Thanks Xuefi.
As I understand from your below statement …… Thus, you only need to build the spark-assembly.jar w/o HIve and put it in Hive's /lib directory…. So this is the procedure I followd: 1. Used spark 1.5.2 pre-built with Hadoop 2.6 as $SPARK_HOME 2. Copied over /usr/lib/spark_1.5.2_build/lib/ spark-assembly-1.5.2-hadoop2.4.0.jar --> $HIVE_HOME/lib 3. Started spark master 4. Started spark slave 5. Logged in to hive in debug mode 6. Ran the following settings a. set spark.home=/usr/lib/spark; b. set hive.execution.engine=spark; c. set spark.master=spark:// 50.140.197.217:7077; --(actually 50.140.197.217 loops back to localhost 127.0.0.1) d. set spark.eventLog.enabled=true; e. set spark.eventLog.dir=/usr/lib/spark/logs; f. set spark.executor.memory=512m; g. set spark.serializer=org.apache.spark.serializer.KryoSerializer; this the log 15/11/28 10:00:04 [main]: INFO spark.SparkTask: set mapreduce.job.reduces=<number> 15/11/28 10:00:04 [main]: INFO session.SparkSessionManagerImpl: Setting up the session manager. 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.connect.timeout -> 1000). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.serializer -> org.apache.spark.serializer.KryoSerializer). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.eventLog.enabled -> true). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.eventLog.dir -> /usr/lib/spark/logs). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.rpc.threads -> 8). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.secret.bits -> 256). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.home -> /usr/lib/spark). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.rpc.max.size -> 52428800). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.master -> spark://50.140.197.217:1077). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.executor.memory -> 512m). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.server.connect.timeout -> 90000). 15/11/28 10:00:04 [main]: DEBUG logging.InternalLoggerFactory: Using SLF4J as the default logging framework 15/11/28 10:00:04 [main]: DEBUG channel.MultithreadEventLoopGroup: -Dio.netty.eventLoopThreads: 24 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent0: java.nio.Buffer.address: available 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent0: sun.misc.Unsafe.theUnsafe: available 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent0: sun.misc.Unsafe.copyMemory: available 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent0: java.nio.Bits.unaligned: true 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: Java version: 7 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: -Dio.netty.noUnsafe: false 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: sun.misc.Unsafe: available 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: -Dio.netty.noJavassist: false 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: Javassist: unavailable 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: You don't have Javassist in your class path or you don't have enough permission to load dynamically generated classes. Please check the configuration for better performance. 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: -Dio.netty.tmpdir: /tmp (java.io.tmpdir) 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: -Dio.netty.bitMode: 64 (sun.arch.data.model) 15/11/28 10:00:04 [main]: DEBUG internal.PlatformDependent: -Dio.netty.noPreferDirect: false 15/11/28 10:00:04 [main]: DEBUG nio.NioEventLoop: -Dio.netty.noKeySetOptimization: false 15/11/28 10:00:04 [main]: DEBUG nio.NioEventLoop: -Dio.netty.selectorAutoRebuildThreshold: 512 15/11/28 10:00:04 [main]: DEBUG internal.ThreadLocalRandom: -Dio.netty.initialSeedUniquifier: 0x615383bf736b2c17 (took 0 ms) 15/11/28 10:00:04 [main]: DEBUG buffer.ByteBufUtil: -Dio.netty.allocator.type: unpooled 15/11/28 10:00:04 [main]: DEBUG buffer.ByteBufUtil: -Dio.netty.threadLocalDirectBufferSize: 65536 15/11/28 10:00:04 [main]: DEBUG util.NetUtil: Loopback interface: lo (lo, 127.0.0.1) 15/11/28 10:00:04 [main]: DEBUG util.NetUtil: /proc/sys/net/core/somaxconn: 128 15/11/28 10:00:04 [main]: WARN rpc.RpcConfiguration: Your hostname, rhes564, resolves to a loopback address; using 192.168.0.9 instead (on interface eth1) 15/11/28 10:00:04 [main]: WARN rpc.RpcConfiguration: Set 'hive.spark.client.server.address' if you need to bind to another address. 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.connect.timeout -> 1000). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.serializer -> org.apache.spark.serializer.KryoSerializer). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.eventLog.enabled -> true). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.eventLog.dir -> /usr/lib/spark/logs). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.rpc.threads -> 8). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.secret.bits -> 256). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.home -> /usr/lib/spark). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.rpc.max.size -> 52428800). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.master -> spark://50.140.197.217:1077). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load spark property from hive configuration (spark.executor.memory -> 512m). 15/11/28 10:00:04 [main]: INFO spark.HiveSparkClientFactory: load RPC property from hive configuration (hive.spark.client.server.connect.timeout -> 90000). 15/11/28 10:00:04 [main]: INFO client.SparkClientImpl: Running client driver with argv: /usr/lib/spark/bin/spark-submit --properties-file /tmp/spark-submit.8364457496527994996.properties --class org.apache.hive.spark.client.RemoteDriver /usr/lib/hive/lib/hive-exec-1.2.1.jar --remote-host 192.168.0.9 --remote-port 38939 --conf hive.spark.client.connect.timeout=1000 --conf hive.spark.client.server.connect.timeout=90000 --conf hive.spark.client.channel.log.level=null --conf hive.spark.client.rpc.max.size=52428800 --conf hive.spark.client.rpc.threads=8 --conf hive.spark.client.secret.bits=256 Failed to execute spark task, with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create spark client.)' 15/11/28 10:00:04 [main]: ERROR spark.SparkTask: Failed to execute spark task, with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create spark client.)' These two lines 15/11/28 10:00:04 [main]: WARN rpc.RpcConfiguration: Your hostname, rhes564, resolves to a loopback address; using 192.168.0.9 instead (on interface eth1) 15/11/28 10:00:04 [main]: WARN rpc.RpcConfiguration: Set 'hive.spark.client.server.address' if you need to bind to another address. Ok the big question is where I can specify explicit value for hive.spark.client.server.address that works. It does not work in hive-site.xml Starting Hive Metastore Server 2015-11-28 10:30:15,372 WARN [main] conf.HiveConf: HiveConf of name hive.spark.client.server.address does not exist Mich Talebzadeh Sybase ASE 15 Gold Medal Award 2008 A Winning Strategy: Running the most Critical Financial Data on ASE 15 http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15", ISBN 978-0-9563693-0-7. co-author "Sybase Transact SQL Guidelines Best Practices", ISBN 978-0-9759693-0-4 Publications due shortly: Complex Event Processing in Heterogeneous Environments, ISBN: 978-0-9563693-3-8 Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume one out shortly http://talebzadehmich.wordpress.com <http://talebzadehmich.wordpress.com/> NOTE: The information in this email is proprietary and confidential. This message is for the designated recipient only, if you are not the intended recipient, you should destroy it immediately. Any information in this message shall not be understood as given or endorsed by Peridale Technology Ltd, its subsidiaries or their employees, unless expressly so stated. It is the responsibility of the recipient to ensure that this email is virus free, therefore neither Peridale Ltd, its subsidiaries nor their employees accept any responsibility. From: Xuefu Zhang [mailto:xzh...@cloudera.com] Sent: 28 November 2015 04:35 To: u...@hive.apache.org Cc: dev@hive.apache.org Subject: Re: Answers to recent questions on Hive on Spark Okay. I think I know what problem you have now. To run Hive on Spark, spark-assembly.jar is needed and it's also recommended that you have a spark installation (identified by spark.home) on the same host where HS2 is running. You only need spark-assembly.jar in HS2's /lib directory. Other than those, Hive on Spark doesn't have any other dependency at service level. On the job level, Hive on Spark jobs of course run on a spark cluster, which could be standalone, yarn-cluster, etc. However, how you get the binaries for your spark cluster and how you start them is completely independent of Hive. Thus, you only need to build the spark-assembly.jar w/o HIve and put it in Hive's /lib directory. The one in the existing spark build may contain Hive classes and that's why you need to build your own. Your spark installation can still have a jar that's different from what you build for Hive on Spark. Your spark.home can still point to your existing spark installation. In fact, Hive on Spark only needs spark-submit from your Spark installation. Therefore, you should be okay even if your spark installation contains Hive classes. By following this, I'm sure you will get your Hive on Spark to work. Depending on the Hive version that your spark installation contains, you may have problem with spark applications such as SparkSQL, but it shouldn't be a concern if you decide that you use Hive in Hive. Let me know if you are still confused. Thanks, Xuefu On Fri, Nov 27, 2015 at 4:34 PM, Mich Talebzadeh <m...@peridale.co.uk <mailto:m...@peridale.co.uk> > wrote: Hi, Thanks for heads up and comments. Sounds like when it comes to using spark as the execution engine for Hive, we are in no man’s land so to speak. I have opened questions in both Hive and Spark user forums. Not much of luck for reasons that you alluded to. Ok just to clarify the prebuild version of spark (as opposed get the source code and build your spec) works fine for me. Components are hadoop version Hadoop 2.6.0 hive --version Hive 1.2.1 Spark version 1.5.2 It does what it says on the tin. For example I can start the master node OK start-master.sh. Spark Command: /usr/java/latest/bin/java -cp /usr/lib/spark_1.5.2_bin/sbin/../conf/:/usr/lib/spark_1.5.2_bin/lib/spark-assembly-1.5.2-hadoop2.6.0.jar:/usr/lib/spark_1.5.2_bin/lib/datanucleus-core-3.2.10.jar:/usr/lib/spark_1.5.2_bin/lib/datanucleus-api-jdo-3.2.6.jar:/usr/lib/spark_1.5.2_bin/lib/datanucleus-rdbms-3.2.9.jar:/home/hduser/hadoop-2.6.0/etc/hadoop/ -Xms1g -Xmx1g -XX:MaxPermSize=256m org.apache.spark.deploy.master.Master --ip 127.0.0.1 --port 7077 --webui-port 8080 ======================================== 15/11/28 00:05:23 INFO master.Master: Registered signal handlers for [TERM, HUP, INT] 15/11/28 00:05:23 WARN util.Utils: Your hostname, rhes564 resolves to a loopback address: 127.0.0.1; using 50.140.197.217 instead (on interface eth0) 15/11/28 00:05:23 WARN util.Utils: Set SPARK_LOCAL_IP if you need to bind to another address 15/11/28 00:05:24 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 15/11/28 00:05:24 INFO spark.SecurityManager: Changing view acls to: hduser 15/11/28 00:05:24 INFO spark.SecurityManager: Changing modify acls to: hduser 15/11/28 00:05:24 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hduser); users with modify permissions: Set(hduser) 15/11/28 00:05:25 INFO slf4j.Slf4jLogger: Slf4jLogger started 15/11/28 00:05:25 INFO Remoting: Starting remoting 15/11/28 00:05:25 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkMaster@127.0.0.1:7077 <http://sparkMaster@127.0.0.1:7077> ] 15/11/28 00:05:25 INFO util.Utils: Successfully started service 'sparkMaster' on port 7077. 15/11/28 00:05:25 INFO master.Master: Starting Spark master at spark://127.0.0.1:7077 <http://127.0.0.1:7077> 15/11/28 00:05:25 INFO master.Master: Running Spark version 1.5.2 15/11/28 00:05:25 INFO server.Server: jetty-8.y.z-SNAPSHOT 15/11/28 00:05:25 INFO server.AbstractConnector: Started SelectChannelConnector@0.0.0.0:8080 <http://SelectChannelConnector@0.0.0.0:8080> 15/11/28 00:05:25 INFO util.Utils: Successfully started service 'MasterUI' on port 8080. 15/11/28 00:05:25 INFO ui.MasterWebUI: Started MasterWebUI at http://50.140.197.217:8080 15/11/28 00:05:25 INFO server.Server: jetty-8.y.z-SNAPSHOT 15/11/28 00:05:25 INFO server.AbstractConnector: Started SelectChannelConnector@rhes564:6066 15/11/28 00:05:25 INFO util.Utils: Successfully started service on port 6066. 15/11/28 00:05:25 INFO rest.StandaloneRestServer: Started REST server for submitting applications on port 6066 15/11/28 00:05:25 INFO master.Master: I have been elected leader! New state: ALIVE However, I cannot use spark in place of MapReduce engine with this build. It fails The instruction says download the source code for spark and build it by excluding Hive jar files so that you can use spark as the execution engine Ok I downloaded spark 1.5.2 source code and used the following to create the tarred and zipped file ./make-distribution.sh --name "hadoop2-without-hive" --tgz "-Pyarn,hadoop-provided,hadoop-2.4,parquet-provided" After unpacking the file, I attempted to start the master node as above start-master.sh, However, regrettably it fails with the following error Spark Command: /usr/java/latest/bin/java -cp /usr/lib/spark_1.5.2_build/sbin/../conf/:/usr/lib/spark_1.5.2_build/lib/spark-assembly-1.5.2-hadoop2.4.0.jar:/home/hduser/hadoop-2.6.0/etc/hadoop/ -Xms1g -Xmx1g -XX:MaxPermSize=256m org.apache.spark.deploy.master.Master --ip 127.0.0.1 --port 7077 --webui-port 8080 ======================================== Exception in thread "main" java.lang.NoClassDefFoundError: org/slf4j/Logger at java.lang.Class.getDeclaredMethods0(Native Method) at java.lang.Class.privateGetDeclaredMethods(Class.java:2521) at java.lang.Class.getMethod0(Class.java:2764) at java.lang.Class.getMethod(Class.java:1653) at sun.launcher.LauncherHelper.getMainMethod(LauncherHelper.java:494) at sun.launcher.LauncherHelper.checkAndLoadMain(LauncherHelper.java:486) Caused by: java.lang.ClassNotFoundException: org.slf4j.Logger at java.net.URLClassLoader$1.run(URLClassLoader.java:366) at java.net.URLClassLoader$1.run(URLClassLoader.java:355) at java.security.AccessController.doPrivileged(Native Method) at java.net.URLClassLoader.findClass(URLClassLoader.java:354) at java.lang.ClassLoader.loadClass(ClassLoader.java:424) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308) at java.lang.ClassLoader.loadClass(ClassLoader.java:357) ... 6 more I believe the problem lies in spark-assembly-1.5.2-hadoop2.4.0.jar file. Case in point, if I copy the jar file spark-assembly-1.5.2-hadoop2.6.0.jar to the lib directory above , I can start the master node. hduser@rhes564::/usr/lib/spark_1.5.2_build/lib <mailto:hduser@rhes564::/usr/lib/spark_1.5.2_build/lib> > mv spark-assembly-1.5.2-hadoop2.4.0.jar spark-assembly-1.5.2-hadoop2.4.0.jar_old hduser@rhes564::/usr/lib/spark_1.5.2_build/lib <mailto:hduser@rhes564::/usr/lib/spark_1.5.2_build/lib> > cp /usr/lib/spark_1.5.2_bin/lib/spark-assembly-1.5.2-hadoop2.6.0.jar . hduser@rhes564::/usr/lib/spark_1.5.2_build/lib <mailto:hduser@rhes564::/usr/lib/spark_1.5.2_build/lib> > cd ../sbin hduser@rhes564::/usr/lib/spark_1.5.2_build/sbin <mailto:hduser@rhes564::/usr/lib/spark_1.5.2_build/sbin> > start-master.sh starting org.apache.spark.deploy.master.Master, logging to /usr/lib/spark_1.5.2_build/sbin/../logs/spark-hduser-org.apache.spark.deploy.master.Master-1-rhes564.out hduser@rhes564::/usr/lib/spark_1.5.2_build/sbin <mailto:hduser@rhes564::/usr/lib/spark_1.5.2_build/sbin> > cat /usr/lib/spark_1.5.2_build/sbin/../logs/spark-hduser-org.apache.spark.deploy.master.Master-1-rhes564.out Spark Command: /usr/java/latest/bin/java -cp /usr/lib/spark_1.5.2_build/sbin/../conf/:/usr/lib/spark_1.5.2_build/lib/spark-assembly-1.5.2-hadoop2.6.0.jar:/home/hduser/hadoop-2.6.0/etc/hadoop/ -Xms1g -Xmx1g -XX:MaxPermSize=256m org.apache.spark.deploy.master.Master --ip 50.140.197.217 --port 7077 --webui-port 8080 ======================================== 15/11/28 00:31:24 INFO master.Master: Registered signal handlers for [TERM, HUP, INT] 15/11/28 00:31:25 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 15/11/28 00:31:25 INFO spark.SecurityManager: Changing view acls to: hduser 15/11/28 00:31:25 INFO spark.SecurityManager: Changing modify acls to: hduser 15/11/28 00:31:25 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hduser); users with modify permissions: Set(hduser) 15/11/28 00:31:25 INFO slf4j.Slf4jLogger: Slf4jLogger started 15/11/28 00:31:26 INFO Remoting: Starting remoting 15/11/28 00:31:26 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkMaster@50.140.197.217:7077 <http://sparkMaster@50.140.197.217:7077> ] 15/11/28 00:31:26 INFO util.Utils: Successfully started service 'sparkMaster' on port 7077. 15/11/28 00:31:26 INFO master.Master: Starting Spark master at spark://50.140.197.217:7077 <http://50.140.197.217:7077> 15/11/28 00:31:26 INFO master.Master: Running Spark version 1.5.2 15/11/28 00:31:26 INFO server.Server: jetty-8.y.z-SNAPSHOT 15/11/28 00:31:26 INFO server.AbstractConnector: Started SelectChannelConnector@0.0.0.0:8080 <http://SelectChannelConnector@0.0.0.0:8080> 15/11/28 00:31:26 INFO util.Utils: Successfully started service 'MasterUI' on port 8080. 15/11/28 00:31:26 INFO ui.MasterWebUI: Started MasterWebUI at http://50.140.197.217:8080 15/11/28 00:31:26 INFO server.Server: jetty-8.y.z-SNAPSHOT 15/11/28 00:31:26 INFO server.AbstractConnector: Started selectchannelconnec...@c-50-140-197-217.hsd1.fl.comcast.net:6066 <http://selectchannelconnec...@c-50-140-197-217.hsd1.fl.comcast.net:6066> 15/11/28 00:31:26 INFO util.Utils: Successfully started service on port 6066. 15/11/28 00:31:26 INFO rest.StandaloneRestServer: Started REST server for submitting applications on port 6066 15/11/28 00:31:27 INFO master.Master: I have been elected leader! New state: ALIVE Thanks again. Mich Talebzadeh Sybase ASE 15 Gold Medal Award 2008 A Winning Strategy: Running the most Critical Financial Data on ASE 15 http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15", ISBN 978-0-9563693-0-7. co-author "Sybase Transact SQL Guidelines Best Practices", ISBN 978-0-9759693-0-4 Publications due shortly: Complex Event Processing in Heterogeneous Environments, ISBN: 978-0-9563693-3-8 Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume one out shortly http://talebzadehmich.wordpress.com <http://talebzadehmich.wordpress.com/> NOTE: The information in this email is proprietary and confidential. This message is for the designated recipient only, if you are not the intended recipient, you should destroy it immediately. Any information in this message shall not be understood as given or endorsed by Peridale Technology Ltd, its subsidiaries or their employees, unless expressly so stated. It is the responsibility of the recipient to ensure that this email is virus free, therefore neither Peridale Ltd, its subsidiaries nor their employees accept any responsibility. From: Xuefu Zhang [mailto:xzh...@cloudera.com <mailto:xzh...@cloudera.com> ] Sent: 27 November 2015 18:12 To: u...@hive.apache.org <mailto:u...@hive.apache.org> ; dev@hive.apache.org <mailto:dev@hive.apache.org> Subject: Answers to recent questions on Hive on Spark Hi there, There seemed an increasing interest in Hive On Spark From the Hive users. I understand that there have been a few questions or problems reported and I can see some frustration sometimes. It's impossible for Hive on Spark team to respond every inquiry even thought we wish we could. However, there are a few items to be noted: 1. Hive on Spark is being tested as part of Precommit test. 2. Hive on Spark is supported in some distributions such as CDH. 3. I tried a couple of days ago with latest master and branch-1, and they all worked with my Spark 1.5 build. Therefore, if you are facing some problem, it's likely due to your setup. Please refer to Wiki on how to do it right. Nevertheless, I have a few suggestions here: 1. Start with simple. Try out a CDH sandbox or distribution first and to see it works in action before building your own. Comparing with your setup may give you some clues. 2. Try with spark.master=local first, making sure that you have all the necessary dependent jars, and then move to your production setup. Please note that yarn-cluster is recommended and mesos is not supported. I tried both yarn-cluster and local-cluster and both worked for me. 3. Check logs beyond hive.log such as spark log, and yarn-log to get more error messages. When you report your problem, please provide as much info as possible, such as your platform, your builds, your configurations, and relevant logs so that others can reproduce. Please note that we are not in a good position to answer questions with respect to Spark itself, such as spark-shell. Not only is that beyond the scope of Hive on Scope, but also the team may not have the expertise to give your meaningful answers. One thing to emphasize. When you build your spark jar, don't include Hive, as it's very likely there is a version mismatch. Again, a distribution may have solve the problem for you if you like to give it a try. Hope this helps. Thanks, Xuefu
