java(多线程)实现高性能数据同步

    需要将生产环境上Infoxmix里的数据原封不动的Copy到另一台 Oracle数据库服务器上,然后对Copy后的数据作些漂白处理。为了将人为干预的因素降到最低,在系统设计时采用Java代码对数据作Copy,思路 如图:



    首 先在代码与生产库间建立一个Connection,将读取到的数据放在ResultSet对象,然后再与开发库建立一个Connection。从 ResultSet取出数据后通过TestConnection插入到开发库,以此来实现Copy。代码写完后运行程序,速度太慢了,一秒钟只能Copy 一千条数据,生产库上有上亿条数据,按照这个速度同步完要到猴年马月呀,用PreparedStatement批处理速度也没有提交多少。我想能不能用多 线程处理,多个人干活总比一个人干活速度要快。
    假设生产库有1万条数据,我开5个线程,每个线程分2000条数据,同时向开发库里插数据,Oracle支持高并发这样的话速度至少会提高好多倍,按照这 个思路重新进行了编码,批处理设置为1万条一提交,统计插入数量的变量使用 java.util.concurrent.atomic.AtomicLong,程序一运行,传输速度飞快CPU利用率在70%~90%,现在一秒钟可 以拷贝50万条记录,没过几分钟上亿条数据一条不落地全部Copy到目标库。

在查询的时候我用了如下语句
String queryStr = "SELECT * FROM xx";
ResultSet coreRs = PreparedStatement.executeQuery(queryStr);

实习生问如果xx表里有上千万条记录,你全部查询出来放到ResultSet, 那内存不溢出了么?Java在设计的时候已经考虑到这个问题了,并没有查询出所有的数据,而是只查询了一部分数据放到ResultSet,数据“用完”它 会自动查询下一批数据,你可以用setFetchSize(int rows)方法设置一个建议值给ResultSet,告诉它每次从数据库Fetch多少条数据。但我不赞成,因为JDBC驱动会根据实际情况自动调整 Fetch的数量。另外性能也与网线的带宽有直接的关系。
相关代码

package com.dlbank.domain; 
 
import java.sql.Connection; 
import java.sql.PreparedStatement; 
import java.sql.ResultSet; 
import java.sql.Statement; 
import java.util.List; 
import java.util.concurrent.atomic.AtomicLong; 
 
import org.apache.log4j.Logger; 
 
/**
*<p>title: 数据同步类 </p>  
*<p>Description: 该类用于将生产核心库数据同步到开发库</p>  
*@author Tank Zhang 
*/ 
public class CoreDataSyncImpl implements CoreDataSync { 
     
    private List<String> coreTBNames; //要同步的核心库表名 
    private ConnectionFactory connectionFactory; 
    private Logger log = Logger.getLogger(getClass()); 
     
    private AtomicLong currentSynCount = new AtomicLong(0L); //当前已同步的条数 
     
    private int syncThreadNum;  //同步的线程数 
 
    @Override 
    public void syncData(int businessType) throws Exception { 
         
        for (String tmpTBName : coreTBNames) { 
            log.info("开始同步核心库" + tmpTBName + "表数据"); 
            // 获得核心库连接 
            Connection coreConnection = connectionFactory.getDMSConnection(4); 
            Statement coreStmt = coreConnection.createStatement(); 
            //为每个线程分配结果集 
            ResultSet coreRs = coreStmt.executeQuery("SELECT count(*) FROM "+tmpTBName); 
            coreRs.next(); 
            //总共处理的数量 
            long totalNum = coreRs.getLong(1); 
            //每个线程处理的数量 
            long ownerRecordNum =(long) Math.ceil((totalNum / syncThreadNum));  
            log.info("共需要同步的数据量:"+totalNum); 
            log.info("同步线程数量:"+syncThreadNum); 
            log.info("每个线程可处理的数量:"+ownerRecordNum); 
            // 开启五个线程向目标库同步数据 
            for(int i=0; i < syncThreadNum; i ++){ 
                StringBuilder sqlBuilder = new StringBuilder(); 
                //拼装后SQL示例 
                //Select * From dms_core_ds Where id between 1 And 657398 
                //Select * From dms_core_ds Where id between 657399 And 1314796 
                //Select * From dms_core_ds Where id between 1314797 And 1972194 
                //Select * From dms_core_ds Where id between 1972195 And 2629592 
                //Select * From dms_core_ds Where id between 2629593 And 3286990 
                //.. 
                sqlBuilder.append("Select * From ").append(tmpTBName) 
                        .append(" Where id between " ).append(i * ownerRecordNum +1) 
                        .append( " And ") 
                        .append((i * ownerRecordNum + ownerRecordNum)); 
                Thread workThread = new Thread( 
                        new WorkerHandler(sqlBuilder.toString(),businessType,tmpTBName)); 
                workThread.setName("SyncThread-"+i); 
                workThread.start(); 
            } 
            while (currentSynCount.get() < totalNum); 
            //休眠一会儿让数据库有机会commit剩余的批处理(只针对JUnit单元测试,
//因为单元测试完成后会关闭虚拟器,使线程里的代码没有机会作提交操作); 
            //Thread.sleep(1000 * 3); 
            log.info( "核心库"+tmpTBName+"表数据同步完成,共同步了" + currentSynCount.get() + "条数据"); 
        } 
    }// end for loop 
     
    public void setCoreTBNames(List<String> coreTBNames) { 
        this.coreTBNames = coreTBNames; 
    } 
 
    public void setConnectionFactory(ConnectionFactory connectionFactory) { 
        this.connectionFactory = connectionFactory; 
    } 
     
    public void setSyncThreadNum(int syncThreadNum) { 
        this.syncThreadNum = syncThreadNum; 
    } 
     
    //数据同步线程 
    final class WorkerHandler implements Runnable { 
        ResultSet coreRs; 
        String queryStr; 
        int businessType; 
        String targetTBName; 
        public WorkerHandler(String queryStr,int businessType,String targetTBName) { 
            this.queryStr = queryStr; 
            this.businessType = businessType; 
            this.targetTBName = targetTBName; 
        } 
        @Override 
        public void run() { 
            try { 
                //开始同步 
                launchSyncData(); 
            } catch(Exception e){ 
                log.error(e); 
                e.printStackTrace(); 
            } 
        } 
        //同步数据方法 
        void launchSyncData() throws Exception{ 
            // 获得核心库连接 
            Connection coreConnection = connectionFactory.getDMSConnection(4); 
            Statement coreStmt = coreConnection.createStatement(); 
            // 获得目标库连接 
            Connection targetConn = connectionFactory.getDMSConnection(businessType); 
            targetConn.setAutoCommit(false);// 设置手动提交 
            PreparedStatement targetPstmt =
targetConn.prepareStatement("INSERT INTO " + targetTBName+" VALUES (?,?,?,?,?)"); 
            ResultSet coreRs = coreStmt.executeQuery(queryStr); 
            log.info(Thread.currentThread().getName()+"'s Query SQL::"+queryStr); 
            int batchCounter = 0; //累加的批处理数量 
            while (coreRs.next()) { 
                targetPstmt.setString(1, coreRs.getString(2)); 
                targetPstmt.setString(2, coreRs.getString(3)); 
                targetPstmt.setString(3, coreRs.getString(4)); 
                targetPstmt.setString(4, coreRs.getString(5)); 
                targetPstmt.setString(5, coreRs.getString(6)); 
                targetPstmt.addBatch(); 
                batchCounter++; 
                currentSynCount.incrementAndGet();//递增 
                if (batchCounter % 10000 == 0) { //1万条数据一提交 
                    targetPstmt.executeBatch(); 
                    targetPstmt.clearBatch(); 
                    targetConn.commit(); 
                } 
            } 
            //提交剩余的批处理 
            targetPstmt.executeBatch(); 
            targetPstmt.clearBatch(); 
            targetConn.commit(); 
            //释放连接  
            connectionFactory.release(targetConn, targetPstmt,coreRs); 
        } 
    } 

 

评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值