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Version: 1.3.1

Spark Engine

This article mainly introduces the installation, use and configuration of the Spark engine plugin in Linkis.

1. Preliminary work

1.1 Engine installation

If you wish to use the spark engine on your server, you need to ensure that the following environment variables are set correctly and that the engine's starting user has these environment variables.

It is strongly recommended that you check these environment variables for the executing user before executing a spark job.

Environment variable nameEnvironment variable contentRemarks
JAVA_HOMEJDK installation pathRequired
HADOOP_HOMEHadoop installation pathRequired
HADOOP_CONF_DIRHadoop configuration pathrequired
HIVE_CONF_DIRHive configuration pathrequired
SPARK_HOMESpark installation pathRequired
SPARK_CONF_DIRSpark configuration pathRequired
pythonpythonIt is recommended to use anaconda's python as the default python

1.2 Environment verification

Verify that Spark is successfully installed by pyspark

pyspark

#After entering the pyspark virtual environment, the spark logo appears, indicating that the environment is successfully installed
Welcome to
______
/__/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 2.4.3
/_/

Using Python version 2.7.13 (default, Sep 30 2017 18:12:43)
SparkSession available as 'spark'.

2. Engine plugin installation default engine

The Spark engine plugin is included in the binary installation package released by linkis by default, and users do not need to install it additionally.

In theory Linkis supports all versions of spark2.x and above. The default supported version is Spark2.4.3. If you want to use another version of spark, such as spark2.1.0, you just need to modify the version of the plugin spark and compile it. Specifically, you can find the linkis-engineplugin-spark module, change the value of the <spark.version> tag in the maven dependency to 2.1.0, and then compile this module separately.

EngineConnPlugin engine plugin installation

3. Using the spark engine

3.1 Submitting tasks via Linkis-cli

# codeType correspondence py-->pyspark sql-->sparkSQL scala-->Spark scala
sh ./bin/linkis-cli -engineType spark-2.4.3 -codeType sql -code "show databases" -submitUser hadoop -proxyUser hadoop

# You can specify the yarn queue in the submission parameter by -confMap wds.linkis.yarnqueue=dws
sh ./bin/linkis-cli -engineType spark-2.4.3 -codeType sql -confMap wds.linkis.yarnqueue=dws -code "show databases" -submitUser hadoop -proxyUser hadoop

More Linkis-Cli command parameter reference: Linkis-Cli usage

3.2 Submitting tasks through Linkis SDK

Linkis provides SDK of Java and Scala to submit tasks to Linkis server. For details, please refer to JAVA SDK Manual. For Spark tasks you only need to modify the EngineConnType and CodeType parameters in Demo:

Map<String, Object> labels = new HashMap<String, Object>();
labels.put(LabelKeyConstant.ENGINE_TYPE_KEY, "spark-2.4.3"); // required engineType Label
labels.put(LabelKeyConstant.USER_CREATOR_TYPE_KEY, "hadoop-IDE");// required execute user and creator
labels.put(LabelKeyConstant.CODE_TYPE_KEY, "sql"); // required codeType py,sql,scala

4. Engine configuration instructions

4.1 Default Configuration Description

ConfigurationDefaultRequiredDescription
wds.linkis.rm.instance10NoMaximum number of concurrent engines
spark.executor.cores1NoNumber of spark executor cores
spark.driver.memory1gnomaximum concurrent number of spark executor instances
spark.executor.memory1gNospark executor memory size
wds.linkis.engineconn.max.free.time1hNoEngine idle exit time
spark.python.versionpython2nopython version

4.2 Queue resource configuration

Because the execution of spark requires queue resources, you need to set up a queue that you can execute.

yarn

4.3 Configuration modification

If the default parameters are not satisfied, there are the following ways to configure some basic parameters

4.3.1 Management Console Configuration

Users can customize settings, such as the number of spark sessions executor and executor memory. These parameters are for users to set their own spark parameters more freely, and other spark parameters can also be modified, such as the python version of pyspark, etc. spark

Note: After modifying the configuration under the IDE tag, you need to specify -creator IDE to take effect (other tags are similar), such as:

sh ./bin/linkis-cli -creator IDE \
-engineType spark-2.4.3 -codeType sql \
-code "show databases" \
-submitUser hadoop -proxyUser hadoop

4.3.2 Task interface configuration

Submit the task interface, configure it through the parameter params.configuration.runtime

Example of http request parameters
{
"executionContent": {"code": "show databases;", "runType": "sql"},
"params": {
"variable": {},
"configuration": {
"runtime": {
"wds.linkis.rm.instance":"10"
}
}
},
"labels": {
"engineType": "spark-2.4.3",
"userCreator": "hadoop-IDE"
}
}

Linkis is managed through the engine tag, and the data table information involved is shown below.

linkis_ps_configuration_config_key: Insert the key and default values ​​​​of the configuration parameters of the engine
linkis_cg_manager_label: insert engine label such as: spark-2.4.3
linkis_ps_configuration_category: The directory association relationship of the insertion engine
linkis_ps_configuration_config_value: The configuration that the insertion engine needs to display
linkis_ps_configuration_key_engine_relation: The relationship between the configuration item and the engine

The initial data in the table related to the spark engine is as follows

-- set variable
SET @SPARK_LABEL="spark-2.4.3";
SET @SPARK_ALL=CONCAT('*-*,',@SPARK_LABEL);
SET @SPARK_IDE=CONCAT('*-IDE,',@SPARK_LABEL);

-- engine label
insert into `linkis_cg_manager_label` (`label_key`, `label_value`, `label_feature`, `label_value_size`, `update_time`, `create_time`) VALUES ('combined_userCreator_engineType', @SPARK_ALL, 'OPTIONAL', 2, now(), now());
insert into `linkis_cg_manager_label` (`label_key`, `label_value`, `label_feature`, `label_value_size`, `update_time`, `create_time`) VALUES ('combined_userCreator_engineType', @SPARK_IDE, 'OPTIONAL', 2, now(), now());

select @label_id := id from linkis_cg_manager_label where `label_value` = @SPARK_IDE;
insert into linkis_ps_configuration_category (`label_id`, `level`) VALUES (@label_id, 2);

-- configuration key
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('wds.linkis.rm.instance', 'Range: 1-20, unit: each', 'Maximum concurrent number of spark engine', '10', 'NumInterval', '[1,20]', '0 ', '0', '1', 'queue resources', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.executor.instances', 'value range: 1-40, unit: individual', 'maximum concurrent number of spark executor instances', '1', 'NumInterval', '[1,40]', '0', '0', '2', 'spark resource settings', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.executor.cores', 'Value range: 1-8, unit: number', 'Number of spark executor cores', '1', 'NumInterval', '[1,8]', ' 0', '0', '1','spark resource settings', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.executor.memory', 'value range: 1-15, unit: G', 'spark executor memory size', '1g', 'Regex', '^([1-9]|1 [0-5])(G|g)$', '0', '0', '3', 'spark resource settings', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.driver.cores', 'Value range: only 1, unit: number', 'Number of spark driver cores', '1', 'NumInterval', '[1,1]', '0 ', '1', '1', 'spark resource settings', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.driver.memory', 'value range: 1-15, unit: G', 'spark driver memory size','1g', 'Regex', '^([1-9]|1[ 0-5])(G|g)$', '0', '0', '1', 'spark resource settings', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('wds.linkis.engineconn.max.free.time', 'Value range: 3m,15m,30m,1h,2h', 'Engine idle exit time','1h', 'OFT', '[\ "1h\",\"2h\",\"30m\",\"15m\",\"3m\"]', '0', '0', '1', 'spark engine settings', ' spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.tispark.pd.addresses', NULL, NULL, 'pd0:2379', 'None', NULL, '0', '0', '1', 'tidb设置', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.tispark.tidb.addr', NULL, NULL, 'tidb', 'None', NULL, '0', '0', '1', 'tidb设置', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.tispark.tidb.password', NULL, NULL, NULL, 'None', NULL, '0', '0', '1', 'tidb设置', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.tispark.tidb.port', NULL, NULL, '4000', 'None', NULL, '0', '0', '1', 'tidb设置', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.tispark.tidb.user', NULL, NULL, 'root', 'None', NULL, '0', '0', '1', 'tidb设置', 'spark');
INSERT INTO `linkis_ps_configuration_config_key` (`key`, `description`, `name`, `default_value`, `validate_type`, `validate_range`, `is_hidden`, `is_advanced`, `level`, `treeName`, `engine_conn_type`) VALUES ('spark.python.version', 'Value range: python2,python3', 'python version','python2', 'OFT', '[\"python3\",\"python2\"]', ' 0', '0', '1', 'spark engine settings', 'spark');

-- key engine relation
insert into `linkis_ps_configuration_key_engine_relation` (`config_key_id`, `engine_type_label_id`)
(select config.id as `config_key_id`, label.id AS `engine_type_label_id` FROM linkis_ps_configuration_config_key config
INNER JOIN linkis_cg_manager_label label ON config.engine_conn_type = 'spark' and label.label_value = @SPARK_ALL);

-- engine default configuration
insert into `linkis_ps_configuration_config_value` (`config_key_id`, `config_value`, `config_label_id`)
(select `relation`.`config_key_id` AS `config_key_id`, '' AS `config_value`, `relation`.`engine_type_label_id` AS `config_label_id` FROM linkis_ps_configuration_key_engine_relation relation
INNER JOIN linkis_cg_manager_label label ON relation.engine_type_label_id = label.id AND label.label_value = @SPARK_ALL);