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 name | Environment variable content | Remarks |
---|---|---|
JAVA_HOME | JDK installation path | Required |
HADOOP_HOME | Hadoop installation path | Required |
HADOOP_CONF_DIR | Hadoop configuration path | required |
HIVE_CONF_DIR | Hive configuration path | required |
SPARK_HOME | Spark installation path | Required |
SPARK_CONF_DIR | Spark configuration path | Required |
python | python | It 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 3.2.1
/_/
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 Spark3.2.1
. 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-3.2.1 -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-3.2.1 -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-3.2.1"); // 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
You can also submit scala and python code:
//scala
labels.put(LabelKeyConstant.CODE_TYPE_KEY, "scala");
code:
val df=spark.sql("show tables")
show(df)
//pyspark
/labels.put(LabelKeyConstant.CODE_TYPE_KEY, "py");
code:
df=spark.sql("show tables")
show(df)
3.3 Submitting tasks by submitting the jar package
Through OnceEngineConn
submit tasks (through the spark-submit submit jar package mission), submission for reference org.apache.linkis.com putation.Client.SparkOnceJobTest
.
public class SparkOnceJobTest {
public static void main(String[] args) {
LinkisJobClient.config().setDefaultServerUrl("http://127.0.0.1:9001");
String submitUser = "linkis";
String engineType = "spark";
SubmittableSimpleOnceJob onceJob =
// region
LinkisJobClient.once().simple().builder()
.setCreateService("Spark-Test")
.setMaxSubmitTime(300000)
.setDescription("SparkTestDescription")
.addExecuteUser(submitUser)
.addJobContent("runType", "jar")
.addJobContent("spark.app.main.class", "org.apache.spark.examples.JavaWordCount")
// Parameters obtained from the submitted jar package
.addJobContent("spark.app.args", "hdfs:///tmp/test_word_count.txt") // WordCount test file
.addLabel("engineType", engineType + "-2.4.7")
.addLabel("userCreator", submitUser + "-IDE")
.addLabel("engineConnMode", "once")
.addStartupParam("spark.app.name", "spark-submit-jar-test-linkis") // Application Name on yarn
.addStartupParam("spark.executor.memory", "1g")
.addStartupParam("spark.driver.memory", "1g")
.addStartupParam("spark.executor.cores", "1")
.addStartupParam("spark.executor.instance", "1")
.addStartupParam("spark.app.resource", "hdfs:///tmp/spark/spark-examples_2.11-2.3.0.2.6.5.0-292.jar")
.addSource("jobName", "OnceJobTest")
.build();
// endregion
onceJob.submit();
onceJob.waitForCompleted(); //A temporary network interruption may cause an exception. It is recommended to modify the SDK later. If the SDK is in use at this stage, exception handling is required.
// Temporary network failure will cause exceptions. It is recommended to modify the SDK later. For use at this stage, exception handling is required
onceJob.waitForCompleted();
}
}
3.4 Submitting tasks with Restful API
Scripts type includes sql
、scala
、python
、data_calc(content type is json)
.
POST /api/rest_j/v1/entrance/submit
Content-Type: application/json
Token-Code: dss-AUTH
Token-User: linkis
{
"executionContent": {
// script content, type: sql, python, scala, json
"code": "show databases",
// script type: sql, py(pyspark), scala, data_calc(json)
"runType": "sql"
},
"params": {
"variable": {
},
"configuration": {
// spark startup parameters, not required
"startup": {
"spark.executor.memory": "1g",
"spark.driver.memory": "1g",
"spark.executor.cores": "1",
"spark.executor.instances": 1
}
}
},
"source": {
// not required, file:/// or hdfs:///
"scriptPath": "file:///tmp/hadoop/test.sql"
},
"labels": {
// pattern:engineType-version
"engineType": "spark-3.2.1",
// userCreator: linkis is username。IDE is system that be configed in Linkis。
"userCreator": "linkis-IDE"
}
}
4. Engine configuration instructions
4.1 Default Configuration Description
Configuration | Default | Required | Description |
---|---|---|---|
wds.linkis.rm.instance | 10 | No | Maximum number of concurrent engines |
spark.executor.cores | 1 | No | Number of spark executor cores |
spark.driver.memory | 1g | no | maximum concurrent number of spark executor instances |
spark.executor.memory | 1g | No | spark executor memory size |
wds.linkis.engineconn.max.free.time | 1h | No | Engine idle exit time |
spark.python.version | python2 | no | python 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.
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.
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-3.2.1 -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-3.2.1",
"userCreator": "hadoop-IDE"
}
}
4.4 Engine related data sheet
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-3.2.1
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-3.2.1";
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);