Spring Batch Partitioning example
Spring Batch Partitioning example
Photo Credit : Spring Source
In Spring Batch, “Partitioning” is “multiple threads to process a range of data each”. For example, assume you have 100 records in a table, which has “primary id” assigned from 1 to 100, and you want to process the entire 100 records.
Normally, the process starts from 1 to 100, a single thread example. The process is estimated to take 10 minutes to finish.
Single Thread - Process from 1 to 100In “Partitioning”, we can start 10 threads to process 10 records each (based on the range of ‘id’). Now, the process may take only 1 minute to finish.
Thread 1 - Process from 1 to 10
Thread 2 - Process from 11 to 20
Thread 3 - Process from 21 to 30
......
Thread 9 - Process from 81 to 90
Thread 10 - Process from 91 to 100To implement “Partitioning” technique, you must understand the structure of the input data to process, so that you can plan the “range of data” properly.
1. Tutorial
In this tutorial, we will show you how to create a “Partitioner” job, which has 10 threads, each thread will read records from the database, based on the provided range of ‘id’.
Tools and libraries used
- Maven 3
- Eclipse 4.2
- JDK 1.6
- Spring Core 3.2.2.RELEASE
- Spring Batch 2.2.0.RELEASE
- MySQL Java Driver 5.1.25
P.S Assume “users” table has 100 records.
users table structure
id, user_login, user_passs, age
1,user_1,pass_1,20
2,user_2,pass_2,40
3,user_3,pass_3,70
4,user_4,pass_4,5
5,user_5,pass_5,52
......
99,user_99,pass_99,89
100,user_100,pass_100,76
2. Project Directory Structure
Review the final project structure, a standard Maven project.
3. Partitioner
First, create a Partitioner implementation, puts the “ partitioning range ” into theExecutionContext . Later, you will declare the same fromId and tied in the batch-job XML file.
In this case, the partitioning range is look like the following :
Thread 1 = 1 - 10
Thread 2 = 11 - 20
Thread 3 = 21 - 30
......
Thread 10 = 91 - 100
RangePartitioner.java
package com.mkyong.partition;
import java.util.HashMap;
import java.util.Map;
import org.springframework.batch.core.partition.support.Partitioner;
import org.springframework.batch.item.ExecutionContext;
public class RangePartitioner implements Partitioner {
@Override
public Map<String, ExecutionContext> partition(int gridSize) {
Map<String, ExecutionContext> result
= new HashMap<String, ExecutionContext>();
int range = 10;
int fromId = 1;
int toId = range;
for (int i = 1; i <= gridSize; i++) {
ExecutionContext value = new ExecutionContext();
System.out.println("\nStarting : Thread" + i);
System.out.println("fromId : " + fromId);
System.out.println("toId : " + toId);
value.putInt("fromId", fromId);
value.putInt("toId", toId);
// give each thread a name, thread 1,2,3
value.putString("name", "Thread" + i);
result.put("partition" + i, value);
fromId = toId + 1;
toId += range;
}
return result;
}
}
4. Batch Jobs
Review the batch job XML file, it should be self-explanatory. Few points to highlight :
- For partitioner, grid-size = number of threads .
- For pagingItemReader bean, a jdbc reader example, the
#{stepExecutionContext[fromId, toId]}values will be injected by theExecutionContextin rangePartitioner. - For itemProcessor bean, the
#{stepExecutionContext[name]}values will be injected by theExecutionContextin rangePartitioner. - For writers, each thread will output the records in a different csv files, with filename format –
users.processed[fromId]}-[toId].csv.
job-partitioner.xml
xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:batch="http://www.springframework.org/schema/batch"
xmlns:util="http://www.springframework.org/schema/util"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.springframework.org/schema/batch
http://www.springframework.org/schema/batch/spring-batch-2.2.xsd
http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans-3.2.xsd
http://www.springframework.org/schema/util
http://www.springframework.org/schema/util/spring-util-3.2.xsd
">
<import resource="../config/context.xml" />
<import resource="../config/database.xml" />
<job id="partitionJob" xmlns="http://www.springframework.org/schema/batch">
<step id="masterStep">
<partition step="slave" partitioner="rangePartitioner">
<handler grid-size="10" task-executor="taskExecutor" />
partition>
step>
job>
<step id="slave" xmlns="http://www.springframework.org/schema/batch">
<tasklet>
<chunk reader="pagingItemReader" writer="flatFileItemWriter"
processor="itemProcessor" commit-interval="1" />
tasklet>
step>
<bean id="rangePartitioner" class="com.mkyong.partition.RangePartitioner" />
<bean id="taskExecutor" class="org.springframework.core.task.SimpleAsyncTaskExecutor" />
<bean id="itemProcessor" class="com.mkyong.processor.UserProcessor" scope="step">
<property name="threadName" value="#{stepExecutionContext[name]}" />
bean>
<bean id="pagingItemReader"
class="org.springframework.batch.item.database.JdbcPagingItemReader"
scope="step">
<property name="dataSource" ref="dataSource" />
<property name="queryProvider">
<bean
class="org.springframework.batch.item.database.support.SqlPagingQueryProviderFactoryBean">
<property name="dataSource" ref="dataSource" />
<property name="selectClause" value="select id, user_login, user_pass, age" />
<property name="fromClause" value="from users" />
<property name="whereClause" value="where id >= :fromId and id <= :toId" />
<property name="sortKey" value="id" />
bean>
property>
<property name="parameterValues">
<map>
<entry key="fromId" value="#{stepExecutionContext[fromId]}" />
<entry key="toId" value="#{stepExecutionContext[toId]}" />
map>
property>
<property name="pageSize" value="10" />
<property name="rowMapper">
<bean class="com.mkyong.UserRowMapper" />
property>
bean>
<bean id="flatFileItemWriter" class="org.springframework.batch.item.file.FlatFileItemWriter"
scope="step" >
<property name="resource"
value="file:csv/outputs/users.processed#{stepExecutionContext[fromId]}-#{stepExecutionContext[toId]}.csv" />
<property name="appendAllowed" value="false" />
<property name="lineAggregator">
<bean
class="org.springframework.batch.item.file.transform.DelimitedLineAggregator">
<property name="delimiter" value="," />
<property name="fieldExtractor">
<bean
class="org.springframework.batch.item.file.transform.BeanWrapperFieldExtractor">
<property name="names" value="id, username, password, age" />
bean>
property>
bean>
property>
bean>
beans>
The item processor class is used to print out the processing item and current running “thread name” only.
UserProcessor.java – item processor
package com.mkyong.processor;
import org.springframework.batch.item.ItemProcessor;
import com.mkyong.User;
public class UserProcessor implements ItemProcessor<User, User> {
private String threadName;
@Override
public User process(User item) throws Exception {
System.out.println(threadName + " processing : "
+ item.getId() + " : " + item.getUsername());
return item;
}
public String getThreadName() {
return threadName;
}
public void setThreadName(String threadName) {
this.threadName = threadName;
}
}5. Run It
Loads everything and run it… 10 threads will be started to process the provided range of data.
package com.mkyong;
import org.springframework.batch.core.Job;
import org.springframework.batch.core.JobExecution;
import org.springframework.batch.core.JobParameters;
import org.springframework.batch.core.JobParametersBuilder;
import org.springframework.batch.core.launch.JobLauncher;
import org.springframework.context.ApplicationContext;
import org.springframework.context.support.ClassPathXmlApplicationContext;
public class PartitionApp {
public static void main(String[] args) {
PartitionApp obj = new PartitionApp ();
obj.runTest();
}
private void runTest() {
String[] springConfig = { "spring/batch/jobs/job-partitioner.xml" };
ApplicationContext context = new ClassPathXmlApplicationContext(springConfig);
JobLauncher jobLauncher = (JobLauncher) context.getBean("jobLauncher");
Job job = (Job) context.getBean("partitionJob");
try {
JobExecution execution = jobLauncher.run(job, new JobParameters());
System.out.println("Exit Status : " + execution.getStatus());
System.out.println("Exit Status : " + execution.getAllFailureExceptions());
} catch (Exception e) {
e.printStackTrace();
}
System.out.println("Done");
}
}
Console output
Starting : Thread1
fromId : 1
toId : 10
Starting : Thread2
fromId : 11
toId : 20
Starting : Thread3
fromId : 21
toId : 30
Starting : Thread4
fromId : 31
toId : 40
Starting : Thread5
fromId : 41
toId : 50
Starting : Thread6
fromId : 51
toId : 60
Starting : Thread7
fromId : 61
toId : 70
Starting : Thread8
fromId : 71
toId : 80
Starting : Thread9
fromId : 81
toId : 90
Starting : Thread10
fromId : 91
toId : 100
Thread8 processing : 71 : user_71
Thread2 processing : 11 : user_11
Thread3 processing : 21 : user_21
Thread10 processing : 91 : user_91
Thread4 processing : 31 : user_31
Thread6 processing : 51 : user_51
Thread5 processing : 41 : user_41
Thread1 processing : 1 : user_1
Thread9 processing : 81 : user_81
Thread7 processing : 61 : user_61
Thread2 processing : 12 : user_12
Thread7 processing : 62 : user_62
Thread6 processing : 52 : user_52
Thread1 processing : 2 : user_2
Thread9 processing : 82 : user_82
......
After the process is completed, 10 CSV files will be created.
users.processed1-10.csv
1,user_1,pass_1,20 2,user_2,pass_2,40 3,user_3,pass_3,70 4,user_4,pass_4,5 5,user_5,pass_5,52 6,user_6,pass_6,69 7,user_7,pass_7,48 8,user_8,pass_8,34 9,user_9,pass_9,62 10,user_10,pass_10,21
6. Misc
6.1 Alternatively, you can inject the #{stepExecutionContext[name]} via annotation.
UserProcessor.java – Annotation version
package com.mkyong.processor;
import org.springframework.batch.item.ItemProcessor;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Scope;
import org.springframework.stereotype.Component;
import com.mkyong.User;
@Component("itemProcessor")
@Scope(value = "step")
public class UserProcessor implements ItemProcessor<User, User> {
@Value("#{stepExecutionContext[name]}")
private String threadName;
@Override
public User process(User item) throws Exception {
System.out.println(threadName + " processing : "
+ item.getId() + " : " + item.getUsername());
return item;
}
}Remember, enable the Spring component auto scanning.
<context:component-scan base-package="com.mkyong" />
6.2 Database partitioner reader – MongoDB example.
job-partitioner.xml
<bean id="mongoItemReader" class="org.springframework.batch.item.data.MongoItemReader"
scope="step">
<property name="template" ref="mongoTemplate" />
<property name="targetType" value="com.mkyong.User" />
<property name="query"
value="{
'id':{$gt:#{stepExecutionContext[fromId]}, $lte:#{stepExecutionContext[toId]}
} }"
/>
<property name="sort">
<util:map id="sort">
<entry key="id" value="" />
util:map>
property>
bean>
Done.
Download Source Code
Download it – SpringBatch-Partitioner-Example.zip (31 KB)