I am trying the run a Presto DB on my local machine to connect the data from Azure Datalake store. Even after adding the JAR files for Azure Data lake store not able to fetch the data from Azure DataLake Store.
I get the below error:
Query 20181005_191247_00000_wcgur failed: No FileSystem for scheme: adl
com.facebook.presto.spi.PrestoException: No FileSystem for scheme: adl
at com.facebook.presto.hive.BackgroundHiveSplitLoader$HiveSplitLoaderTask.process(BackgroundHiveSplitLoader.java:189)
at com.facebook.presto.hive.util.ResumableTasks.safeProcessTask(ResumableTasks.java:47)
at com.facebook.presto.hive.util.ResumableTasks.access$000(ResumableTasks.java:20)
at com.facebook.presto.hive.util.ResumableTasks$1.run(ResumableTasks.java:35)
at io.airlift.concurrent.BoundedExecutor.drainQueue(BoundedExecutor.java:78)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: No FileSystem for scheme: adl
at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2660)
at org.apache.hadoop.fs.PrestoFileSystemCache.createFileSystem(PrestoFileSystemCache.java:114)
at org.apache.hadoop.fs.PrestoFileSystemCache.getInternal(PrestoFileSystemCache.java:89)
at org.apache.hadoop.fs.PrestoFileSystemCache.get(PrestoFileSystemCache.java:62)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295)
at com.facebook.presto.hive.HdfsEnvironment.lambda$getFileSystem$0(HdfsEnvironment.java:71)
at com.facebook.presto.hive.authentication.NoHdfsAuthentication.doAs(NoHdfsAuthentication.java:23)
at com.facebook.presto.hive.HdfsEnvironment.getFileSystem(HdfsEnvironment.java:70)
at com.facebook.presto.hive.HdfsEnvironment.getFileSystem(HdfsEnvironment.java:64)
at com.facebook.presto.hive.BackgroundHiveSplitLoader.loadPartition(BackgroundHiveSplitLoader.java:282)
at com.facebook.presto.hive.BackgroundHiveSplitLoader.loadSplits(BackgroundHiveSplitLoader.java:256)
at com.facebook.presto.hive.BackgroundHiveSplitLoader.access$300(BackgroundHiveSplitLoader.java:91)
at com.facebook.presto.hive.BackgroundHiveSplitLoader$HiveSplitLoaderTask.process(BackgroundHiveSplitLoader.java:185)
... 7 more
Reference:
Persto server: presto-server-0.212.tar.gz
Presto CLI: presto-cli-0.212-executable.jar
JARs added to plugin/hive-hadoop2:
hadoop-azure-datalake-3.1.1.jar
azure-data-lake-store-sdk-2.3.2.jar
hadoop-azure-3.1.1.jar
hive.properties
connector.name=hive-hadoop2
hive.metastore.uri=thrift://hive:9083
hive.config.resources=presto/server/etc/catalog/adls-site.xml
adls-site.xml
<configuration>
<property>
<name>fs.adl.impl</name>
<value>org.apache.hadoop.fs.adl.AdlFileSystem</value>
</property>
<property>
<name>fs.AbstractFileSystem.adl.impl</name>
<value>org.apache.hadoop.fs.adl.Adl</value>
</property>
<property>
<name>fs.adl.oauth2.access.token.provider.type</name>
<value>ClientCredential</value>
</property>
<property>
<name>fs.adl.oauth2.refresh.url</name>
<value>my_url</value>
</property>
<property>
<name>fs.adl.oauth2.client.id</name>
<value>my_id</value>
</property>
<property>
<name>fs.adl.oauth2.credential</name>
<value>my_cred</value>
</property>
</configuration>
Any comment on this will be much helpful. Thanks in advance!
Related
Simple queries, e.g. select, work fine, but when I use aggregate functions, e.g. count, I face errors.
I use beeline to connect to Hive 2.1.1 with Spark 2.2.0 and Hadoop 2.8.
hive-site.xml is as follows:
<property>
<name>hive.execution.engine</name>
<value>spark</value>
<description>
Expects one of [mr, tez, spark].
Chooses execution engine. Options are: mr (Map reduce, default), tez, spark. While MR
remains the default engine for historical reasons, it is itself a historical engine
and is deprecated in Hive 2 line. It may be removed without further warning.
</description>
</property>
<property>
<name>spark.master</name>
<value>spark://master:7077</value>
<description>Spark Master URL</description>
</property>
<property>
<name>spark.eventLog.enabled</name>
<value>true</value>
<description>Spark Event Log</description>
</property>
<property>
<name>spark.eventLog.dir</name>
<value>hdfs://master:8020/user/spark/eventLogging</value>
<description>Spark event log folder</description>
</property>
<property>
<name>spark.executor.memory</name>
<value>512m</value>
<description>Spark executor memory</description>
</property>
<property>
<name>spark.serializer</name>
<value>org.apache.spark.serializer.KryoSerializer</value>
<description>Spark serializer</description>
</property>
<property>
<name>spark.yarn.jars</name>
<value>hdfs://master:9000:/user/spark/spark-jars/*</value>
</property>
<property>
<name>spark.master</name>
<value>spark://master:7077</value>
<description>Spark Master URL</description>
</property>
<property>
<name>spark.eventLog.enabled</name>
<value>true</value>
<description>Spark Event Log</description>
</property>
<property>
<name>spark.eventLog.dir</name>
<value>hdfs://master:8020/user/spark/eventLogging</value>
<description>Spark event log folder</description>
</property>
<property>
<name>spark.executor.memory</name>
<value>512m</value>
<description>Spark executor memory</description>
</property>
<property>
<name>spark.serializer</name>
<value>org.apache.spark.serializer.KryoSerializer</value>
<description>Spark serializer</description>
</property>
<property>
<name>spark.yarn.jars</name>
<value>hdfs://master:9000:/user/spark/spark-jars/*</value>
</property>
When executing select count(*) from table in hive I get the below error:
WARN thrift.ThriftCLIService: Error executing statement:
org.apache.hive.service.cli.HiveSQLException: Error running query: java.lang.NoClassDefFoundError: scala/collection/Iterable
at org.apache.hive.service.cli.operation.SQLOperation.prepare(SQLOperation.java:225) ~[hive-service-2.1.1.jar:2.1.1]
at org.apache.hive.service.cli.operation.SQLOperation.runInternal(SQLOperation.java:276) ~[hive-service-2.1.1.jar:2.1.1]
at org.apache.hive.service.cli.operation.Operation.run(Operation.java:324) ~[hive-service-2.1.1.jar:2.1.1]
at org.apache.hive.service.cli.session.HiveSessionImpl.executeStatementInternal(HiveSessionImpl.java:499) ~[hive-service-2.1.1.jar:2.1.1]
at org.apache.hive.service.cli.session.HiveSessionImpl.executeStatementAsync(HiveSessionImpl.java:486) ~[hive-service-2.1.1.jar:2.1.1]
at org.apache.hive.service.cli.CLIService.executeStatementAsync(CLIService.java:295) ~[hive-service-2.1.1.jar:2.1.1]
at org.apache.hive.service.cli.thrift.ThriftCLIService.ExecuteStatement(ThriftCLIService.java:506) [hive-service-2.1.1.jar:2.1.1]
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[?:1.8.0_121]
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) ~[?:1.8.0_121]
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[?:1.8.0_121]
at java.lang.reflect.Method.invoke(Method.java:498) ~[?:1.8.0_121]
at org.apache.hive.jdbc.HiveConnection$SynchronizedHandler.invoke(HiveConnection.java:1412) [hive-jdbc-2.1.1.jar:2.1.1]
at com.sun.proxy.$Proxy35.ExecuteStatement(Unknown Source) [?:?]
at org.apache.hive.jdbc.HiveStatement.runAsyncOnServer(HiveStatement.java:308) [hive-jdbc-2.1.1.jar:2.1.1]
at org.apache.hive.jdbc.HiveStatement.execute(HiveStatement.java:250) [hive-jdbc-2.1.1.jar:2.1.1]
I have set the hive.execution.engine to spark and also am using a spark-enabled queue. Spark sql is able to access the hive tables - and so is beeline from a directly connected cluster machine.
But the hive cli seems to need additional steps. So far the following have been done:
** Copy the scala libraries to the $HIVE_HOME/libs dir (or we get ClassNotFoundException)
** Run the following at the start of the hive script (or in .hiverc)
set hive.execution.engine=spark;
set mapred.job.queue.name=root.spark.sbg.hos;
However the following error now happens Failed to create spark client.:
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Logging initialized using configuration in jar:file:/usr/local/Cellar/hive/2.1.1/libexec/lib/hive-common-2.1.1.jar!/hive-log4j2.properties Async: true
hive (default)> insert into sb.test2 values (1,'ab');
Query ID = sboesch_20171030175629_dc310c9a-519e-4f84-a632-f3a44f1df8c3
Total jobs = 3
Launching Job 1 out of 3
In order to change the average load for a reducer (in bytes):
set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
set mapreduce.job.reduces=<number>
Failed to execute spark task, with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create spark client.)'
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.spark.SparkTask
Has anyone managed to connect to spark backend for hive ? I am connecting via vanilla hive (not Cloudera or Hortonworks or MapR).
you have to start Hive metastore Server separately for accessing hive tables through spark.
Try hive --service metastore in a new Terminal you will get a response like Starting Hive Metastore Server
hive-site.xml
`<property>
<name>javax.jdo.option.ConnectionDriverName</name>
<value>com.mysql.jdbc.Driver</value>
</property>
<property>
<name>javax.jdo.option.ConnectionUserName</name>
<value>**mysql metastore username**</value>
</property>
<property>
<name>javax.jdo.option.ConnectionPassword</name>
<value>**mysql metastore DB password**</value>
</property>
<property>
<name>hive.querylog.location</name>
<value>/tmp/hivequerylogs/${user.name}</value>
</property>
<property>
<name>hive.aux.jars.path</name>
<value>file:///usr/local/hive/apache-hive-2.1.1-bin/lib/hive-hbase-handler-2.1.1.jar,file:///usr/local/hive/apache-hive-2.1.1-bin/lib/zookeeper-3.4.6.jar</value>
<description>A comma separated list (with no spaces) of the jar files required for Hive-HBase integration</description>
</property>
<property>
<name>hive.support.concurrency</name>
<value>false</value>
</property>
<property>
<name>hive.server2.enable.doAs</name>
<value>true</value>
</property>
<property>
<name>hive.server2.authentication</name>
<value>PAM</value>
</property>
<property>
<name>hive.server2.custom.authentication.class</name>
<value>org.apache.hive.service.auth.PamAuthenticationProvider</value>
</property>
<property>
<name>hive.server2.authentication.pam.services</name>
<value>sshd,sudo</value>
</property>
<property>
<name>hive.stats.dbclass</name>
<value>jdbc:mysql</value>
</property>
<property>
<name>hive.stats.jdbcdriver</name>
<value>com.mysql.jdbc.Driver</value>
</property>
<property>
<name>hive.session.history.enabled</name>
<value>true</value>
</property>
<property>
<name>hive.metastore.schema.verification</name>
<value>false</value>
</property>
<property>
<name>hive.optimize.sort.dynamic.partition</name>
<value>false</value>
</property>
<property>
<name>hive.optimize.insert.dest.volume</name>
<value>false</value>
</property>
<property>
<name>hive.exec.scratchdir</name>
<value>/tmp/hive/${user.name}</value>
<description>HDFS root scratch dir for Hive jobs which gets created with write all (733) permission. For each connecting user, an HDFS scratch dir: ${hive.exec.scratchdir}/<username> is created, with ${hive.scratch.dir.permission}.</description>
</property>
<property>
<name>datanucleus.fixedDatastore</name>
<value>true</value>
<description/>
</property>
<property>
<name>hive.metastore.warehouse.dir</name>
<value>/user/hive/warehouse</value>
<description>location of default database for the warehouse</description>
</property>
<property>
<name>datanucleus.autoCreateSchema</name>
<value>false</value>
<description>creates necessary schema on a startup if one doesn't exist. set this to false, after creating it once</description>
</property>
<property>
<name>datanucleus.schema.autoCreateAll</name>
<value>true</value>
</property>
<property>
<name>datanucleus.schema.validateConstraints</name>
<value>true</value>
</property>
<property>
<name>datanucleus.schema.validateColumns</name>
<value>true</value>
</property>
<property>
<name>datanucleus.schema.validateTables</name>
<value>true</value>
</property>
</configuration>`
This question already has answers here:
How to connect Spark SQL to remote Hive metastore (via thrift protocol) with no hive-site.xml?
(11 answers)
Closed 2 years ago.
The following are the versions that we have
Spark 1.6.1
Hadoop 2.6.2
Hive 1.1.0
I have the hive-site.xml in $SPARK_HOME/conf directory. The hive.metastore.uris property is also configured properly.
<property>
<name>javax.jdo.option.ConnectionURL</name>
<value>jdbc:mysql://host.domain.com:3306/metastore</value>
<description>metadata is stored in a MySQL server</description>
</property>
<property>
<name>javax.jdo.option.ConnectionDriverName</name>
<value>com.mysql.jdbc.Driver</value>
<description>MySQL JDBC driver class</description>
</property>
<property>
<name>javax.jdo.option.ConnectionUserName</name>
<value>hive</value>
<description>user name for connecting to mysql server </description>
</property>
<property>
<name>javax.jdo.option.ConnectionPassword</name>
<value>*****</value>
<description>password for connecting to mysql server </description>
</property>
<property>
<name>hive.metastore.uris</name>
<value>thrift://host.domain.com:9083</value>
<description>IP address (or fully-qualified domain name) and port of the metastore host</description>
</property>
Unfortunately Spark is creating a temp derby db without connecting to MySQL metastore
I need Spark to connect to MySQL metastore as that is the central store for all metadata. Please help
Regards
Bala
Can you try passing the hive-site.xml
(--files) with spark-submit when running in cluster mode?
I wrote a spark job which registers a temp table
and when I expose it via beeline (JDBC client)
$ ./bin/beeline
beeline> !connect jdbc:hive2://IP:10003 -n ram -p xxxx
0: jdbc:hive2://IP> show tables;
+---------------------------------------------+--------------+---------------------+
| tableName | isTemporary |
+---------------------------------------------+--------------+---------------------+
| f238 | true |
+---------------------------------------------+--------------+---------------------+
2 rows selected (0.309 seconds)
0: jdbc:hive2://IP>
I can view the table. When querying I get this error message
0: jdbc:hive2://IP> select * from f238;
Error: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.security.authorize.AuthorizationException): User: ram is not allowed to impersonate ram (state=,code=0)
0: jdbc:hive2://IP>
I have this in hive-site.xml,
<property>
<name>hive.metastore.sasl.enabled</name>
<value>false</value>
<description>If true, the metastore Thrift interface will be secured with SASL. Clients must authenticate with Kerberos.</description>
</property>
<property>
<name>hive.server2.enable.doAs</name>
<value>false</value>
</property>
<property>
<name>hive.server2.authentication</name>
<value>NONE</value>
</property>
I have this in core-site.xml,
<property>
<name>hadoop.proxyuser.hive.groups</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.hive.hosts</name>
<value>*</value>
</property>
full log
ERROR [pool-19-thread-2] thriftserver.SparkExecuteStatementOperation: Error running hive query:
org.apache.hive.service.cli.HiveSQLException: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.security.authorize.AuthorizationException): User: ram is not allowed to impersonate ram
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.runInternal(SparkExecuteStatementOperation.scala:259)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$1$$anon$2.run(SparkExecuteStatementOperation.scala:171)
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:1657)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$1.run(SparkExecuteStatementOperation.scala:182)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Any idea what configuration I am missing?
<property>
<name>hive.server2.enable.doAs</name>
<value>true</value>
</property>
Also if you want user ABC to impersonate all(*), add below properties to your core-site.xml
<property>
<name>hadoop.proxyuser.ABC.groups</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.ABC.hosts</name>
<value>*</value>
</property>
check that the owner of hiveserver2 process is 'hive'
, I have installed
1) scala-2.10.3
2) spark-1.0.0
Changed spark-env.sh with below variables
export SCALA_HOME=$HOME/scala-2.10.3
export SPARK_WORKER_MEMORY=16g
I can see Spark master.
3) shark-0.9.1-bin-hadoop1
Changed shark-env.sh with below variables
export SHARK_MASTER_MEM=1g
SPARK_JAVA_OPTS=" -Dspark.local.dir=/tmp "
SPARK_JAVA_OPTS+="-Dspark.kryoserializer.buffer.mb=10 "
SPARK_JAVA_OPTS+="-verbose:gc -XX:-PrintGCDetails -XX:+PrintGCTimeStamps "
export SPARK_JAVA_OPTS
export HIVE_HOME=/usr/share/dse/hive
export HIVE_CONF_DIR="/etc/dse/hive"
export SPARK_HOME=/home/ubuntu/spark-1.0.0
export SPARK_MEM=16g
source $SPARK_HOME/conf/spark-env.sh
4) In DSE, Hive version is Hive 0.11
Existing Hive-site.xml is
<configuration>
<!-- Hive Execution Parameters -->
<property>
<name>hive.exec.mode.local.auto</name>
<value>false</value>
<description>Let hive determine whether to run in local mode automatically</description>
</property>
<property>
<name>hive.metastore.warehouse.dir</name>
<value>cfs:///user/hive/warehouse</value>
<description>location of default database for the warehouse</description>
</property>
<property>
<name>hive.hwi.war.file</name>
<value>lib/hive-hwi.war</value>
<description>This sets the path to the HWI war file, relative to ${HIVE_HOME}</description>
</property>
<property>
<name>hive.metastore.rawstore.impl</name>
<value>com.datastax.bdp.hadoop.hive.metastore.CassandraHiveMetaStore</value>
<description>Use the Apache Cassandra Hive RawStore implementation</description>
</property>
<property>
<name>hadoop.bin.path</name>
<value>${dse.bin}/dse hadoop</value>
</property>
<!-- Set this to true to enable auto-creation of Cassandra keyspaces as Hive Databases -->
<property>
<name>cassandra.autoCreateHiveSchema</name>
<value>true</value>
</property>
</configuration>
5) while running Shark shell getting error:
Unable to instantiate Org.apache.hadoop.hive.metastore.HiveMetaStoreClient
And
6) While running shark shell with -skipRddReload - I'm able to get Shark shell but not able to connect hive and not able execute any commands.
shark> DESCRIVE mykeyspace;
and getting error message:
FAILED: Error in metastore: java.lang.RuntimeException: Unable to instantiate org.apache.haddop.hive.metastore.HiveMataStoreClient.
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.q1.exec.DDLTask.
Please provide details how to configure spark/shark on Datastax enterprise (Cassandra).