Spring批处理分区：连续（不并行）运行从属程序

Question

我使用spring batch来执行一些calcul，在reader中，我必须获得一个大数据，以便在处理器/写入器中处理，这个过程需要大量的(RAM)。因此，我尝试使用分区器拆分步骤，如下所示：

<batch:step id="MyStep.master" >
    <partition step="MyStep" partitioner="MyPartitioner">
        <handler grid-size="1" task-executor="TaskExecutor" />
    </partition>
</batch:step>

<batch:step id="MyStep" >
    <batch:tasklet transaction-manager="transactionManager">
        <batch:chunk reader="MyReader" processor="MyProcessor"
            writer="MyWriter" commit-interval="1000" skip-limit="1000">
            <batch:skippable-exception-classes>
                <batch:include class="...FunctionalException" />
            </batch:skippable-exception-classes>
        </batch:chunk>
    </batch:tasklet>
</batch:step>

<bean id="MyPartitioner" class="...MyPartitioner" scope="step"/>

<bean id="TaskExecutor" class="org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor" >

<bean name="MyReader"
    class="org.springframework.batch.item.database.JdbcCursorItemReader"
    scope="step">
    <property name="dataSource" ref="dataSource" />
    <property name="sql">
        <value>
            <![CDATA[
                SELECT...                   
            ]]>
        </value>
    </property>
    <property name="rowMapper" ref="MyRowMapper" />
</bean>

<bean id="MyRowMapper" class="...MyRowMapper" />

<bean id="dataSource" class="com.mchange.v2.c3p0.ComboPooledDataSource" destroy-method="close">
    <property name="driverClass" value="org.postgresql.Driver"/>
    <property name="jdbcUrl" value="jdbc:postgresql://${database.host}/${database.name}"/>
    <property name="user" value="${database.user}"/>
    <property name="password" value="${database.password}"/>        
    <property name="acquireIncrement" value="1" />
    <property name="autoCommitOnClose" value="true" />
    <property name="minPoolSize" value="${min.pool.size}" /> <!-- min.pool.size=5  -->
    <property name="maxPoolSize" value="${max.pool.size}" /> <!-- max.pool.size=15  -->
</bean>

但是分区也徒劳地占用了大量内存，因为步骤（从机）是并行执行的，我想做的是拆分步骤并连续执行线程（而不是并行执行）以减少内存使用(RAM)，这可能吗？

Answer 1

这个问题有点老了，所以我不确定这是否有帮助，可能你自己解决了。

如果行执行顺序没有问题，那么解决方案是查询分区器bean中的db，然后将所有信息传递给每个分区，以便将表/秒(start_key，end_key)分成几个部分。这将大大减少ram的使用。

一些警告：

null

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:batch="http://www.springframework.org/schema/batch"
    xmlns:context="http://www.springframework.org/schema/context"
    xmlns:aop="http://www.springframework.org/schema/aop" xmlns:util="http://www.springframework.org/schema/util"
    xsi:schemaLocation="http://www.springframework.org/schema/aop http://www.springframework.org/schema/aop/spring-aop-4.0.xsd
        http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-4.0.xsd
        http://www.springframework.org/schema/util http://www.springframework.org/schema/util/spring-util-4.0.xsd
        http://www.springframework.org/schema/batch http://www.springframework.org/schema/batch/spring-batch-3.0.xsd
        http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-4.0.xsd">

    <!-- JOB -->
    <batch:job id="printPdf" job-repository="jobRepository"
        restartable="false">

        <batch:step id="MyStep">
            <batch:partition step="MyStep.template"
                partitioner="myPartitioner" handler="partitionHandler">
            </batch:partition>
        </batch:step>

    </batch:job>

    <!-- Partitioner -->
    <bean id="myPartitioner" class="foo.MyPartitioner"
        scope="step">
        <property name="jdbcTemplate" ref="myJdbcTemplate" />
        <property name="sql"
            value="Select ...." />
        <property name="rowMap">
            <bean
                class="foo.MyPartitionHandlerRowMapper" />
        </property>
        <property name="preparedStatementSetter">
            <bean
                class="org.springframework.batch.core.resource.ListPreparedStatementSetter">
                <property name="parameters">
                    <list>
                        <value>#{jobParameters['param1']}</value>
                    </list>
                </property>
            </bean>
        </property>
    </bean>

    <bean id="partitionHandler" scope="step"
        class="org.springframework.batch.core.partition.support.TaskExecutorPartitionHandler">
        <property name="taskExecutor" ref="customTaskExecutor" />
        <property name="gridSize" value="#{jobParameters['gridSize']}" />
        <property name="step" ref="MyStep.template" />
    </bean>

    <bean id="customTaskExecutor"
        class="org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor">
        <property name="corePoolSize" value="8" />
        <property name="maxPoolSize" value="8" />
        <property name="waitForTasksToCompleteOnShutdown" value="true" />
        <property name="awaitTerminationSeconds" value="120" />
    </bean>

    <batch:step id="MyStep.tempate">
        <batch:tasklet transaction-manager="transactionManager">
            <batch:chunk commit-interval="2500" reader="myReader"
                processor="myProcessor" writer="myWriter" skip-limit="2500">
            <batch:skippable-exception-classes>
                <batch:include class="...FunctionalException" />
            </batch:skippable-exception-classes>
            </batch:chunk>
        </batch:tasklet>
    </batch:step>

    <!-- Beans -->

    <!-- Processors -->
    <bean id="myProcessor" class="foo.MyProcessor"
        scope="step">
    </bean>

    <bean id="classLoaderVerifier"
        class="it.addvalue.pkjwd.services.genbean.GenericStockKeysForNoDuplicate" />

    <!-- Readers -->
    <bean id="myReader"
        class="org.springframework.batch.item.database.JdbcCursorItemReader"
        scope="step">
        <property name="dataSource" ref="myDataSouce" />
        <property name="sql"
            value="select ... from ... where ID >= ? and ID <= ?" />
        <property name="rowMapper">
            <bean class="foo.MyReaderPartitionedRowMapper" />
        </property>
        <property name="preparedStatementSetter">
            <bean
                class="org.springframework.batch.core.resource.ListPreparedStatementSetter">
                <property name="parameters">
                    <list>
                        <value>#{stepExecutionContext['START_ID']}</value>
                        <value>#{stepExecutionContext['END_ID']}</value>
                    </list>
                </property>
            </bean>
        </property>
    </bean>

    <!-- Writers -->
    <bean id="myWriter"
        class="org.springframework.batch.item.database.JdbcBatchItemWriter">
        <property name="assertUpdates" value="false" />
        <property name="itemPreparedStatementSetter">
            <bean class="foo.MyWriterStatementSetters" />
        </property>
        <property name="sql"
            value="insert ..." />
        <property name="dataSource" ref="myDataSouce" />
    </bean>

</beans>

您的分区器Bean如下所示：

package foo;

import foo.model.MyTable;

import java.util.HashMap;
import java.util.List;
import java.util.Map;

import org.apache.commons.lang.StringUtils;
import org.springframework.batch.core.partition.support.Partitioner;
import org.springframework.batch.item.ExecutionContext;
import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.jdbc.core.PreparedStatementSetter;
import org.springframework.jdbc.core.RowMapper;

public class MyPartitioner implements Partitioner
{
    private JdbcTemplate                     jdbcTemplate;

    private RowMapper<foo.model.MyTable> rowMap;

    private String                           sql;

    private PreparedStatementSetter          preparedStatementSetter;

    public JdbcTemplate getJdbcTemplate()
    {
        return jdbcTemplate;
    }

    public void setJdbcTemplate(JdbcTemplate jdbcTemplate)
    {
        this.jdbcTemplate = jdbcTemplate;
    }

    public RowMapper<foo.model.MyTable> getRowMap()
    {
        return rowMap;
    }

    public void setRowMap(RowMapper<PkjwdPolizzePartition> rowMap)
    {
        this.rowMap = rowMap;
    }

    public String getSql()
    {
        return sql;
    }

    public void setSql(String sql)
    {
        this.sql = sql;
    }

    public PreparedStatementSetter getPreparedStatementSetter()
    {
        return preparedStatementSetter;
    }

    public void setPreparedStatementSetter(PreparedStatementSetter preparedStatementSetter)
    {
        this.preparedStatementSetter = preparedStatementSetter;
    }

    @Override
    public Map<String, ExecutionContext> partition(int gridSize)
    {
        Map<String, ExecutionContext> map = new HashMap<String, ExecutionContext>();

        try
        {
            List<PkjwdPolizzePartition> lstMyRows = jdbcTemplate.query(sql, preparedStatementSetter ,rowMap);

            if ( lstMyRows.size() > 0 )
            {
                int total = lstMyRows.size();
                int rowsPerPartition = total / gridSize;
                int leftovers = total % gridSize;
                total = lstMyRows.size() - 1;

                int startPos = 0;
                int endPos = rowsPerPartition - 1;

                int i = 0;

                while (endPos <= (total))
                {

                    ExecutionContext context = new ExecutionContext();

                    if ( endPos + leftovers == total )
                    {
                        endPos = total;
                    }
                    else if ( endPos >= (total) )
                    {
                        endPos = total;
                    }

                    context.put("START_ID", lstMyRows.get(startPos).getId());
                    context.put("END_ID", lstMyRows.get(endPos).getId());



                    map.put("PART_" + StringUtils.leftPad("" + i, ("" + gridSize).length(), '0'), context);

                    i++;
                    startPos = endPos + 1;
                    endPos = endPos + rowsPerPartition;
                }
            }

        }
        catch ( Exception e )
        {
            e.printStackTrace();
        }

        return map;
    }

}