Cassandra Error While running Debezium cassandra Connector - cassandra

I am facing below error while running debezium-cassandra connector: for CDC
sudo java -jar /home/centos/debezium-connector-cassandra-1.2.0.Beta2-jar-with-dependencies.jar /home/centos/debezium-connector-cassandra/deb_conf.properties
Error :
Exception in thread "main" org.apache.cassandra.exceptions.ConfigurationException: Error instantiating snitch class 'org.apache.cassandra.locator.GossipingPropertyFileSnitch'.
at org.apache.cassandra.utils.FBUtilities.construct(FBUtilities.java:596)
at org.apache.cassandra.utils.FBUtilities.construct(FBUtilities.java:574)
at org.apache.cassandra.config.DatabaseDescriptor.createEndpointSnitch(DatabaseDescriptor.java:1045)
at org.apache.cassandra.config.DatabaseDescriptor.applySnitch(DatabaseDescriptor.java:969)
at org.apache.cassandra.config.DatabaseDescriptor.toolInitialization(DatabaseDescriptor.java:192)
at org.apache.cassandra.config.DatabaseDescriptor.toolInitialization(DatabaseDescriptor.java:157)
at io.debezium.connector.cassandra.CassandraConnectorContext.loadDdlFromDisk(CassandraConnectorContext.java:64)
at io.debezium.connector.cassandra.CassandraConnectorContext.<init>(CassandraConnectorContext.java:36)
at io.debezium.connector.cassandra.CassandraConnectorTask.run(CassandraConnectorTask.java:72)
at io.debezium.connector.cassandra.CassandraConnectorTask.main(CassandraConnectorTask.java:61)
Caused by: org.apache.cassandra.exceptions.ConfigurationException: DC or rack not found in snitch properties, check your configuration in: cassandra-rackdc.properties
at org.apache.cassandra.locator.GossipingPropertyFileSnitch.loadConfiguration(GossipingPropertyFileSnitch.java:76)
at org.apache.cassandra.locator.GossipingPropertyFileSnitch.<init>(GossipingPropertyFileSnitch.java:54)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at java.lang.Class.newInstance(Class.java:442)
at org.apache.cassandra.utils.FBUtilities.construct(FBUtilities.java:581)
... 9 more
I checked the cassandra-rackdc.properties is present in the /etc/cassandra/
Cassandra Version: Cassandra 3.11.6
I have changes these param in cassandra.yaml
cdc_enabled: true
cdc_raw_directory: /var/lib/cassandra/cdc_raw
cdc_total_space_in_mb: 4096
cdc_free_space_check_interval_ms: 250
Edit: CASSANDRA_HOME defined and correct.

Related

spark with hive : exception while connecting to local metaStore

buddy.I got a problem while using spark(version 3.2.1) connecting hive(version 3.1.2) metastore (local ) in my mac(Catalina 10.15.7). My hadoop and hive run in my mac in local mode and they both work well (I can insert records into hive table and select them out).
Here is my problem description.
Firstly,I start the metastore Service by
hive --service metastore
Secondly,I run code in spark-shell
val spark = SparkSession.builder() .config("hive.metastore.uris", s"thrift://hiveHost:9083") .enableHiveSupport() .getOrCreate()
Finally,I got exceptions below(there are more in my terminal and I just copy the last several 'caused by' here).By the way,my mysql is version 8.0.27,I do not know if this is related to exception.Thanks for your helping!
Caused by: com.zaxxer.hikari.pool.HikariPool$PoolInitializationException: Failed to initialize pool: Could not create connection to database server.
at com.zaxxer.hikari.pool.HikariPool.checkFailFast(HikariPool.java:512)
at com.zaxxer.hikari.pool.HikariPool.<init>(HikariPool.java:105)
at com.zaxxer.hikari.HikariDataSource.<init>(HikariDataSource.java:71)
at org.datanucleus.store.rdbms.connectionpool.HikariCPConnectionPoolFactory.createConnectionPool(HikariCPConnectionPoolFactory.java:176)
at org.datanucleus.store.rdbms.ConnectionFactoryImpl.generateDataSources(ConnectionFactoryImpl.java:213)
... 198 more
Caused by: com.mysql.jdbc.exceptions.jdbc4.MySQLNonTransientConnectionException: Could not create connection to database server.
at sun.reflect.GeneratedConstructorAccessor150.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at com.mysql.jdbc.Util.handleNewInstance(Util.java:411)
at com.mysql.jdbc.Util.getInstance(Util.java:386)
at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:1015)
at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:989)
at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:975)
at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:920)
at com.mysql.jdbc.ConnectionImpl.connectOneTryOnly(ConnectionImpl.java:2575)
at com.mysql.jdbc.ConnectionImpl.createNewIO(ConnectionImpl.java:2311)
at com.mysql.jdbc.ConnectionImpl.<init>(ConnectionImpl.java:834)
at com.mysql.jdbc.JDBC4Connection.<init>(JDBC4Connection.java:47)
at sun.reflect.GeneratedConstructorAccessor146.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at com.mysql.jdbc.Util.handleNewInstance(Util.java:411)
at com.mysql.jdbc.ConnectionImpl.getInstance(ConnectionImpl.java:416)
at com.mysql.jdbc.NonRegisteringDriver.connect(NonRegisteringDriver.java:347)
at com.zaxxer.hikari.util.DriverDataSource.getConnection(DriverDataSource.java:95)
at com.zaxxer.hikari.util.DriverDataSource.getConnection(DriverDataSource.java:101)
at com.zaxxer.hikari.pool.PoolBase.newConnection(PoolBase.java:341)
at com.zaxxer.hikari.pool.HikariPool.checkFailFast(HikariPool.java:506)
... 202 more
Caused by: java.lang.NullPointerException
at com.mysql.jdbc.ConnectionImpl.getServerCharacterEncoding(ConnectionImpl.java:3286)
at com.mysql.jdbc.MysqlIO.sendConnectionAttributes(MysqlIO.java:1987)
at com.mysql.jdbc.MysqlIO.proceedHandshakeWithPluggableAuthentication(MysqlIO.java:1913)
at com.mysql.jdbc.MysqlIO.doHandshake(MysqlIO.java:1290)
at com.mysql.jdbc.ConnectionImpl.coreConnect(ConnectionImpl.java:2493)
at com.mysql.jdbc.ConnectionImpl.connectOneTryOnly(ConnectionImpl.java:2526)

spark-submit unable to connect

After running the command
spark-submit --class org.apache.spark.examples.SparkPi --proxy-user yarn --master yarn --deploy-mode cluster --driver-memory 4g --executor-memory 2g --executor-cores 1 --queue default ./examples/jars/spark-examples_2.11-2.3.0.jar 10000
I get this in the output and it keeps on retrying. Where am I going wrong? Am I missing some configuration?
I have created a new user for yarn and running that user.
WARN Utils:66 - Your hostname, ukaleem-HP-EliteBook-850-G3 resolves to a loopback address: 127.0.1.1; using 10.XX.XX.XX instead (on interface enp0s31f6)
2018-06-14 16:50:41 WARN Utils:66 - Set SPARK_LOCAL_IP if you need to bind to another address
Warning: Local jar /home/yarn/Documents/Scala-Examples/./examples/jars/spark-examples_2.11-2.3.0.jar does not exist, skipping.
2018-06-14 16:50:42 INFO RMProxy:98 - Connecting to ResourceManager at /0.0.0.0:8032
2018-06-14 16:50:44 INFO Client:871 - Retrying connect to server: 0.0.0.0/0.0.0.0:8032. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
And in the end, it gives the exception
Exception in thread "main" java.net.ConnectException: Call From ukaleem-HP-EliteBook-850-G3/127.0.1.1 to 0.0.0.0:8032 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.GeneratedConstructorAccessor4.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:792)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:732)
at org.apache.hadoop.ipc.Client.call(Client.java:1479)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy8.getClusterMetrics(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ApplicationClientProtocolPBClientImpl.getClusterMetrics(ApplicationClientProtocolPBClientImpl.java:206)
at sun.reflect.GeneratedMethodAccessor7.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy9.getClusterMetrics(Unknown Source)
at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.getYarnClusterMetrics(YarnClientImpl.java:487)
at org.apache.spark.deploy.yarn.Client$$anonfun$submitApplication$1.apply(Client.scala:155)
at org.apache.spark.deploy.yarn.Client$$anonfun$submitApplication$1.apply(Client.scala:155)
at org.apache.spark.internal.Logging$class.logInfo(Logging.scala:54)
at org.apache.spark.deploy.yarn.Client.logInfo(Client.scala:59)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:154)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1146)
at org.apache.spark.deploy.yarn.YarnClusterApplication.start(Client.scala:1518)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:879)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:179)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:177)
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:1698)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:177)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:227)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:136)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.net.ConnectException: Connection refused
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:614)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:712)
at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
at org.apache.hadoop.ipc.Client.call(Client.java:1451)
... 28 more
2018-06-14 17:10:53 INFO ShutdownHookManager:54 - Shutdown hook called
2018-06-14 17:10:53 INFO ShutdownHookManager:54 - Deleting directory /tmp/spark-5bddb7f3-165f-451c-8ab4-bb7729f4237c
EDIT : After adding config files to my spark/conf dir, I get this error now.
The files I added are
*core-site.xml
dfs.hosts
masters
slaves
yarn-site.xml*
And some more. What I understand is that I only need yarn-site.xml to tell spark the location of the yarn cluster. (ids, address, hostname etc).
All this time I had been thinking that even we want to submit a job on Yarn these config need to go in /etc/Hadoop dir not in Spark/conf. Whats the purpose of installing hadoop then (other than communicating)?
And following this question. If the config need to go in spark/conf then HADOOP_CONF_DIR & YARN_CONF_DIR should point to etc/hadoop dir or spark/conf?
INFO client.ConfiguredRMFailoverProxyProvider: Failing over to rm2
18/06/19 11:04:50 INFO retry.RetryInvocationHandler: Exception while invoking getClusterMetrics of class ApplicationClientProtocolPBClientImpl over rm2 after 1 fail over attempts. Trying to fail over after sleeping for 38176ms.
java.net.ConnectException: Call From ukaleem-HP-EliteBook-850-G3/127.0.1.1 to svc-hadoop-mgnt-pre-c2-01.jamba.net:8032 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:792)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:732)
at org.apache.hadoop.ipc.Client.call(Client.java:1479)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy13.getClusterMetrics(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ApplicationClientProtocolPBClientImpl.getClusterMetrics(ApplicationClientProtocolPBClientImpl.java:206)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy14.getClusterMetrics(Unknown Source)
at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.getYarnClusterMetrics(YarnClientImpl.java:487)
at org.apache.spark.deploy.yarn.Client$$anonfun$submitApplication$1.apply(Client.scala:155)
at org.apache.spark.deploy.yarn.Client$$anonfun$submitApplication$1.apply(Client.scala:155)
at org.apache.spark.internal.Logging$class.logInfo(Logging.scala:54)
at org.apache.spark.deploy.yarn.Client.logInfo(Client.scala:59)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:154)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1146)
at org.apache.spark.deploy.yarn.YarnClusterApplication.start(Client.scala:1518)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:879)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:179)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:177)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:177)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:227)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:136)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.net.ConnectException: Connection refused
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:614)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:712)
at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
at org.apache.hadoop.ipc.Client.call(Client.java:1451)
... 29 more
Assuming you have a fully distributed yarn cluster: your spark-submit script is unable to find the configuration for the yarn resourcemanager (basically the yarn master node). Ensure you have HADOOP_CONF_DIR properly set in your environment, and that it points to your cluster's configuration. Specifically your yarn-site.xml.
Edit: more detail
The hadoop package comes with both server and client software. The server software would be the many daemons that run that make up the cluster. If your workstation is acting as a client (using that term loosely, not fully related to sparks --deploy-mode), then the hadoop client software must know the network locations of the server daemons running in the cluster. If your yarn-site.xml is empty, then it is pulling it's default values from yarn-defauls.xml (which is hard-coded, I believe).
Assuming your cluster is not running in HA mode, and is a mostly default configuration, then your workstation's yarn-site.xml should contain at least an entry like the following:
<property>
<name>yarn.resourcemanager.hostname</name>
<value>rm-host.yourdomain.com</value>
</property>
Obviously, replace the hostname with the hostname where your actual resource manager is running. Of course, any spark interaction with HDFS will require a properly configured hdfs-site.xml, etc.
Some cluster managing software will have something like "generate client configs" (thinking of my cloudera experience specifically), which will give you a .tar.gz with all of the config files correctly populated to access the cluster from an external workstation.
Further recommendations:
If you plan to do spark on yarn a lot in this cluster, spark recommends making sure that you have the external shuffle service configured to launch with your yarn node managers. (Please bear in mind, this config directive would have to be present in the yarn-site.xml where yarn's node manager services are running, not on your workstation.
If you are running this on your local machine,
Update your /etc/hosts file, Enter 127.0.0.1 against your hostname.

How to integrate Ganglia for Spark 2.1 Job metrics, Spark ignoring Ganglia metrics

I am trying to integrate Spark 2.1 job's metrics to Ganglia.
My spark-default.conf looks like
*.sink.ganglia.class org.apache.spark.metrics.sink.GangliaSink
*.sink.ganglia.name Name
*.sink.ganglia.host $MASTERIP
*.sink.ganglia.port $PORT
*.sink.ganglia.mode unicast
*.sink.ganglia.period 10
*.sink.ganglia.unit seconds
When i submit my job i can see the warn
Warning: Ignoring non-spark config property: *.sink.ganglia.host=host
Warning: Ignoring non-spark config property: *.sink.ganglia.name=Name
Warning: Ignoring non-spark config property: *.sink.ganglia.mode=unicast
Warning: Ignoring non-spark config property: *.sink.ganglia.class=org.apache.spark.metrics.sink.GangliaSink
Warning: Ignoring non-spark config property: *.sink.ganglia.period=10
Warning: Ignoring non-spark config property: *.sink.ganglia.port=8649
Warning: Ignoring non-spark config property: *.sink.ganglia.unit=seconds
My environment details are
Hadoop : Amazon 2.7.3 - emr-5.7.0
Spark : Spark 2.1.1,
Ganglia: 3.7.2
If you have any inputs or any other alternative of Ganglia please reply.
according to the spark docs
The metrics system is configured via a configuration file that Spark expects to be present at $SPARK_HOME/conf/metrics.properties. A custom file location can be specified via the spark.metrics.conf configuration property.
so instead of having these confs in spark-default.conf, move them to $SPARK_HOME/conf/metrics.properties
For EMR specifically, you'll need to put these settings in /etc/spark/conf/metrics.properties on the master node.
Spark on EMR does include the Ganglia library:
$ ls -l /usr/lib/spark/external/lib/spark-ganglia-lgpl_*
-rw-r--r-- 1 root root 28376 Mar 22 00:43 /usr/lib/spark/external/lib/spark-ganglia-lgpl_2.11-2.3.0.jar
In addition, your example is missing the equals sign (=) between the config names and values - unsure if that's an issue. Below is an example config that worked successfully for me.
*.sink.ganglia.class=org.apache.spark.metrics.sink.GangliaSink
*.sink.ganglia.name=AMZN-EMR
*.sink.ganglia.host=$MASTERIP
*.sink.ganglia.port=8649
*.sink.ganglia.mode=unicast
*.sink.ganglia.period=10
*.sink.ganglia.unit=seconds
From this page:
https://spark.apache.org/docs/latest/monitoring.html
Spark also supports a Ganglia sink which is not included in the default build due to licensing restrictions:
GangliaSink: Sends metrics to a Ganglia node or multicast group.
**To install the GangliaSink you’ll need to perform a custom build of Spark**. Note that by embedding this library you will include LGPL-licensed code in your Spark package. For sbt users, set the SPARK_GANGLIA_LGPL environment variable before building. For Maven users, enable the -Pspark-ganglia-lgpl profile. In addition to modifying the cluster’s Spark build user
I don't know if anyone still needs this. But you have to make the full Ganglia configurations:
# Ganglia conf
*.sink.ganglia.class=org.apache.spark.metrics.sink.GangliaSink
*.sink.ganglia.name=AMZN-EMR
*.sink.ganglia.host=$MASTERIP
*.sink.ganglia.port=8649
*.sink.ganglia.mode=unicast
*.sink.ganglia.period=10
*.sink.ganglia.unit=seconds
# Enable JvmSource for instance master, worker, driver and executor
master.source.jvm.class=org.apache.spark.metrics.source.JvmSource
worker.source.jvm.class=org.apache.spark.metrics.source.JvmSource
driver.source.jvm.class=org.apache.spark.metrics.source.JvmSource
executor.source.jvm.class=org.apache.spark.metrics.source.JvmSource
Even with the full configuration, I'm running into this issue from AWS EMR 5.33.0
21/05/26 14:18:20 ERROR org.apache.spark.metrics.MetricsSystem: Source class org.apache.spark.metrics.source.JvmSource cannot be instantiated
java.lang.ClassNotFoundException: org.apache.spark.metrics.source.JvmSource
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at org.apache.spark.util.Utils$.classForName(Utils.scala:239)
at org.apache.spark.metrics.MetricsSystem$$anonfun$registerSources$1.apply(MetricsSystem.scala:184)
at org.apache.spark.metrics.MetricsSystem$$anonfun$registerSources$1.apply(MetricsSystem.scala:181)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:236)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
at scala.collection.mutable.HashMap.foreach(HashMap.scala:130)
at org.apache.spark.metrics.MetricsSystem.registerSources(MetricsSystem.scala:181)
at org.apache.spark.metrics.MetricsSystem.start(MetricsSystem.scala:102)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:528)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:238)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
21/05/26 14:18:20 ERROR org.apache.spark.metrics.MetricsSystem: Sink class org.apache.spark.metrics.sink.GangliaSink cannot be instantiated
21/05/26 14:18:20 ERROR org.apache.spark.SparkContext: Error initializing SparkContext.
java.lang.ClassNotFoundException: org.apache.spark.metrics.sink.GangliaSink
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at org.apache.spark.util.Utils$.classForName(Utils.scala:239)
at org.apache.spark.metrics.MetricsSystem$$anonfun$registerSinks$1.apply(MetricsSystem.scala:200)
at org.apache.spark.metrics.MetricsSystem$$anonfun$registerSinks$1.apply(MetricsSystem.scala:196)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:236)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
at scala.collection.mutable.HashMap.foreach(HashMap.scala:130)
at org.apache.spark.metrics.MetricsSystem.registerSinks(MetricsSystem.scala:196)
at org.apache.spark.metrics.MetricsSystem.start(MetricsSystem.scala:104)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:528)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:238)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
It's weird because AWS EMR should provide this dependency (org.apache.spark:spark-core_2.11:2.4.7) and I hope that the Spark distribution with AWS EMR is compiled with the Ganglia option. Forcing this jar on --packages or --jars spark options doesn't help either.
If someone manages to get Ganglia working with Spark on AWS EMR with driver/executors jvm monitoring. Please do tell me how.

HA setup of Spark Cluster using Zookeeper Quorum

We are trying to setup Spark HA setup with ZK.
We have 2 machines for Master for Spark process and another 3 for Spark Slaves
The configuration In Master Machine for spark HA done as below in spark-env.sh :
# - SPARK_DAEMON_JAVA_OPTS, to set config properties for all daemons (e.g. "-Dx=y")
export SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=DEV-SMP-Manager01:2181DEV-SMP-Worker01:2181,DEV-SMP-Worker05:2181"
where DEV-SMP-Manager01:2181DEV-SMP-Worker01:2181,DEV-SMP-Worker05:2181 are ZK Quorum. and they are up and running .
When we start the master(s) using command sbin/start-master.sh ,
We have seen some error messages related to curator
java.lang.NoClassDefFoundError: org/apache/curator/RetryPolicy at storm.kafka.KafkaSpout.open(KafkaSpout.java:85) at backtype.storm.daemon.executor$fn__3373$fn__3388.invoke(executor.clj:522) at backtype.storm.util$async_loop$fn__464.invoke(util.clj:461) at clojure.lang.AFn.run(AFn.java:24) at java.lang.Thread.run(Thread.java:745) Caused by: java.lang.ClassNotFoundException: org.apache.curator.RetryPolicy at java.net.URLClassLoader$1.run(URLClassLoader.java:372) at java.net.URLClassLoader$1.run(URLClassLoader.java:361) at java.security.AccessController.doPrivileged(Native Method) at java.net.URLClassLoader.findClass(URLClassLoader.java:360) at java.lang.ClassLoader.loadClass(ClassLoader.java:424) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308) at java.lang.ClassLoader.loadClass(ClassLoader.java:357) ... 5 more
Version used :-
Spark - spark-1.6.1
ZK - 3.4.6
Please try adding the curator-client jar in classpath by adding the following in your spark-env.sh file :
SPARK_CLASSPATH="$SPARK_CLASSPATH:/path/to/curator-client.jar"

Spark 1.1.0 on cdh5.1.3 does not work in yarn-cluster mode

I am having CDH 5.1 (Hadoop 2.3.0-cdh5.1.3) installed on my cluster, version:
I have installed and configured a prebuilt version of Spark 1.1.0 (Apache Version), built for hadoop 2.3 on my cluster.
when I run the Pi example in the ‘client mode’, it runs successfully, but it fails in the ‘yarn-cluster’ mode. The spark job is successfully submitted, but fails after polling the application master for sometime:
More Logs:
Application application_1415193640322_0016 failed 2 times due to Error launching appattempt_1415193640322_0016_000002. Got exception: org.apache.hadoop.yarn.exceptions.YarnException: java.io.EOFException
at org.apache.hadoop.yarn.ipc.RPCUtil.getRemoteException(RPCUtil.java:38)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:710)
at org.apache.hadoop.yarn.api.impl.pb.service.ContainerManagementProtocolPBServiceImpl.startContainers(ContainerManagementProtocolPBServiceImpl.java:60)
at org.apache.hadoop.yarn.proto.ContainerManagementProtocol$ContainerManagementProtocolService$2.callBlockingMethod(ContainerManagementProtocol.java:95)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:587)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1026)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2013)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2009)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2007)
Caused by: java.io.EOFException
at java.io.DataInputStream.readFully(DataInputStream.java:197)
at java.io.DataInputStream.readUTF(DataInputStream.java:609)
at java.io.DataInputStream.readUTF(DataInputStream.java:564)
at org.apache.hadoop.yarn.security.ContainerTokenIdentifier.readFields(ContainerTokenIdentifier.java:151)
at org.apache.hadoop.security.token.Token.decodeIdentifier(Token.java:142)
at org.apache.hadoop.yarn.server.utils.BuilderUtils.newContainerTokenIdentifier(BuilderUtils.java:262)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:696)
... 10 more
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at org.apache.hadoop.yarn.ipc.RPCUtil.instantiateException(RPCUtil.java:53)
at org.apache.hadoop.yarn.ipc.RPCUtil.unwrapAndThrowException(RPCUtil.java:101)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:99)
at org.apache.hadoop.yarn.server.resourcemanager.amlauncher.AMLauncher.launch(AMLauncher.java:118)
at org.apache.hadoop.yarn.server.resourcemanager.amlauncher.AMLauncher.run(AMLauncher.java:249)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.yarn.exceptions.YarnException): java.io.EOFException
at org.apache.hadoop.yarn.ipc.RPCUtil.getRemoteException(RPCUtil.java:38)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:710)
at org.apache.hadoop.yarn.api.impl.pb.service.ContainerManagementProtocolPBServiceImpl.startContainers(ContainerManagementProtocolPBServiceImpl.java:60)
at org.apache.hadoop.yarn.proto.ContainerManagementProtocol$ContainerManagementProtocolService$2.callBlockingMethod(ContainerManagementProtocol.java:95)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:587)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1026)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2013)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2009)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2007)
Caused by: java.io.EOFException
at java.io.DataInputStream.readFully(DataInputStream.java:197)
at java.io.DataInputStream.readUTF(DataInputStream.java:609)
at java.io.DataInputStream.readUTF(DataInputStream.java:564)
at org.apache.hadoop.yarn.security.ContainerTokenIdentifier.readFields(ContainerTokenIdentifier.java:151)
at org.apache.hadoop.security.token.Token.decodeIdentifier(Token.java:142)
at org.apache.hadoop.yarn.server.utils.BuilderUtils.newContainerTokenIdentifier(BuilderUtils.java:262)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:696)
... 10 more
at org.apache.hadoop.ipc.Client.call(Client.java:1409)
at org.apache.hadoop.ipc.Client.call(Client.java:1362)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:206)
at com.sun.proxy.$Proxy69.startContainers(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:96)
... 5 more
. Failing the application.
When I go to node Manager logs:
Log Type: stderr
Log Length: 87
Error: Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
Can you please suggest any solution.Do you think I should compile the spark code on my cluster. Or should I use Spark provided with CDH5.1.
Any help will be appreciated!
spark-shell does not work with spark yarn-cluster mode. You should add --master yarn-client
Example:
path/to/pyspark --master yarn-client

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