oracle10 千万级数据存取优化
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     今天对一个存有1000万数据的大表进行了优化，尽是简单的优化，效果很明显。下面把自己的优化经过简单总结备忘一下。
     1:创建表的备份，把生产表的querySql copy后修改table 为temp_tbl
     2:从原有表中copy 数据插入到temp_tbl中语句如下
       insert into temp_tbl select * from source_tbl
     3:查看表数据量
       selct count(1) from temp_tbl
     4:查看表所在空间大小
       select segment_name, bytes/1024/1024/1024 from user_segments
       where segment_NAME = 'TEMP_TBL';
     5:查看当前表索引
       select * from user_indexes where TABLE_Name = 'TEMP_TBL'
     6:利用存储过程做基数数据准备
    

      CREATE OR REPLACE PROCEDURE CASE_ACLINE_TEMP_INSERT
AS
SQL_STMT VARCHAR2(1000) ;
TYPE T_CUR IS REF CURSOR;
V_PCUR T_CUR;
TYPE CASE_IDS_TBL IS TABLE OF CASE_INFO_TEMP.ID%TYPE
INDEX BY PLS_INTEGER;
CASE_IDS CASE_IDS_TBL ;
RESULTCOUNT INTEGER ;
BEGIN
   SQL_STMT := 'SELECT ID FROM CASE_INFO_TEMP WHERE ID > 725' ;
   EXECUTE IMMEDIATE  'SELECT COUNT(1) FROM ('||SQL_STMT||') ' INTO RESULTCOUNT ;
   IF RESULTCOUNT = 0 THEN
      RETURN ;
   END IF ;

   OPEN V_PCUR FOR SQL_STMT;
     FETCH V_PCUR BULK COLLECT INTO CASE_IDS;
     FOR I IN CASE_IDS.FIRST .. CASE_IDS.LAST
     LOOP
     SQL_STMT := 'INSERT INTO CASE_ACLINE_TEMP SELECT ID,NAME,VALID,I_NODE ,';
     SQL_STMT := SQL_STMT || 'J_NODE,I_OFF,J_OFF,NOTE,'||CASE_IDS(I)||',R,X,B,UPDATETIME,I_P,I_Q,';
     SQL_STMT := SQL_STMT || 'J_P,J_Q,I_QC,J_QC FROM CASE_ACLINE WHERE CASE_ID=725' ;
     --DBMS_OUTPUT.PUT_LINE(SQL_STMT);
     EXECUTE IMMEDIATE SQL_STMT ;
     COMMIT ;
   END LOOP;
   CLOSE V_PCUR ;
  
END CASE_ACLINE_TEMP_INSERT;             

     

     7:在java中开启100个线程模拟100个用户 对该表进行单次10000数据插入(前提：temp_tbl     表中存有1000万数据)
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     @Service
public class CaseAclineServiceImpl extends CaseServiceImpl<CaseAcline> implements
		CaseAclineService {
       @Autowired
       private CaseAclineDao aclineDao;
       public void insertTemp(int caseID, CountDownLatch counter) {
		long l1 = System.currentTimeMillis() ;
		this.aclineDao.insertTemp(caseID);
		counter.countDown() ;
		long l2 = System.currentTimeMillis() ;
		System.out.println("编号 "+caseID+ "插入消耗："+(l2-l1)+"毫秒");
	}
	
	public void queryTemp(int caseID, CountDownLatch counter) {
		long l1 = System.currentTimeMillis() ;
		Query q = new Query() ;
		q.addQueryParam("caseID", caseID) ;
		//PagingResult<CaseAcline> pr = this.aclineDao.queryTemp(q);
		this.aclineDao.insertTemp(caseID);
		//PagingResult<CaseAcline> caseAcline = this.aclineDao.queryTemp(q) ;
		long l2 = System.currentTimeMillis() ;
		System.out.println("编号 "+caseID+ " 查询消耗："+((l2-l1)/1000)+"秒");
		counter.countDown() ;
		
	}

}


/**   
 * @filename: TestWorker   
 * @description: TODO  
 * @author java 小生 
 * @date 2013-2-27 上午11:32:28      
 */
public class TestWorker extends Thread{
   private CaseAclineService caseAclineService;
   private CountDownLatch counter;
   private int caseID ;
   TestWorker(CaseAclineService caseAclineService,CountDownLatch counter,int caseID ){
	   this.caseAclineService = caseAclineService ;
	   this.counter = counter ;
	   this.caseID = caseID ;
	  
   }
	
   @Override	
   public void run(){
	   //System.out.println(caseID);
	   caseAclineService.queryTemp(caseID, counter);
   }
}

  

/**   
 * @filename: CaseAclineServiceTest   
 * @description: TODO  
 * @author java 小生 
 * @date 2013-2-26 下午11:27:50      
 */
@RunWith(SpringJUnit4ClassRunner.class)
@ContextConfiguration(locations={"classpath:applicationContext.xml"})
public class CaseAclineServiceTest{
	CountDownLatch coun