kyuubi/docs/deployment/on_yarn.md

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# Deploy Kyuubi engines on Yarn

## 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](http://spark.apache.org/docs/latest/running-on-yarn.html)
- 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](https://spark.apache.org/downloads.html) directly
  - You can [Build Spark](http://spark.apache.org/docs/latest/building-spark.html#specifying-the-hadoop-version-and-enabling-yarn) with `-Pyarn` maven option
- An active [Apache Hadoop YARN](https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html) 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.
```bash
$ 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.

```bash
$ 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](http://spark.apache.org/docs/3.0.1/configuration.html#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](http://spark.apache.org/docs/latest/running-on-yarn.html#spark-properties) to check other acceptable configs.


## Kerberos

Kyuubi currently does not support Spark's [YARN-specific Kerberos Configuration](http://spark.apache.org/docs/3.0.1/running-on-yarn.html#kerberos),
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](settings.html#kinit)