Hi everyone, I have a cluster where each worker has 110 GB of RAM. On the Cloudera Manager I've configured the following Yarn memory parameters:   yarn.nodemanager.resource.memory-mb 80 GB yarn.scheduler.minimum-allocation-mb 1 GB yarn.scheduler.maximum-allocation-mb 20 GB mapreduce.map.memory.mb 0 mapreduce.reduce.memory.mb 0 yarn.app.mapreduce.am.resource.mb 1 GB mapreduce.job.heap.memory-mb.ratio 0,8 mapreduce.map.java.opts -Djava.net.preferIPv4Stack=true mapreduce.reduce.java.opts -Djava.net.preferIPv4Stack=true Map Task Maximum Heap Size 0 Reduce Task Maximum Heap Size 0     One of my goal was to let YARN to autochoose the correct Java Heap size for the jobs using the 0,8 ratio as the upperbound (20 GB * 0,8 =  16 GB), thus I've leave all the heap and mapper/reducer settings to zero.   I have this hive job which perfoms some joins between large tables. Just running the job as it is I get a failure:   Container [pid=26783,containerID=container_1389136889967_0009_01_000002] is running beyond physical memory limits. Current usage: 2.7 GB of 2 GB physical memory used; 3.7 GB of 3 GB virtual memory used. Killing container. If I explicitly set the memory requirements for the job in the hive code, it completes succesfully:   SET mapreduce.map.memory.mb=8192; SET mapreduce.reduce.memory.mb=16384; SET mapreduce.map.java.opts=-Xmx6553m; SET mapreduce.reduce.java.opts=-Xmx13106m; My question: why does not YARN automatically gives this job enough memory to complete succesfully? Since I have specified 20 GB as the maximum container size and 0,8 as the maximum heap ratio, I was expecting that YARN could give a max of 16 GB to each mapper/reducer without have to me esplicitly specify these parameters.   Could someone please explain what's going on?   Thanks for any information.   ... View more

  Hello everyone!   I have a typical scenario where there are multiple pipelines running on Oozie, each one with different dependencies and time schedules. These pipelines comprise different jobs like Hive, Spark, Java etc. Many of these jobs are heavy on memory, the cluster has a total of 840 GB of RAM, so let's say that the memory is enough to complete any of these jobs but could not be enough to allow several of these jobs to run and complete at the same time.   Sometimes happen that few of these jobs need  to run concurrently, in this case I've noticed a sort of starvation in YARN. None of the jobs continues the execution, there are a lot of heartbeats in the logs, and none eventually completes. YARN is set to use the Fair Scheduler, I would imagine that in a situation like this it should give resources at least to one of the job but it seems that all the jobs are fighting for resources and YARN is not capable to handle the impasse.   I would like to know which are the best practices to handle these type of scenarios. Do I need to define different YARN queues with different resources/priority (actually all the jobs run on the default queue)?       ... View more

Hello everyone, I have a Spark application which runs fine with test tables but fails in production where there are tables with 200 million records and about 100 columns. From the logs the error seems related to Snappy codec, although these tables have been saved in Parquet without compression, and also at write time I have explicitly turned off compression with:      sqlContext.sql("SET hive.exec.compress.output=false") sqlContext.sql("SET parquet.compression=NONE") sqlContext.sql("SET spark.sql.parquet.compression.codec=uncompressed")     The error is the following:     2018-08-01 16:19:45,467 [dag-scheduler-event-loop] INFO org.apache.spark.scheduler.DAGScheduler - ShuffleMapStage 183 (saveAsTable at Model1Prep.scala:776) failed in 543.126 s due to Job aborted due to stage failure: Task 169 in stage 97.0 failed 4 times, most recent failure: Lost task 169.3 in stage 97.0 (TID 15079, prwor-e414c813.azcloud.local, executor 2): java.io.IOException: FAILED_TO_UNCOMPRESS(5) at org.xerial.snappy.SnappyNative.throw_error(SnappyNative.java:78) at org.xerial.snappy.SnappyNative.rawUncompress(Native Method) at org.xerial.snappy.Snappy.rawUncompress(Snappy.java:391) at org.xerial.snappy.Snappy.uncompress(Snappy.java:427) at org.xerial.snappy.SnappyInputStream.readFully(SnappyInputStream.java:127) at org.xerial.snappy.SnappyInputStream.readHeader(SnappyInputStream.java:88) at org.xerial.snappy.SnappyInputStream.<init>(SnappyInputStream.java:58) at org.apache.spark.io.SnappyCompressionCodec.compressedInputStream(CompressionCodec.scala:159) at org.apache.spark.storage.BlockManager.wrapForCompression(BlockManager.scala:1280) at org.apache.spark.util.collection.unsafe.sort.UnsafeSorterSpillReader.<init>(UnsafeSorterSpillReader.java:54) at org.apache.spark.util.collection.unsafe.sort.UnsafeSorterSpillWriter.getReader(UnsafeSorterSpillWriter.java:148) at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.getSortedIterator(UnsafeExternalSorter.java:416) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:117) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:170) at org.apache.spark.sql.execution.Sort$$anonfun$1.apply(Sort.scala:90) at org.apache.spark.sql.execution.Sort$$anonfun$1.apply(Sort.scala:64) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$21.apply(RDD.scala:728) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$21.apply(RDD.scala:728) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:88) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) at org.apache.spark.scheduler.Task.run(Task.scala:89) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:242) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)     Why is this happenig if compression is turned off? Could it be compression is used anyway during shuffle phases?     The cluster has the following characteristics: 2 master nodes 7 worker nodes   Each node has: cpu: 16 cores ram: 110GB hdfs disks: 4x1TB   These are the YARN settings for memory (GB):   yarn.nodemanager.resource.memory-mb 84 yarn.scheduler.minimum-allocation-mb 12 yarn.scheduler.maximum-allocation-mb 84 mapreduce.map.memory.mb 6 mapreduce.reduce.memory.mb 12 mapreduce.map.java.opts 4,8 mapreduce.reduce.java.opts 9,6 yarn.app.mapreduce.am.resource.mb 6 yarn.app.mapreduce.am.command-opts 4,8 yarn.scheduler.maximum-allocation-vcores 5     SPARK on YARN settings: spark.shuffle.service.enabled: ENABLED spark.dynamicAllocation.enabled: ENABLED   SPARK job submission settings:  --driver-memory 30G --executor-cores 5 --executor-memory 30G   Has anyone any hint on why is this happening?                 ... View more

Hello everyone, I have High Availabity of HiveServer2 enabled on a kerberized cluster. I can succesfully connect to beeline with the following command:   beeline -u "jdbc:hive2://trmas-fc2d552a.azcloud.local:2181,trmas-c9471d78.azcloud.local:2181,trmas-6b8bc78c.azcloud.local:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2;ssl=true;"   My problem is when I try to use Hive2 credentials in Oozie (which afaik uses beeline and jdbc connection as above):   <credentials> <credential name="hive2_credentials" type="hive2"> <property> <name>hive2.jdbc.url</name> <value>jdbc:hive2://trmas-fc2d552a.azcloud.local:2181,trmas-c9471d78.azcloud.local:2181,trmas-6b8bc78c.azcloud.local:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2;ssl=true;</value> </property> <property> <name>hive2.server.principal</name> <value>hive/_HOST@AZCLOUD.LOCAL</value> </property> </credential> </credentials> I took the value of hive2.server.principal fron the hive.server2.authentication.kerberos.principal property in the hive-site.xml, is this correct?   This is the hive2 oozie action:   <action cred="hive2_credentials" name="HIVE2_ACTION_NODE"> <hive2 xmlns="uri:oozie:hive2-action:0.1"> <job-tracker>${jobTracker}</job-tracker> <name-node>${nameNode}</name-node> <job-xml>${package}/hive-site.xml</job-xml> <jdbc-url>jdbc:hive2://trmas-fc2d552a.azcloud.local:2181,trmas-c9471d78.azcloud.local:2181,trmas-6b8bc78c.azcloud.local:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2;ssl=true;</jdbc-url> <script>${package}/my_query.hql</script> <param>nameNode=${nameNode}</param> </hive2> <ok to="END_NODE"/> <error to="KILL_NODE"/> </action>   I got this error when running the workflow:   Connecting to jdbc:hive2://trmas-fc2d552a.azcloud.local:2181,trmas-c9471d78.azcloud.local:2181,trmas-6b8bc78c.azcloud.local:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2;ssl=true; Error: Could not open client transport for any of the Server URI's in ZooKeeper: Unable to read HiveServer2 configs from ZooKeeper (state=08S01,code=0) No current connection Intercepting System.exit(2) Failing Oozie Launcher, Main class [org.apache.oozie.action.hadoop.Hive2Main], exit code [2]   Does anyone know how to solve this issue?     ... View more

  I don't understand how includePattern works in Flume. It should accept a regular expression, but the only one that is working to me is the following:     # accepts only .zip files agent.sources.src1.includePattern=^.*\.zip$   But if for example I want to match only files with format WWWW.DDDDD.zip (e.g. abc.123.zip) the followings does not work:   agent.sources.src1.includePattern=^[^\.]+\.[^\.]+\.zip$ agent.sources.src1.includePattern=^\w+\.\d+\.zip$   Does anyone know how regex expressions work in Flume?     ... View more

Hello everyone   I need to run a Spark-SQL action on an Hive table. I am having problems on authentication (the cluster is Kerberos-secured).  I've tried first with hive2 credentials because they work with my other hive2 actions, my I got a failure (I suppose this type of credentials can only be used with hive2 actions?):   2018-04-06 08:37:21,831 [Driver] INFO org.apache.hadoop.hive.ql.session.SessionState - No Tez session required at this point. hive.execution.engine=mr. 2018-04-06 08:37:22,117 [Driver] INFO hive.metastore - Trying to connect to metastore with URI thrift://trmas-fc2d552a.azcloud.local:9083 2018-04-06 08:37:22,153 [Driver] ERROR org.apache.thrift.transport.TSaslTransport - SASL negotiation failure javax.security.sasl.SaslException: GSS initiate failed [Caused by GSSException: No valid credentials provided (Mechanism level: Failed to find any Kerberos tgt)] at com.sun.security.sasl.gsskerb.GssKrb5Client.evaluateChallenge(GssKrb5Client.java:212) at org.apache.thrift.transport.TSaslClientTransport.handleSaslStartMessage(TSaslClientTransport.java:94) [...] I've also tried with hcat credentials, but with this one I got a START_RETRY state of the actin with the following error:   JA009: org.apache.hive.hcatalog.common.HCatException : 9001 : Exception occurred while processing HCat request : TException while getting delegation token.. Cause : org.apache.thrift.transport.TTransportException This is the workflow.xml:   <workflow-app xmlns="uri:oozie:workflow:0.5" name="oozie_spark_wf"> <credentials> <credential name="hive2_credentials" type="hive2"> <property> <name>hive2.jdbc.url</name> <value>jdbc:hive2://trmas-fc2d552a.azcloud.local:10000/default;ssl=true</value> </property> <property> <name>hive2.server.principal</name> <value>hive/trmas-fc2d552a.azcloud.local@AZCLOUD.LOCAL</value> </property> </credential> <credential name="hcat_cred" type="hcat"> <property> <name>hcat.metastore.uri</name> <value>thrift://trmas-fc2d552a.azcloud.local:9083</value> </property> <property> <name>hcat.metastore.principal</name> <value>hive/trmas-fc2d552a.azcloud.local@AZCLOUD.LOCAL</value> </property> </credential> </credentials> <start to="spark_action"/> <action cred="hcat_cred" name="spark_action"> <spark xmlns="uri:oozie:spark-action:0.2"> <job-tracker>${jobTracker}</job-tracker> <name-node>${nameNode}</name-node> <prepare> <delete path="${nameNode}/user/icon0104/output"/> </prepare> <master>yarn-cluster</master> <mode>cluster</mode> <name>OozieSpark</name> <class>my.Main</class> <jar>/home/icon0104/oozie/ooziespark/lib/ooziespark-1.0.jar</jar> <spark-opts>--files ${nameNode}/user/icon0104/oozie/ooziespark/hive-site.xml</spark-opts> </spark> <ok to="END_NODE"/> <error to="KILL_NODE"/> </action> <kill name="KILL_NODE"> <message>${wf:errorMessage(wf:lastErrorNode())}</message> </kill> <end name="END_NODE"/> </workflow-app>   This is the hive-site.xml:   <?xml version="1.0" encoding="UTF-8"?> <!--Autogenerated by Cloudera Manager--> <configuration> <property> <name>hive.metastore.uris</name> <value>thrift://trmas-fc2d552a.azcloud.local:9083</value> </property> <property> <name>hive.metastore.client.socket.timeout</name> <value>300</value> </property> <property> <name>hive.metastore.warehouse.dir</name> <value>/user/hive/warehouse</value> </property> <property> <name>hive.warehouse.subdir.inherit.perms</name> <value>true</value> </property> <property> <name>hive.auto.convert.join</name> <value>false</value> </property> <property> <name>hive.auto.convert.join.noconditionaltask.size</name> <value>20971520</value> </property> <property> <name>hive.optimize.bucketmapjoin.sortedmerge</name> <value>false</value> </property> <property> <name>hive.smbjoin.cache.rows</name> <value>10000</value> </property> <property> <name>hive.server2.logging.operation.enabled</name> <value>true</value> </property> <property> <name>hive.server2.logging.operation.log.location</name> <value>/var/log/hive/operation_logs</value> </property> <property> <name>mapred.reduce.tasks</name> <value>-1</value> </property> <property> <name>hive.exec.reducers.bytes.per.reducer</name> <value>67108864</value> </property> <property> <name>hive.exec.copyfile.maxsize</name> <value>33554432</value> </property> <property> <name>hive.exec.reducers.max</name> <value>1099</value> </property> <property> <name>hive.vectorized.groupby.checkinterval</name> <value>4096</value> </property> <property> <name>hive.vectorized.groupby.flush.percent</name> <value>0.1</value> </property> <property> <name>hive.compute.query.using.stats</name> <value>false</value> </property> <property> <name>hive.vectorized.execution.enabled</name> <value>true</value> </property> <property> <name>hive.vectorized.execution.reduce.enabled</name> <value>false</value> </property> <property> <name>hive.merge.mapfiles</name> <value>true</value> </property> <property> <name>hive.merge.mapredfiles</name> <value>false</value> </property> <property> <name>hive.cbo.enable</name> <value>false</value> </property> <property> <name>hive.fetch.task.conversion</name> <value>minimal</value> </property> <property> <name>hive.fetch.task.conversion.threshold</name> <value>268435456</value> </property> <property> <name>hive.limit.pushdown.memory.usage</name> <value>0.1</value> </property> <property> <name>hive.merge.sparkfiles</name> <value>true</value> </property> <property> <name>hive.merge.smallfiles.avgsize</name> <value>16777216</value> </property> <property> <name>hive.merge.size.per.task</name> <value>268435456</value> </property> <property> <name>hive.optimize.reducededuplication</name> <value>true</value> </property> <property> <name>hive.optimize.reducededuplication.min.reducer</name> <value>4</value> </property> <property> <name>hive.map.aggr</name> <value>true</value> </property> <property> <name>hive.map.aggr.hash.percentmemory</name> <value>0.5</value> </property> <property> <name>hive.optimize.sort.dynamic.partition</name> <value>false</value> </property> <property> <name>hive.execution.engine</name> <value>mr</value> </property> <property> <name>spark.executor.memory</name> <value>268435456</value> </property> <property> <name>spark.driver.memory</name> <value>268435456</value> </property> <property> <name>spark.executor.cores</name> <value>4</value> </property> <property> <name>spark.yarn.driver.memoryOverhead</name> <value>26</value> </property> <property> <name>spark.yarn.executor.memoryOverhead</name> <value>26</value> </property> <property> <name>spark.dynamicAllocation.enabled</name> <value>true</value> </property> <property> <name>spark.dynamicAllocation.initialExecutors</name> <value>1</value> </property> <property> <name>spark.dynamicAllocation.minExecutors</name> <value>1</value> </property> <property> <name>spark.dynamicAllocation.maxExecutors</name> <value>2147483647</value> </property> <property> <name>hive.metastore.execute.setugi</name> <value>true</value> </property> <property> <name>hive.support.concurrency</name> <value>true</value> </property> <property> <name>hive.zookeeper.quorum</name> <value>trmas-6b8bc78c.azcloud.local,trmas-c9471d78.azcloud.local,trmas-fc2d552a.azcloud.local</value> </property> <property> <name>hive.zookeeper.client.port</name> <value>2181</value> </property> <property> <name>hive.zookeeper.namespace</name> <value>hive_zookeeper_namespace_CD-HIVE-LTqXUcrR</value> </property> <property> <name>hbase.zookeeper.quorum</name> <value>trmas-6b8bc78c.azcloud.local,trmas-c9471d78.azcloud.local,trmas-fc2d552a.azcloud.local</value> </property> <property> <name>hbase.zookeeper.property.clientPort</name> <value>2181</value> </property> <property> <name>hive.cluster.delegation.token.store.class</name> <value>org.apache.hadoop.hive.thrift.MemoryTokenStore</value> </property> <property> <name>hive.server2.enable.doAs</name> <value>false</value> </property> <property> <name>hive.metastore.sasl.enabled</name> <value>true</value> </property> <property> <name>hive.server2.authentication</name> <value>kerberos</value> </property> <property> <name>hive.metastore.kerberos.principal</name> <value>hive/_HOST@AZCLOUD.LOCAL</value> </property> <property> <name>hive.server2.authentication.kerberos.principal</name> <value>hive/_HOST@AZCLOUD.LOCAL</value> </property> <property> <name>hive.server2.use.SSL</name> <value>true</value> </property> <property> <name>spark.shuffle.service.enabled</name> <value>true</value> </property> </configuration>     In Oozie configuration I have the following credentials classes enabled:   hcat=org.apache.oozie.action.hadoop.HCatCredentials,hbase=org.apache.oozie.action.hadoop.HbaseCredentials,hive2=org.apache.oozie.action.hadoop.Hive2Credentials   Can anyone help? What am I missing?     ... View more

Hello everybody   I am working on a CDH 5.13.2 cluster configured with Kerberos and LDAP authentication.   I need to connect to Impala thorugh jdbc and impala-shell, but I am having problems on both (Impala queries on HUE work fine).   For impala-shell I've tried:     impala-shell -k -i trwor-b9a4f2a7.azcloud.local ---> Starting Impala Shell using Kerberos authentication Using service name 'impala' Error connecting: TTransportException, TSocket read 0 bytes *********************************************************************************** Welcome to the Impala shell. (Impala Shell v2.10.0-cdh5.13.2 (dc867db) built on Fri Feb 2 10:46:38 PST 2018)   I've also tried without Kerberos:   impala-shell -i trwor-b9a4f2a7.azcloud.local ---> Starting Impala Shell without Kerberos authentication Error connecting: TTransportException, TSocket read 0 bytes Kerberos ticket found in the credentials cache, retrying the connection with a secure transport. Error connecting: TTransportException, TSocket read 0 bytes *********************************************************************************** Welcome to the Impala shell. (Impala Shell v2.10.0-cdh5.13.2 (dc867db) built on Fri Feb 2 10:46:38 PST 2018)   In both cases I got a TTransportException.     I am having trouble also for connecting to Impala through jdbc (using Cloudera_ImpalaJDBC4_2.5.5.1007 driver):     String impalaConnectionUrl = "jdbc:impala://trwor-dafb587f.azcloud.local:21050;AuthMech=1;KrbRealm=AZCLOUD.LOCAL;KrbHostFQDN=trwor-dafb587f.azcloud.local;KrbServiceName=impala"; try { Connection impalaConn = DriverManager.getConnection(impalaConnectionUrl); [...] } catch (SQLEception ex) { [...] } ----> java.sql.SQLException: [Simba][ImpalaJDBCDriver](500310) Invalid operation: Unable to connect to server:; at com.cloudera.impala.hivecommon.api.HiveServer2ClientFactory.createTransport(HiveServer2ClientFactory.java:224) at com.cloudera.impala.hivecommon.api.HiveServer2ClientFactory.createClient(HiveServer2ClientFactory.java:52) at com.cloudera.impala.hivecommon.core.HiveJDBCConnection.connect(HiveJDBCConnection.java:597) at com.cloudera.impala.jdbc.common.BaseConnectionFactory.doConnect(BaseConnectionFactory.java:219) at com.cloudera.impala.jdbc.common.AbstractDriver.connect(AbstractDriver.java:216) at java.sql.DriverManager.getConnection(DriverManager.java:571) at java.sql.DriverManager.getConnection(DriverManager.java:233) at ico.az.deploy.TestSuite.testTeradata(TestSuite.java:98) at ico.az.deploy.TestSuite.run(TestSuite.java:311) Caused by: com.cloudera.impala.support.exceptions.GeneralException: [Simba][ImpalaJDBCDriver](500310) Invalid operation: Unable to connect to server:; ... 9 more Caused by: java.lang.RuntimeException: Unable to connect to server: at com.cloudera.impala.hivecommon.api.HiveServer2ClientFactory$1.run(HiveServer2ClientFactory.java:150) at com.cloudera.impala.hivecommon.api.HiveServer2ClientFactory$1.run(HiveServer2ClientFactory.java:141) at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs(Subject.java:356) at com.cloudera.impala.hivecommon.api.HiveServer2ClientFactory.createTransport(HiveServer2ClientFactory.java:140) at com.cloudera.impala.hivecommon.api.HiveServer2ClientFactory.createClient(HiveServer2ClientFactory.java:52) at com.cloudera.impala.hivecommon.core.HiveJDBCConnection.connect(HiveJDBCConnection.java:597) at com.cloudera.impala.jdbc.common.BaseConnectionFactory.doConnect(BaseConnectionFactory.java:219) at com.cloudera.impala.jdbc.common.AbstractDriver.connect(AbstractDriver.java:216) at java.sql.DriverManager.getConnection(DriverManager.java:571) at java.sql.DriverManager.getConnection(DriverManager.java:233) at ico.az.deploy.TestSuite.testTeradata(TestSuite.java:98) at ico.az.deploy.TestSuite.run(TestSuite.java:311) at ico.az.deploy.TestSuite.main(TestSuite.java:347) Caused by: org.apache.thrift.transport.TTransportException at org.apache.thrift.transport.TIOStreamTransport.read(TIOStreamTransport.java:132) at org.apache.thrift.transport.TTransport.readAll(TTransport.java:84) at org.apache.thrift.transport.TSaslTransport.receiveSaslMessage(TSaslTransport.java:178) at org.apache.thrift.transport.TSaslTransport.open(TSaslTransport.java:258) at org.apache.thrift.transport.TSaslClientTransport.open(TSaslClientTransport.java:37) at com.cloudera.impala.hivecommon.api.HiveServer2ClientFactory$1.run(HiveServer2ClientFactory.java:146) ... 13 more   Regarding connection string parameters: hostname : the host name where is running an Impala daemon, I took this one from Cloudera Manager->Impala->Instances->Impala daemon (there is one deamon running in each worker node, thus I've just choosen the first one). port : taken from  Impala Daemon HiveServer2 Port property property in the Impala Configuration. AuthMech : according to the jdbc driver documentation 1 is for Kerberos authentication. KrbRealm : I took this one from the param default_realm in the /etc/krb5.conf file on the edge node, is this correct? KrbHostFQDN : same as Impala daemon hostname, correct? KrbServiceName : should be "impala" the default, and it is also the nameof  Impala Kerberos Principal on the CM, correct? These are the relevant properties I found on the Cloudera Manager (read only access) for Impala and Kerberos:       I am trying Kerberos authentication because it seems LDAP authentication is disabled for Impala:         What am I doing wrong?       ... View more