java（多线程）实现高性能数据同步

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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

Java代码

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

Java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);
}
}
}