManagedClientConnectionImpl.java:191)
at org.apache.http.protocol.HttpRequestExecutor.doReceiveResponse(HttpRequestExecutor.java:300)
at com.amazonaws.http.protocol.SdkHttpRequestExecutor.doReceiveResponse(SdkHttpRequestExecutor.java:66)
at org.apache.http.protocol.HttpRequestExecutor.execute(HttpRequestExecutor.java:127)
at org.apache.http.impl.client.DefaultRequestDirector.createTunnelToTarget(DefaultRequestDirector.java:902)
at org.apache.http.impl.client.DefaultRequestDirector.establishRoute(DefaultRequestDirector.java:821)
at org.apache.http.impl.client.DefaultRequestDirector.tryConnect(DefaultRequestDirector.java:647)
at org.apache.http.impl.client.DefaultRequestDirector.execute(DefaultRequestDirector.java:479)
at org.apache.http.impl.client.AbstractHttpClient.execute(AbstractHttpClient.java:906)
at org.apache.http.impl.client.AbstractHttpClient.execute(AbstractHttpClient.java:805)
at com.amazonaws.http.AmazonHttpClient.executeHelper(AmazonHttpClient.java:384)
at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:232)
at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3528)
at com.amazonaws.services.s3.AmazonS3Client.getObject(AmazonS3Client.java:1111)
at org.apache.hadoop.fs.s3a.S3AInputStream.reopen(S3AInputStream.java:91)
at org.apache.hadoop.fs.s3a.S3AInputStream.seek(S3AInputStream.java:115)
at org.apache.hadoop.fs.FSDataInputStream.seek(FSDataInputStream.java:62)
at org.apache.hadoop.hive.ql.io.orc.MetadataReader.readStripeFooter(MetadataReader.java:111)
at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.readStripeFooter(RecordReaderImpl.java:245)
at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.beginReadStripe(RecordReaderImpl.java:831)
at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.readStripe(RecordReaderImpl.java:802)
at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.advanceStripe(RecordReaderImpl.java:1013)
at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.advanceToNextRow(RecordReaderImpl.java:1046)
at org.apache.hadoop.hive.ql.io.orc.RecordReaderImpl.nextBatch(RecordReaderImpl.java:1101)
at org.apache.hadoop.hive.ql.io.orc.VectorizedOrcInputFormat$VectorizedOrcRecordReader.next(VectorizedOrcInputFormat.java:120)
at org.apache.hadoop.hive.ql.io.orc.VectorizedOrcInputFormat$VectorizedOrcRecordReader.next(VectorizedOrcInputFormat.java:54)
at org.apache.hadoop.hive.ql.io.HiveContextAwareRecordReader.doNext(HiveContextAwareRecordReader.java:350)
at org.apache.hadoop.hive.ql.io.HiveRecordReader.doNext(HiveRecordReader.java:79)
at org.apache.hadoop.hive.ql.io.HiveRecordReader.doNext(HiveRecordReader.java:33)
at org.apache.hadoop.hive.ql.io.HiveContextAwareRecordReader.next(HiveContextAwareRecordReader.java:116)
at org.apache.hadoop.mapred.split.TezGroupedSplitsInputFormat$TezGroupedSplitsRecordReader.next(TezGroupedSplitsInputFormat.java:141)
at org.apache.tez.mapreduce.lib.MRReaderMapred.next(MRReaderMapred.java:113)
at org.apache.hadoop.hive.ql.exec.tez.MapRecordSource.pushRecord(MapRecordSource.java:61)
at org.apache.hadoop.hive.ql.exec.tez.MapRecordProcessor.run(MapRecordProcessor.java:328)
at org.apache.hadoop.hive.ql.exec.tez.TezProcessor.initializeAndRunProcessor(TezProcessor.java:150)
at org.apache.hadoop.hive.ql.exec.tez.TezProcessor.run(TezProcessor.java:139)
at org.apache.tez.runtime.LogicalIOProcessorRuntimeTask.run(LogicalIOProcessorRuntimeTask.java:344)
at org.apache.tez.runtime.task.TezTaskRunner$TaskRunnerCallable$1.run(TezTaskRunner.java:181)
at org.apache.tez.runtime.task.TezTaskRunner$TaskRunnerCallable$1.run(TezTaskRunner.java:172)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1709)
at org.apache.tez.runtime.task.TezTaskRunner$TaskRunnerCallable.callInternal(TezTaskRunner.java:172)
at org.apache.tez.runtime.task.TezTaskRunner$TaskRunnerCallable.callInternal(TezTaskRunner.java:168)
at org.apache.tez.common.CallableWithNdc.call(CallableWithNdc.java:36)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
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Apache Hive