Shulou(Shulou.com)06/03 Report--

Elastic job is a Java distributed timing task developed and open source by Dangdang Network architect Zhang Liang, Cao Hao and Jiang Shujian based on Zookepper and Quartz, which solves the disadvantage that Quartz does not support distributed. The main features of Elastic job include support for flexible capacity expansion, centralized management and monitoring of job through Zookepper, and support for failure transfer, which are unmatched by other scheduled tasks such as Quartz.

At present, the latest version of Elastic job has been separated from the original elastic-job-core except for two projects, Elastic-Job-Lite and Elastic-Job-Cloud. Elastic-Job is a distributed scheduling solution, which is composed of two independent sub-projects Elastic-Job-Lite and Elastic-Job-Cloud. Elastic-Job-Lite is positioned as a lightweight decentralized solution and provides coordination services for distributed tasks in the form of jar packages. Elastic-Job-Cloud uses the solution of Mesos + Docker (TBD) to provide additional services such as resource governance, application distribution and process isolation. Elastic-Job-Lite and Elastic-Job-Cloud provide the same set of API development jobs, and developers only need to develop once to deploy as Lite or Cloud as needed.

At the beginning of a term on copy, the explanation is very clear. The summary is: elastic job is used to achieve distributed scheduled tasks, such as scheduled task projects, deployed in 2, but only need to execute once, but want to keep the code of the two servers consistent, at this time elasitc job can perfectly solve the problem, of course, it uses the relevant features of zookeeper.

1. Actual combat

The project directory is as follows

1.pom.xml

Create a new maven project and introduce the related jar packages of springboot

Then introduce the relevant core package elastic-job-core,elastic-job-spring of elastic job

4.0.0 com.xj el 0.0.1-SNAPSHOT jar el http://maven.apache.org UTF-8 org.springframework.boot spring-boot-starter-parent 1.4.0.RELEASE junit junit 3.8.1 test org.springframework.boot spring-boot-starter-web com.dangdang Elastic-job-core 1.1.1 com.dangdang elastic-job-spring 1.1.1 org.springframework.boot spring-boot-maven-plugin

2.reg.properties

Store the configuration information of the zookeeper configuration center

ServerLists=10.3.142.107:2181,10.3.142.107:2182106.3.14.107:2183namespace=elastic-job-examplebaseSleepTimeMilliseconds=1000maxSleepTimeMilliseconds=3000maxRetries=3

3.withNamespace.xml

Store the relevant details of the job. Here the test stores the situation in simple and dataFlow 2.

Elastic-job provides three types of jobs: Simple type jobs, Dataflow type jobs, and Script type jobs. Here we mainly talk about the first two. Script type job means script type job. All types of scripts, such as shell,python,perl, are supported. If you don't use much, you can refer to the github documentation.

SimpleJob needs to implement the SimpleJob interface, which means simple implementation without any encapsulation, similar to the native quartz interface, such as job used in the sample code.

The Dataflow type is used to handle data flow, and you need to implement the DataflowJob interface. This interface provides two methods for overriding, which are used to fetchData and processData data, respectively.

Streaming can be configured through DataflowJobConfiguration.

For streaming data, the job stops crawling only when the return value of the fetchData method is null or the set length is empty, otherwise the job will run forever; non-streaming data will only execute the fetchData method and processData method once during each job execution, and the job will be completed immediately.

In actual development, the Dataflow type of job is still very useful.

4.MySimpleJob.java

Package com.xj.el;import com.dangdang.ddframe.job.api.JobExecutionMultipleShardingContext;import com.dangdang.ddframe.job.plugin.job.type.simple.AbstractSimpleElasticJob Public class MySimpleJob extends AbstractSimpleElasticJob {@ Override public void process (JobExecutionMultipleShardingContext shardingContext) {System.out.println (String.format ("- Thread ID:% s, total number of tasks:% s, current shard item:% s", Thread.currentThread () .getId (), shardingContext.getShardingTotalCount (), shardingContext.getShardingItems ();}}

5.MyThroughputDataFlowElasticJob.java

Package com.xj.el;import java.sql.Time;import java.text.SimpleDateFormat;import java.util.ArrayList;import java.util.Date;import java.util.List;import com.dangdang.ddframe.job.api.JobExecutionMultipleShardingContext;import com.dangdang.ddframe.job.internal.job.AbstractJobExecutionShardingContext;import com.dangdang.ddframe.job.plugin.job.type.dataflow.AbstractIndividualThroughputDataFlowElasticJob;public class MyThroughputDataFlowElasticJob extends AbstractIndividualThroughputDataFlowElasticJob {public List fetchData (JobExecutionMultipleShardingContext shardingContext) {List testBeanList = new ArrayList () / / obtain the relevant data of testBean return testBeanList;} public boolean processData (JobExecutionMultipleShardingContext shardingContext, TestBean data) {/ / process the relevant data of testBean above return false;}}

6.springboot test main class SpringBootSampleApplication.java

Package com.xj.el;import org.springframework.boot.SpringApplication;import org.springframework.boot.autoconfigure.EnableAutoConfiguration;import org.springframework.context.annotation.ImportResource;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RestController / * * Hello world! * * / @ RestController@EnableAutoConfiguration@ImportResource (locations = {"classpath:withNamespace.xml"}) public class SpringBootSampleApplication {public static void main (String [] args) {SpringApplication.run (SpringBootSampleApplication.class, args);} @ RequestMapping ("/") String home () {return "Hello World!";}}

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