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Technology sharing | introduction to linkis parameters
2022-07-01 11:02:00 【Wechat open source】

Introduction : This paper mainly focuses on Linkis The parameter system of , Include Linkis Server parameters 、 Client parameters 、 Introduction of management console parameters .
Linkis Parameters are mainly divided into the following three parts :
Linkis Server parameters , It mainly includes Linkis Its own parameters and Spring Parameters of
Linkis SDK、Restful Wait for the client side to call the submitted parameters
Linkis Management console parameters
├──conf The configuration directory│ ├── application-eureka.yml│ ├── application-linkis.yml│ ├── linkis-cg-engineconnmanager.properties│ ├── linkis-cg-engineplugin.properties│ ├── linkis-cg-entrance.properties│ ├── linkis-cg-linkismanager.properties│ ├── linkis-mg-gateway.properties│ ├── linkis-ps-cs.properties│ ├── linkis-ps-data-source-manager.properties│ ├── linkis-ps-metadatamanager.properties│ ├── linkis-ps-publicservice.properties│ ├── linkis.properties│ ├── log4j2-console.xml│ ├── log4j2.xml
It is recommended that general parameters be placed in the main configuration file , The personality profile is placed in the service profile
Linkis Service is based on SpringBoot Applied ,Spring Relevant parameters are supported in application-linkis.yml Set it up , Also support in linkis Configure in the configuration file . stay linkis The configuration in the configuration file needs to be added spring. The prefix of . as follows :
spring port defaultserver.port=9102in linkis conf need spring prefixspring.server.port=9102
{"executionContent": {"code": "show tables", "runType": "sql"},"params": { // Submit parameters"variable":{ // Custom variables needed in the code"k1":"v1"},"configuration":{"special":{ // Special configuration parameters Such as log path , Result set path, etc"k2":"v2"},"runtime":{ // Runtime parameters , Such as JDBC Database connection parameters of the engine ,presto Data source parameters of the engine"k3":"v3"},"startup":{ // Launch parameters , If you start EC Memory parameters ,spark Engine parameters 、hive Engine parameters, etc"k4":"v4" Such as :spark.executor.memory:5G Set up Spark Actuator memory , Bottom Spark、hive Equal engine parameters keyName It is consistent with the native parameters}}},"labels": { // Tag parameters , Support setting engine version 、 Users and Applications"engineType": "spark-2.4.3","userCreator": "hadoop-IDE"}}
notes : Comments on methodsJobSubmitAction jobSubmitAction =JobSubmitAction.builder().addExecuteCode(code)// Launch parameters , If you start EC Memory parameters ,spark Engine parameters 、hive Engine parameters, etc , Such as :spark.executor.memory:5G Set up Spark Actuator memory , Bottom Spark、hive Equal engine parameters keyName It is consistent with the native parameters.setStartupParams(startupMap)// Runtime parameters , Such as JDBC Database connection parameters of the engine ,presto Data source parameters of the engine.setRuntimeParams(runTimeMap)// Custom variables needed in the code.setVariableMap(varMap)// Tag parameters , Support setting engine version 、 Users and Applications.setLabels(labels)//submit user.setUser(user)// execute user.addExecuteUser(user).build();
linkis-cli -runtieMap key1=value -runtieMap key2=value-labelMap key1=value-varMap key1=value-startUpMap key1=value
Map<String, Object> labels = new HashMap<String, Object>();labels.put(LabelKeyConstant.ENGINE_TYPE_KEY, "spark-2.4.3"); // Specify the engine type and versionlabels.put(LabelKeyConstant.USER_CREATOR_TYPE_KEY, user + "-IDE");// Specify the user running and your APPNamelabels.put(LabelKeyConstant.CODE_TYPE_KEY, "sql"); // Specify the type of script to run :spark Support :sql、scala、py;Hive:hql;shell:sh;python:python;presto:psqllabels.put(LabelKeyConstant.JOB_RUNNING_TIMEOUT_KEY, "10");//job function 10s Failed to complete automatic initiation Kill, Unit is slabels.put(LabelKeyConstant.JOB_QUEUING_TIMEOUT_KEY, "10");//job Queue over 10s Failed to complete automatic initiation Kill, Unit is slabels.put(LabelKeyConstant.RETRY_TIMEOUT_KEY, "10000");//job Waiting time for retry due to failure of resources , Unit is ms, If the queue fails because of insufficient resources , By default, it will initiate 10 Retrieslabels.put(LabelKeyConstant.TENANT_KEY,"hduser02");// Tenant label , If the tenant parameter is specified for the task, the task will be routed to a separate ECM machinelabels.put(LabelKeyConstant.EXECUTE_ONCE_KEY,"");// Execute label once , This parameter is not recommended , After setting, the engine will not reuse, and the engine will end after the task runs , Only a task parameter with specialization can be set

queue CPU Use the upper limit [wds.linkis.rm.yarnqueue.cores.max], At this stage, only restrictions are supported Spark Use of total queue resources for type tasksMaximum queue memory usage [wds.linkis.rm.yarnqueue.memory.max]Global memory usage limit of each engine [wds.linkis.rm.client.memory.max] This parameter does not refer to the total memory that can only be used , Instead, specify a Creator Total memory usage of a specific engine , Such as restrictions IDE-SPARK Tasks can only use 10G MemoryThe maximum number of cores of each engine in the whole world [wds.linkis.rm.client.core.max] This parameter does not mean that it can only be used in total CPU, Instead, specify a Creator Total memory usage of a specific engine , Such as restrictions IDE-SPARK Tasks can only use 10CoresThe maximum concurrency of each engine globally [wds.linkis.rm.instance], This parameter has two meanings , One is to limit one Creator How many specific engines can be started in total , And limit a Creator The number of tasks that a specific engine task can run at the same time


How to be a community contributor
1 ► Official document contribution . Discover the inadequacy of the document 、 Optimize the document , Participate in community contribution by continuously updating documents . Contribute through documentation , Let developers know how to submit PR And really participate in the construction of the community . Reference guide : Nanny class course : How to become Apache Linkis Document contributors
2 ► Code contribution . We sorted out the simple and easy to get started tasks in the community , It is very suitable for newcomers to make code contributions . Please refer to the novice task list :https://github.com/apache/incubator-linkis/issues/1161
3 ► Content contribution : Release WeDataSphere Content related to open source components , Including but not limited to installation and deployment tutorials 、 Use experience 、 Case practice, etc , There is no limit to form , Please submit your contribution to the little assistant . for example :
Technical dry cargo | Linkis practice : The new engine implements process parsing
Community developer column | MariaCarrie:Linkis1.0.2 Installation and use guide
4 ► Community Q & A : Actively answer questions in the community 、 Share technology 、 Help developers solve problems, etc ;
5 ► other : Actively participate in community activities 、 Become a community volunteer 、 Help the community promote 、 Provide effective suggestions for community development ;

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