Deploying Kyuubi - Deploy Kyuubi engines on YARN - 《Apache Kyuubi 1.9.1》

Deploy Kyuubi Spark Engine on YARN
Deploy Kyuubi Flink Engine on YARN
Deploy Kyuubi Hive Engine on YARN
- Requirements
- Configurations
  - Environment
  - Required Environment Variable

Deploy Kyuubi Spark Engine on YARN

Requirements

To deploy Kyuubi’s Spark SQL engines on YARN, you’d better have cognition upon the following things.

Knowing the basics about Running Spark on YARN
A binary distribution of Spark which is built with YARN support
- You can use the built-in Spark distribution
- You can get it from Spark official website directly
- You can Build Spark with -Pyarn maven option
An active Apache Hadoop YARN cluster
An active Apache Hadoop HDFS cluster
Setup Hadoop client configurations at the machine the Kyuubi server locates

Configurations

Environment

Either HADOOP_CONF_DIR or YARN_CONF_DIR is configured and points to the Hadoop client configurations directory, usually, $HADOOP_HOME/etc/hadoop.

If the HADOOP_CONF_DIR points the YARN and HDFS cluster correctly, you should be able to run the SparkPi example on YARN.

$ HADOOP_CONF_DIR=/path/to/hadoop/conf $SPARK_HOME/bin/spark-submit \
    --class org.apache.spark.examples.SparkPi \
    --master yarn \
    --queue thequeue \
    $SPARK_HOME/examples/jars/spark-examples*.jar \
    10

If the SparkPi passes, configure it in $KYUUBI_HOME/conf/kyuubi-env.sh or $SPARK_HOME/conf/spark-env.sh, e.g.

$ echo "export HADOOP_CONF_DIR=/path/to/hadoop/conf" >> $KYUUBI_HOME/conf/kyuubi-env.sh

Spark Properties

These properties are defined by Spark and Kyuubi will pass them to spark-submit to create Spark applications.

Note: None of these would take effect if the application for a particular user already exists.

Specify it in the JDBC connection URL, e.g. jdbc:hive2://localhost:10009/;#spark.master=yarn;spark.yarn.queue=thequeue
Specify it in $KYUUBI_HOME/conf/kyuubi-defaults.conf
Specify it in $SPARK_HOME/conf/spark-defaults.conf

Note: The priority goes down from top to bottom.

Master

Setting spark.master=yarn tells Kyuubi to submit Spark SQL engine applications to the YARN cluster manager.

Queue

Set spark.yarn.queue=thequeue in the JDBC connection string to tell Kyuubi to use the QUEUE in the YARN cluster, otherwise, the QUEUE configured at Kyuubi server side will be used as default.

Sizing

Pass the configurations below through the JDBC connection string to set how many instances of Spark executor will be used and how many cpus and memory will Spark driver, ApplicationMaster and each executor take.

Name	Default	Meaning
spark.executor.instances	1	The number of executors for static allocation
spark.executor.cores	1	The number of cores to use on each executor
spark.yarn.am.memory	512m	Amount of memory to use for the YARN Application Master in client mode
spark.yarn.am.memoryOverhead	amMemory * 0.10, with minimum of 384	Amount of non-heap memory to be allocated per am process in client mode
spark.driver.memory	1g	Amount of memory to use for the driver process
spark.driver.memoryOverhead	driverMemory * 0.10, with minimum of 384	Amount of non-heap memory to be allocated per driver process in cluster mode
spark.executor.memory	1g	Amount of memory to use for the executor process
spark.executor.memoryOverhead	executorMemory * 0.10, with minimum of 384	Amount of additional memory to be allocated per executor process. This is memory that accounts for things like VM overheads, interned strings other native overheads, etc

It is recommended to use Dynamic Allocation with Kyuubi, since the SQL engine will be long-running for a period, execute user’s queries from clients periodically, and the demand for computing resources is not the same for those queries. It is better for Spark to release some executors when either the query is lightweight, or the SQL engine is being idled.

Tuning

You can specify spark.yarn.archive or spark.yarn.jars to point to a world-readable location that contains Spark jars on HDFS, which allows YARN to cache it on nodes so that it doesn’t need to be distributed each time an application runs.

Others

Please refer to Spark properties to check other acceptable configs.

Kerberos

Kyuubi currently does not support Spark’s YARN-specific Kerberos Configuration, so spark.kerberos.keytab and spark.kerberos.principal should not use now.

Instead, you can schedule a periodically kinit process via crontab task on the local machine that hosts Kyuubi server or simply use Kyuubi Kinit.

Deploy Kyuubi Flink Engine on YARN

Requirements

To deploy Kyuubi’s Flink SQL engines on YARN, you’d better have cognition upon the following things.

Knowing the basics about Running Flink on YARN
A binary distribution of Flink which is built with YARN support
- Download a recent Flink distribution from the Flink official website and unpack it
An active Apache Hadoop YARN cluster
- Make sure your YARN cluster is ready for accepting Flink applications by running yarn top. It should show no error messages
An active Object Storage cluster, e.g. HDFS, S3 and Minio etc.
Setup Hadoop client configurations at the machine the Kyuubi server locates

Flink Deployment Modes

Currently, Flink supports two deployment modes on YARN: YARN Application Mode and YARN Session Mode.

YARN Application Mode: In this mode, Kyuubi starts a dedicated Flink application cluster and runs the SQL engine on it.
YARN Session Mode: In this mode, Kyuubi starts the Flink SQL engine locally and connects to a running Flink YARN session cluster.

As Kyuubi has to know the deployment mode before starting the SQL engine, it’s required to specify the deployment mode in Kyuubi configuration.

# candidates: yarn-application, yarn-session
flink.execution.target=yarn-application

YARN Application Mode

Flink Configurations

Since the Flink SQL engine runs inside the JobManager, it’s recommended to tune the resource configurations of the JobManager based on your workload.

The related Flink configurations are listed below (see more details at Flink Configuration):

Name	Default	Meaning
yarn.appmaster.vcores	1	The number of virtual cores (vcores) used by the JobManager (YARN application master).
jobmanager.memory.process.size	(none)	Total size of the memory of the JobManager process.

Note that Flink application mode doesn’t support HA for multiple jobs as for now, this also applies to Kyuubi’s Flink SQL engine. If JobManager fails and restarts, the submitted jobs would not be recovered and should be re-submitted.

Environment

Either HADOOP_CONF_DIR or YARN_CONF_DIR is configured and points to the Hadoop client configurations directory, usually, $HADOOP_HOME/etc/hadoop.

You could verify your setup by the following command:

# we assume to be in the root directory of 
# the unzipped Flink distribution
# (0) export HADOOP_CLASSPATH
export HADOOP_CLASSPATH=`hadoop classpath`
# (1) submit a Flink job and ensure it runs successfully
./bin/flink run -m yarn-cluster ./examples/streaming/WordCount.jar

YARN Session Mode

Flink Configurations

execution.target: yarn-session
# YARN Session Cluster application id.
yarn.application.id: application_00000000XX_00XX

Environment

Either HADOOP_CONF_DIR or YARN_CONF_DIR is configured and points to the Hadoop client configurations directory, usually, $HADOOP_HOME/etc/hadoop.

If the HADOOP_CONF_DIR points to the YARN and HDFS cluster correctly, and the HADOOP_CLASSPATH environment variable is set, you can launch a Flink on YARN session, and submit an example job:

# we assume to be in the root directory of 
# the unzipped Flink distribution
# (0) export HADOOP_CLASSPATH
export HADOOP_CLASSPATH=`hadoop classpath`
# (1) Start YARN Session
./bin/yarn-session.sh --detached
# (2) You can now access the Flink Web Interface through the
# URL printed in the last lines of the command output, or through
# the YARN ResourceManager web UI.
# (3) Submit example job
./bin/flink run ./examples/streaming/TopSpeedWindowing.jar
# (4) Stop YARN session (replace the application id based 
# on the output of the yarn-session.sh command)
echo "stop" | ./bin/yarn-session.sh -id application_XXXXX_XXX

If the TopSpeedWindowing passes, configure it in $KYUUBI_HOME/conf/kyuubi-env.sh

$ echo "export HADOOP_CONF_DIR=/path/to/hadoop/conf" >> $KYUUBI_HOME/conf/kyuubi-env.sh

Required Environment Variable

The FLINK_HADOOP_CLASSPATH is required, too.

For users who are using Hadoop 3.x, Hadoop shaded client is recommended instead of Hadoop vanilla jars. For users who are using Hadoop 2.x, FLINK_HADOOP_CLASSPATH should be set to hadoop classpath to use Hadoop vanilla jars. For users which does not use Hadoop services, e.g. HDFS, YARN at all, Hadoop client jars is also required, and recommend to use Hadoop shaded client as Hadoop 3.x’s users do.

See HADOOP-11656 for details of Hadoop shaded client.

To use Hadoop shaded client, please configure $KYUUBI_HOME/conf/kyuubi-env.sh as follows:

$ echo "export FLINK_HADOOP_CLASSPATH=/path/to/hadoop-client-runtime-3.3.2.jar:/path/to/hadoop-client-api-3.3.2.jar" >> $KYUUBI_HOME/conf/kyuubi-env.sh

To use Hadoop vanilla jars, please configure $KYUUBI_HOME/conf/kyuubi-env.sh as follows:

$ echo "export FLINK_HADOOP_CLASSPATH=`hadoop classpath`" >> $KYUUBI_HOME/conf/kyuubi-env.sh

Kerberos

With regard to YARN application mode, Kerberos is supported natively by Flink, see Flink Kerberos Configuration for details.

With regard to YARN session mode, security.kerberos.login.keytab and security.kerberos.login.principal are not effective, as Kyuubi Flink SQL engine mainly relies on Flink SQL client which currently does not support Flink Kerberos Configuration,

As a workaround, you can schedule a periodically kinit process via crontab task on the local machine that hosts Kyuubi server or simply use Kyuubi Kinit.

Deploy Kyuubi Hive Engine on YARN

Requirements

To deploy Kyuubi’s Hive SQL engines on YARN, you’d better have cognition upon the following things.

Knowing the basics about Running Hive on YARN
A binary distribution of Hive
- You can use the built-in Hive distribution
- Download a recent Hive distribution from the Hive official website and unpack it
- You can Build Hive
An active Apache Hadoop YARN cluster
- Make sure your YARN cluster is ready for accepting Hive applications by running yarn top. It should show no error messages
An active Apache Hadoop HDFS cluster
Setup Hadoop client configurations at the machine the Kyuubi server locates
An active Hive Metastore Service

Configurations

Environment

Either HADOOP_CONF_DIR or YARN_CONF_DIR is configured and points to the Hadoop client configurations directory, usually, $HADOOP_HOME/etc/hadoop.

If the HADOOP_CONF_DIR points to the YARN and HDFS cluster correctly, you should be able to run the Hive SQL example on YARN.

$ $HIVE_HOME/bin/hiveserver2
# In another terminal
$ $HIVE_HOME/bin/beeline -u 'jdbc:hive2://localhost:10000/default'
0: jdbc:hive2://localhost:10000/default> CREATE TABLE pokes (foo INT, bar STRING);
0: jdbc:hive2://localhost:10000/default> INSERT INTO TABLE pokes VALUES (1, 'hello');

If the Hive SQL passes and there is a job in YARN Web UI, it indicates the hive environment is good.

Required Environment Variable

The HIVE_HADOOP_CLASSPATH is required, too. It should contain commons-collections-*.jar, hadoop-client-runtime-*.jar, hadoop-client-api-*.jar and htrace-core4-*.jar. All four jars are in the HADOOP_HOME.

For example, in Hadoop 3.1.0 version, the following is their location.

${HADOOP_HOME}/share/hadoop/common/lib/commons-collections-3.2.2.jar
${HADOOP_HOME}/share/hadoop/client/hadoop-client-runtime-3.1.0.jar
${HADOOP_HOME}/share/hadoop/client/hadoop-client-api-3.1.0.jar
${HADOOP_HOME}/share/hadoop/common/lib/htrace-core4-4.1.0-incubating.jar

Configure them in $KYUUBI_HOME/conf/kyuubi-env.sh or $HIVE_HOME/conf/hive-env.sh, e.g.

$ echo "export HADOOP_CONF_DIR=/path/to/hadoop/conf" >> $KYUUBI_HOME/conf/kyuubi-env.sh
$ echo "export HIVE_HADOOP_CLASSPATH=${HADOOP_HOME}/share/hadoop/common/lib/commons-collections-3.2.2.jar:${HADOOP_HOME}/share/hadoop/client/hadoop-client-runtime-3.1.0.jar:${HADOOP_HOME}/share/hadoop/client/hadoop-client-api-3.1.0.jar:${HADOOP_HOME}/share/hadoop/common/lib/htrace-core4-4.1.0-incubating.jar" >> $KYUUBI_HOME/conf/kyuubi-env.sh