<!--
- Licensed to the Apache Software Foundation (ASF) under one or more
- contributor license agreements.  See the NOTICE file distributed with
- this work for additional information regarding copyright ownership.
- The ASF licenses this file to You under the Apache License, Version 2.0
- (the "License"); you may not use this file except in compliance with
- the License.  You may obtain a copy of the License at
-
-   http://www.apache.org/licenses/LICENSE-2.0
-
- Unless required by applicable law or agreed to in writing, software
- distributed under the License is distributed on an "AS IS" BASIS,
- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- See the License for the specific language governing permissions and
- limitations under the License.
-->

# Deploy Kyuubi engines on YARN

## 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](https://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](https://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:kyuubi://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](https://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 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](https://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](https://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](../configuration/settings.md#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](https://nightlies.apache.org/flink/flink-docs-stable/docs/deployment/resource-providers/yarn)
- A binary distribution of Flink which is built with YARN support
  - Download a recent Flink distribution from the [Flink official website](https://flink.apache.org/downloads.html) and unpack it
- An active [Apache Hadoop YARN](https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html) 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](https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html), S3 and [Minio](https://min.io/) 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](https://nightlies.apache.org/flink/flink-docs-release-1.17/docs/deployment/resource-providers/yarn/#application-mode) and [YARN Session Mode](https://nightlies.apache.org/flink/flink-docs-release-1.17/docs/deployment/resource-providers/yarn/#application-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.

```properties
# 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](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/config/#yarn)):

|              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:

```bash
# 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

```bash
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:

```bash
# 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`

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

#### Required Environment Variable

The `FLINK_HADOOP_CLASSPATH` is required unless the necessary Hadoop client jars (such as `hadoop-client` or
`flink-shaded-hadoop`) have already been placed in the Flink lib directory (`$FLINK_HOME/lib`).

If the jars are not present in `$FLINK_HOME/lib`, you must set `FLINK_HADOOP_CLASSPATH` to include the appropriate
Hadoop client jars.

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 who 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](https://issues.apache.org/jira/browse/HADOOP-11656) for details of Hadoop shaded client.

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

```bash
$ 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:

```bash
$ 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](https://nightlies.apache.org/flink/flink-docs-stable/docs/deployment/config/#security-kerberos-login-keytab) 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](https://nightlies.apache.org/flink/flink-docs-stable/docs/deployment/config/#security-kerberos-login-keytab),

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](../configuration/settings.md#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](https://cwiki.apache.org/confluence/display/Hive/GettingStarted)
- A binary distribution of Hive
  - You can use the built-in Hive distribution
  - Download a recent Hive distribution from the [Hive official website](https://hive.apache.org/downloads.html) and unpack it
  - You can [Build Hive](https://cwiki.apache.org/confluence/display/Hive//GettingStarted#GettingStarted-BuildingHivefromSource)
- An active [Apache Hadoop YARN](https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html) 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](https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) cluster
- Setup Hadoop client configurations at the machine the Kyuubi server locates
- An active [Hive Metastore Service](https://cwiki.apache.org/confluence/display/hive/design#Design-Metastore)

### 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.

```bash
$ $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.

```bash
$ 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
```

