I am working on streaming the data from postgreSQL to HDFS. I had setup confluent environment on HDP 2.6 sandbox. My jdbc source configs for postgreSQL are
name=jdbc_1
connector.class=io.confluent.connect.jdbc.JdbcSourceConnector
tasks.max=1
connection.url=jdbc:postgresql://host:port/db?currentSchema=schema&user=user&password=password
mode=timestamp
timestamp.column.name=col1
validate.non.null=false
topic.prefix=psql-
All other properties for connection are also fine and i am running it by
./bin/connect-standalone ./etc/kafka/connect-standalone.properties ./etc/kafka-connect-jdbc/source.properties
Its working fine and creating topics based on the number of tables in the database as
psql-table1
psql-table2
Now i want to run HDFS sinks on all the topics to create separate dir for every table in the postgreSQL database.
But when i run HDFS sink with command
./bin/connect-standalone ./etc/kafka/connect-standalone.properties ./etc/kafka-connect-hdfs/hdfs-postGres.properties
by running the source i am getting error
ERROR Stopping after connector error (org.apache.kafka.connect.cli.ConnectStandalone:113)
org.apache.kafka.connect.errors.ConnectException: Unable to start REST server
at org.apache.kafka.connect.runtime.rest.RestServer.start(RestServer.java:214)
at org.apache.kafka.connect.runtime.Connect.start(Connect.java:53)
at org.apache.kafka.connect.cli.ConnectStandalone.main(ConnectStandalone.java:95)
Caused by: java.net.BindException: Address already in use
at sun.nio.ch.Net.bind0(Native Method)
at sun.nio.ch.Net.bind(Net.java:433)
at sun.nio.ch.Net.bind(Net.java:425)
at sun.nio.ch.ServerSocketChannelImpl.bind(ServerSocketChannelImpl.java:223)
at sun.nio.ch.ServerSocketAdaptor.bind(ServerSocketAdaptor.java:74)
at org.eclipse.jetty.server.ServerConnector.openAcceptChannel(ServerConnector.java:331)
at org.eclipse.jetty.server.ServerConnector.open(ServerConnector.java:299)
at org.eclipse.jetty.server.AbstractNetworkConnector.doStart(AbstractNetworkConnector.java:80)
at org.eclipse.jetty.server.ServerConnector.doStart(ServerConnector.java:235)
at org.eclipse.jetty.util.component.AbstractLifeCycle.start(AbstractLifeCycle.java:68)
at org.eclipse.jetty.server.Server.doStart(Server.java:398)
at org.eclipse.jetty.util.component.AbstractLifeCycle.start(AbstractLifeCycle.java:68)
at org.apache.kafka.connect.runtime.rest.RestServer.start(RestServer.java:212)
... 2 more
and if i stop the source connection and start the sink it works fine.
Anyone can help me that how i can setup multiple sink connectors.
Kafka Connect starts a rest server on port 8083.
If you run more that one standalone connector on a single machine, you need to change it with the rest.port property
Or you can run connect-distributed, then POST your source and sink configurations individually as JSON payloads running on a single Connect server, then you wouldn't have this Address already in use issue.
Related
I have installed Hadoop (2.9.1) and Hbase (2.1) on my linux machine with the appropriate configurations.
1) I start all hadoop components. Using jps, I am able to see all the components that are running. This step is working fine.
2) When I start hbase, all the hbase components start again . Using the jps command, I am able to see the required components are running again. However, within 10 seconds, Hmaster turns off.
This is the contents of the log file for hbase master:-
The errors outlined below are pretty much the same for both master and regionserver log file.
2018-08-17 17:13:14,255 WARN [main-SendThread(localhost:2181)] zookeeper.ClientCnxn: Session 0x0 for server null, unexpected error, closing socket connection and attempting reconnect
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.zookeeper.ClientCnxnSocketNIO.doTransport(ClientCnxnSocketNIO.java:361)
at org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1141)
I understand that there is some port connection problem, but don't quite know what and where to make the changes.
Thank you in advance for your guidance.
I am creating a jdbc connection to hive using javax.sql.DataSource and passing zookeeper service discovery (obtained from Ambari) string to Hive .
Zookeeper Hive URL : jdbc:hive2://localhost:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2;transportMode=http;httpPath=cliservice
If I make direct jdbc connection with HiveServer host and port then connection work properly but it fails with zookeeper string.
After that I tested zookeeper string with beeline and I worked fine.
Below is exception when connection is made.
Caused by: java.sql.SQLException: Could not open client transport for any of the Server URI's in ZooKeeper: Unable to read HiveServer2 uri from ZooKeeper
at org.apache.hive.jdbc.HiveConnection.openTransport(HiveConnection.java:205)
at org.apache.hive.jdbc.HiveConnection.<init>(HiveConnection.java:163)
at org.apache.hive.jdbc.HiveDriver.connect(HiveDriver.java:105)
at org.apache.tomcat.jdbc.pool.PooledConnection.connectUsingDriver(PooledConnection.java:307)
at org.apache.tomcat.jdbc.pool.PooledConnection.connect(PooledConnection.java:200)
at org.apache.tomcat.jdbc.pool.ConnectionPool.createConnection(ConnectionPool.java:710)
at org.apache.tomcat.jdbc.pool.ConnectionPool.borrowConnection(ConnectionPool.java:644)
at org.apache.tomcat.jdbc.pool.ConnectionPool.init(ConnectionPool.java:466)
at org.apache.tomcat.jdbc.pool.ConnectionPool.<init>(ConnectionPool.java:143)
at org.apache.tomcat.jdbc.pool.DataSourceProxy.pCreatePool(DataSourceProxy.java:115)
at org.apache.tomcat.jdbc.pool.DataSourceProxy.createPool(DataSourceProxy.java:102)
at org.apache.tomcat.jdbc.pool.DataSourceProxy.getConnection(DataSourceProxy.java:126)
at org.apache.tomcat.jdbc.pool.DataSourceProxy.getConnection(DataSourceProxy.java:85)
at com.thinkbiganalytics.kerberos.KerberosUtil.getConnectionWithOrWithoutKerberos(KerberosUtil.java:60)
at com.thinkbiganalytics.hive.service.RefreshableDataSource.getConnectionForValidation(RefreshableDataSource.java:113)
at com.thinkbiganalytics.hive.service.RefreshableDataSource.testAndRefreshIfInvalid(RefreshableDataSource.java:133)
at com.thinkbiganalytics.hive.service.RefreshableDataSource.getConnection(RefreshableDataSource.java:145)
at com.thinkbiganalytics.kerberos.KerberosUtil.getConnectionWithOrWithoutKerberos(KerberosUtil.java:60)
at com.thinkbiganalytics.schema.DBSchemaParser.listCatalogs(DBSchemaParser.java:80)
... 118 more
Caused by: org.apache.hive.jdbc.ZooKeeperHiveClientException: Unable to read HiveServer2 uri from ZooKeeper
at org.apache.hive.jdbc.ZooKeeperHiveClientHelper.getNextServerUriFromZooKeeper(ZooKeeperHiveClientHelper.java:86)
at org.apache.hive.jdbc.Utils.updateConnParamsFromZooKeeper(Utils.java:506)
at org.apache.hive.jdbc.HiveConnection.openTransport(HiveConnection.java:203)
... 136 more
Caused by: org.apache.hive.jdbc.ZooKeeperHiveClientException: Tried all existing HiveServer2 uris from ZooKeeper.
at org.apache.hive.jdbc.ZooKeeperHiveClientHelper.getNextServerUriFromZooKeeper(ZooKeeperHiveClientHelper.java:73)
... 138 more
Did anyone encounter this ?
After spending my 2 days , i figured out problem . I have hive 0.14 dependency in my code where this problem is occurring. To fix i updated below two hive maven dependencies..
Hive Services - https://mvnrepository.com/artifact/org.apache.hive/hive-service/1.2.1000.2.4.2.10-1
Hive JDBC - https://mvnrepository.com/artifact/org.apache.hive/hive-jdbc/1.2.1000.2.4.2.10-1
I deployed Spark (1.3.1) with yarn-client on Hadoop (2.6) cluster using bdutil, by default, the instances are created with Ephemeral external ips, and so far spark works fine. With some security concerns, and assuming the cluster is internal accessed only, I removed the external ips from the instances; after that, the spark-shell will not even run, and seemed it cannot communicate with Yarn/Hadoop, and just stuck indefinitely. Only after I added the external ips back, the spark-shell starts working properly.
My question is, is external ips of the nodes required to run spark over yarn, and why? If yes, will there be any concerns regarding security, etc? Thanks!
Short Answer
You need external IP addresses to access GCS, and default bdutil settings set GCS as the default Hadoop filesystem, including for control files. Use ./bdutil -F hdfs ... deploy to use HDFS as the default instead.
Security shouldn't be a concern when using external IP addresses unless you've added too many permissive rules to your firewall rules in your GCE network config.
EDIT: At the moment there appears to be a bug where we set spark.eventLog.dir to a GCS path even if the default_fs is hdfs. I filed https://github.com/GoogleCloudPlatform/bdutil/issues/35 to track this. In the meantime just manually edit /home/hadoop/spark-install/conf/spark-defaults.conf on your master (you might need to sudo -u hadoop vim.tiny /home/hadoop/spark-install/conf/spark-defaults.conf to have edit permissions on it) to set spark.eventLog.dir to hdfs:///spark-eventlog-base or something else in HDFS, and run hadoop fs -mkdir -p hdfs:///spark-eventlog-base to get it working.
Long Answer
By default, bdutil also configures Google Cloud Storage as the "default Hadoop filesystem", which means that control files used by Spark and YARN require access to Google Cloud Storage. Additionally, external IPs are required in order to access Google Cloud Storage.
I did manage to partially repro your case after manually configuring intra-network SSH; during startup I actually see the following:
15/06/26 17:23:05 INFO yarn.Client: Preparing resources for our AM container
15/06/26 17:23:05 INFO gcs.GoogleHadoopFileSystemBase: GHFS version: 1.4.0-hadoop2
15/06/26 17:23:26 WARN http.HttpTransport: exception thrown while executing request
java.net.SocketTimeoutException: connect timed out
at java.net.PlainSocketImpl.socketConnect(Native Method)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:339)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:200)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:182)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:579)
at sun.security.ssl.SSLSocketImpl.connect(SSLSocketImpl.java:625)
at sun.net.NetworkClient.doConnect(NetworkClient.java:175)
at sun.net.www.http.HttpClient.openServer(HttpClient.java:432)
at sun.net.www.http.HttpClient.openServer(HttpClient.java:527)
at sun.net.www.protocol.https.HttpsClient.<init>(HttpsClient.java:275)
at sun.net.www.protocol.https.HttpsClient.New(HttpsClient.java:371)
at sun.net.www.protocol.https.AbstractDelegateHttpsURLConnection.getNewHttpClient(AbstractDelegateHttpsURLConnection.java:191)
at sun.net.www.protocol.http.HttpURLConnection.plainConnect(HttpURLConnection.java:933)
at sun.net.www.protocol.https.AbstractDelegateHttpsURLConnection.connect(AbstractDelegateHttpsURLConnection.java:177)
at sun.net.www.protocol.https.HttpsURLConnectionImpl.connect(HttpsURLConnectionImpl.java:153)
at com.google.api.client.http.javanet.NetHttpRequest.execute(NetHttpRequest.java:93)
at com.google.api.client.http.HttpRequest.execute(HttpRequest.java:965)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:410)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:343)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.execute(AbstractGoogleClientRequest.java:460)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageImpl.getBucket(GoogleCloudStorageImpl.java:1557)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageImpl.getItemInfo(GoogleCloudStorageImpl.java:1512)
at com.google.cloud.hadoop.gcsio.CacheSupplementedGoogleCloudStorage.getItemInfo(CacheSupplementedGoogleCloudStorage.java:516)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageFileSystem.getFileInfo(GoogleCloudStorageFileSystem.java:1016)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageFileSystem.exists(GoogleCloudStorageFileSystem.java:382)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.configureBuckets(GoogleHadoopFileSystemBase.java:1639)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem.configureBuckets(GoogleHadoopFileSystem.java:71)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.configure(GoogleHadoopFileSystemBase.java:1587)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.initialize(GoogleHadoopFileSystemBase.java:776)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.initialize(GoogleHadoopFileSystemBase.java:739)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2596)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:169)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:216)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:384)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:102)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:58)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:381)
at org.apache.spark.repl.SparkILoop.createSparkContext(SparkILoop.scala:1016)
at $line3.$read$$iwC$$iwC.<init>(<console>:9)
at $line3.$read$$iwC.<init>(<console>:18)
at $line3.$read.<init>(<console>:20)
at $line3.$read$.<init>(<console>:24)
at $line3.$read$.<clinit>(<console>)
at $line3.$eval$.<init>(<console>:7)
at $line3.$eval$.<clinit>(<console>)
at $line3.$eval.$print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:856)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:901)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:813)
at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:123)
at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:122)
at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoopInit.scala:122)
at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:973)
at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.scala:157)
at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkILoopInit.scala:106)
at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:64)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:990)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:944)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:944)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:944)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1058)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
As expected, simply by calling org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start it tries to contact Google Cloud Storage, and fails because there's not GCS access without external IPs.
To get around this, you can simply use -F hdfs when creating your cluster to use HDFS as your default filesystem; in that case everything should work intra-cluster even without external IP addresses. In that mode, you can still even continue to use GCS whenever you have external IP addresses assigned by specifying full gs://bucket/object paths as your Hadoop arguments. However, note that in that case, as long as you've removed the external IP addresses, you won't be able to use GCS unless you also configure a proxy server and funnal all data through your proxy; the GCS configs for that is fs.gs.proxy.address.
In general, there's no need to worry about security just because of having external IP addresses unless you've opened up new permissive rules in your "default" network firewall rules in Google Compute Engine.
I am trying to log the SQL produced by Squeryl in a Play 2 application, for debugging purposes. I am using this with the following Oracle logging properties:
.level=SEVERE
oracle.jdbc.level=FINE
oracle.jdbc.handlers=java.util.logging.ConsoleHandler
java.util.logging.ConsoleHandler.level=ALL
java.util.logging.ConsoleHandler.formatter=java.util.logging.SimpleFormatter
oracle.net.ns.level=FINEST
oracle.net.ns.handlers=java.util.logging.ConsoleHandler
This has worked for me before in a non-Play application with the same Oracle driver jar, but in a Play application, the JUL-to-SLF4J bridge seems to be causing a problem:
Oops, cannot start the server.
Configuration error: Configuration error[Cannot connect to database [default]]
at play.api.Configuration$.play$api$Configuration$$configError(Configuration.scala:92)
at play.api.Configuration.reportError(Configuration.scala:570)
at play.api.db.BoneCPPlugin$$anonfun$onStart$1.apply(DB.scala:252)
at play.api.db.BoneCPPlugin$$anonfun$onStart$1.apply(DB.scala:243)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.immutable.List.foreach(List.scala:318)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.AbstractTraversable.map(Traversable.scala:105)
at play.api.db.BoneCPPlugin.onStart(DB.scala:243)
at play.api.Play$$anonfun$start$1$$anonfun$apply$mcV$sp$1.apply(Play.scala:88)
at play.api.Play$$anonfun$start$1$$anonfun$apply$mcV$sp$1.apply(Play.scala:88)
at scala.collection.immutable.List.foreach(List.scala:318)
at play.api.Play$$anonfun$start$1.apply$mcV$sp(Play.scala:88)
at play.api.Play$$anonfun$start$1.apply(Play.scala:88)
at play.api.Play$$anonfun$start$1.apply(Play.scala:88)
at play.utils.Threads$.withContextClassLoader(Threads.scala:18)
at play.api.Play$.start(Play.scala:87)
at play.core.StaticApplication.<init>(ApplicationProvider.scala:52)
at play.core.server.NettyServer$.createServer(NettyServer.scala:243)
at play.core.server.NettyServer$$anonfun$main$3.apply(NettyServer.scala:279)
at play.core.server.NettyServer$$anonfun$main$3.apply(NettyServer.scala:274)
at scala.Option.map(Option.scala:145)
at play.core.server.NettyServer$.main(NettyServer.scala:274)
at play.core.server.NettyServer.main(NettyServer.scala)
Caused by: java.lang.IllegalArgumentException: can't parse argument number 18=false
at java.text.MessageFormat.makeFormat(MessageFormat.java:1339)
at java.text.MessageFormat.applyPattern(MessageFormat.java:458)
at java.text.MessageFormat.<init>(MessageFormat.java:350)
at java.text.MessageFormat.format(MessageFormat.java:811)
at org.slf4j.bridge.SLF4JBridgeHandler.getMessageI18N(SLF4JBridgeHandler.java:268)
at org.slf4j.bridge.SLF4JBridgeHandler.callLocationAwareLogger(SLF4JBridgeHandler.java:223)
at org.slf4j.bridge.SLF4JBridgeHandler.publish(SLF4JBridgeHandler.java:301)
at java.util.logging.Logger.log(Logger.java:481)
at java.util.logging.Logger.doLog(Logger.java:503)
at java.util.logging.Logger.log(Logger.java:547)
at oracle.net.ns.NSProtocol.establishConnection(NSProtocol.java:919)
at oracle.net.ns.NSProtocol.connect(NSProtocol.java:267)
at oracle.jdbc.driver.T4CConnection.connect(T4CConnection.java:1625)
at oracle.jdbc.driver.T4CConnection.logon(T4CConnection.java:365)
at oracle.jdbc.driver.PhysicalConnection.<init>(PhysicalConnection.java:557)
at oracle.jdbc.driver.T4CConnection.<init>(T4CConnection.java:233)
at oracle.jdbc.driver.T4CDriverExtension.getConnection(T4CDriverExtension.java:29)
at oracle.jdbc.driver.OracleDriver.connect(OracleDriver.java:556)
at java.sql.DriverManager.getConnection(DriverManager.java:582)
at java.sql.DriverManager.getConnection(DriverManager.java:185)
at com.jolbox.bonecp.BoneCP.obtainRawInternalConnection(BoneCP.java:351)
at com.jolbox.bonecp.BoneCP.<init>(BoneCP.java:416)
at com.jolbox.bonecp.BoneCPDataSource.getConnection(BoneCPDataSource.java:120)
at play.api.db.BoneCPPlugin$$anonfun$onStart$1.apply(DB.scala:245)
... 22 more
I tried simply removing the JUL to SLF4J bridge jar from my deployed application, but Play refuses to start if that jar isn't present, so that didn't work.
I obviously don't need to use this particular approach, I just want some way to log the SQL selects being executed (preferably without admin access to the Oracle server).
I just needed to change the oracle.net.ns.level to SEVERE. Logging of oracle.net is only needed if you want to log the network packets being sent to and from the server, which I didn't need in this case.
Before i ask my question let me first explain the scenario. I had setup the hbase cluster on ec2 with 3 instances:
i-xxxxxxx-- master, zookeeper1, regionserver1
i-xxxxxxx-- slave1, zookeeper2, regionserver2
i-xxxxxxx-- slave2, zookeeper3, regionserver3.
Which was working perfectly fine. Now, I was trying to connect to master of this cluster with the remote EMR instance with hive installed.
So, I followed this link of amazon aws documentation :
http://docs.aws.amazon.com/ElasticMapReduce/latest/DeveloperGuide/emr-hbase-access-hive.html
Which says before you create some table. Let hive knows the public-DNS of remote hbase master.
set hbase.zookeeper.quorum=public-DNS-name;
I did exactly which has been mentioned. But, I was not able to connect to the master. I tried create one table using the following script :
CREATE TABLE hauto(cookie string, timespent string, pageviews string, visit string, logdate string)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES ("hbase.columns.mapping" = "m:timespent, m:pageviews, m:visit, m:logdate")
TBLPROPERTIES ("hbase.table.name" = "hauto");
So, it gave this error :
FAILED: Error in metadata: MetaException(message:org.apache.hadoop.hbase.MasterNotRunningException: Retried 10 times
at org.apache.hadoop.hbase.client.HBaseAdmin.<init>(HBaseAdmin.java:127)
at org.apache.hadoop.hive.hbase.HBaseStorageHandler.getHBaseAdmin(HBaseStorageHandler.java:74)
at org.apache.hadoop.hive.hbase.HBaseStorageHandler.preCreateTable(HBaseStorageHandler.java:148)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.createTable(HiveMetaStoreClient.java:467)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.createTable(HiveMetaStoreClient.java:460)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:74)
at com.sun.proxy.$Proxy14.createTable(Unknown Source)
at org.apache.hadoop.hive.ql.metadata.Hive.createTable(Hive.java:600)
at org.apache.hadoop.hive.ql.exec.DDLTask.createTable(DDLTask.java:3791)
at org.apache.hadoop.hive.ql.exec.DDLTask.execute(DDLTask.java:258)
at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:144)
at org.apache.hadoop.hive.ql.exec.TaskRunner.runSequential(TaskRunner.java:57)
at org.apache.hadoop.hive.ql.Driver.launchTask(Driver.java:1355)
at org.apache.hadoop.hive.ql.Driver.execute(Driver.java:1139)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:945)
at org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:310)
at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:231)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:466)
at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:819)
at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:674)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.hadoop.util.RunJar.main(RunJar.java:187)
)
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask
FYI, EMR hive installed instance and EC2 Hbase-cluster are in same security group. I am
able to telnet to 2181, 60000, 60010, 60020 ports from EMR to EC2 as well as EC2 to EMR.
And in that group i have allowed the tcp, udp and ICMP connections on all ports within the group.
My /etc/hosts file of master look like this:
XXXXXXXXXXX master localhost
XXXXXXXXXXX zkserver1 rgserver1
XXXXXXXXXXX zkserver2 rgserver2
XXXXXXXXXXX zkserver3 rgserver3
I am using hadoop 1.0.1, hbase 0.94.11, hive 0.11.0 and zookeeper-3.4.3. And zookeeper is manager externally.
Also, after that i tried other way around. This time i tried to connect from hive CLI installed on EC2 Hbase cluster to EMR Hbase. Now, i was able to create the same table on EMR hbase.
Updated Question:
It seems like this is an issue with amazon ec2. I am providing you the snapshot of those issues also the link :
http://hbase.apache.org/book.html#trouble.log.gc