../_images/kyuubi_logo.png

1. Deploy Kyuubi engines on Yarn¶

1.1. Requirements¶

When you want 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

1.2. Configurations¶

1.2.1. 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

1.2.2. 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 aperiodically, 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.

1.3. 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