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);  
        }  
    }  
}  
  

java（多线程）实现高性能数据同步