1. 程式人生 > >java中對於大量資料採用批量處理來提高效率

java中對於大量資料採用批量處理來提高效率

  設計的話, 是在dao層寫批量新增的方法,以及實現類dao的實現類, 在service呼叫這個dao就可以了!   不過最終走的還是單個只不過是集合的遍歷, 所以不用再mapper.xml裡面配置方法。

IReconBankOrderCpsBatchDao裡面的方法:

public interface IReconBankOrderCpsBatchDao {
	/**
	 * 儲存多條記錄
	 * 
	 * @param l_eos : 交易對賬-控制表-EO列表
	 */
	void saveAll(List<ReconBankOrderCpsEo> l_eos);

	/**
	 * 批量更新記錄
	 * @param l_eos : 交易對賬-控制表-EO列表
	 */
	void batchUpdate(List<ReconBankOrderCpsEo> l_eos);

	/**
	 * 批量刪除
	 * @param eos
	 */
	void batchDelete(List<ReconBankOrderCpsEo> eos);

	
}

dao的實現類:

@Repository("reconBankOrderCpsBatchDao")
public class ReconBankOrderCpsBatchDaoImpl implements
		IReconBankOrderCpsBatchDao {
	static Logger logger = LogManager.getLogger(ReconBankOrderCpsBatchDaoImpl.class);
	
	@Resource(name = "reconTransBaseSqlSessionTemplate")
	private SqlSessionTemplate sqlSessionTemplate;
	
	@Override
	public void saveAll(List<ReconBankOrderCpsEo> l_eos) {
		SqlSession session = sqlSessionTemplate.getSqlSessionFactory().openSession(ExecutorType.BATCH, false);
		IReconBankOrderCpsDao dao = session.getMapper(IReconBankOrderCpsDao.class);
		int size = l_eos.size();
		try {
			for (int i = 0; i < size; i++) {
				dao.save(l_eos.get(i));
				if (i % 1000 == 0 || i == size - 1) {
					//手動每1000個一提交,提交後無法回滾
					session.commit();
					//清理快取,防止溢位
					session.clearCache();
				}
			}
		} catch (Exception e) {
			logger.error("批量儲存失敗:" ,e);
			session.rollback();
		} finally {
			session.close();
		}
	}

	@Override
	public void batchUpdate(List<ReconBankOrderCpsEo> l_eos) {
		SqlSession session = sqlSessionTemplate.getSqlSessionFactory().openSession(ExecutorType.BATCH, false);
		IReconBankOrderCpsDao dao = session.getMapper(IReconBankOrderCpsDao.class);
		int size = l_eos.size();
		try {
			for (int i = 0; i < size; i++) {
				dao.update(l_eos.get(i));
				if (i % 500 == 0 || i == size - 1) {
					//手動每500個一提交,提交後無法回滾
					session.commit();
					//清理快取,防止溢位
					session.clearCache();
				}
			}
		} catch (Exception e) {
			session.rollback();
		} finally {
			session.close();
		}
	}

	@Override
	public void batchDelete(List<ReconBankOrderCpsEo> eos) {
		SqlSession session = sqlSessionTemplate.getSqlSessionFactory().openSession(ExecutorType.BATCH, false);
		IReconBankOrderCpsDao dao = session.getMapper(IReconBankOrderCpsDao.class);
		int size = eos.size();
		try {
			for (int i = 0; i < size; i++) {
				dao.delete(eos.get(i).getBankOrderId());
				if (i % 1000 == 0 || i == size - 1) {
					//手動每1000個一提交,提交後無法回滾
					session.commit();
					//清理快取,防止溢位
					session.clearCache();
				}
			}
		} catch (Exception e) {
			session.rollback();
		} finally {
			session.close();
		}
	}

}

使用的時候只需要在service裡面呼叫dao就可以了。

對於批量新增, 也可以在mapper.xml中配置方法, 實現批量新增。

<!-- 儲存多條記錄 -->
	<insert id="saveAll" parameterType="java.util.List">
		INSERT INTO RECONCAV.T_CBS_RECON_BANKORDER_HANDLE
		<trim prefix="(" suffix=")" >
			<include refid="allColumns" />
		</trim>
		SELECT RECONCAV.SEQ_bankorder_hd_tmp.NEXTVAL,RC.* from(
		<foreach collection="list" item="eo" index="index" separator="union all">
			SELECT
			#{eo.reconId			,jdbcType=VARCHAR},
			#{eo.reconDate			,jdbcType=TIMESTAMP},
			#{eo.orderDate			,jdbcType=TIMESTAMP},
			#{eo.bankTransType		,jdbcType=NUMERIC},
			#{eo.bankAcctId			,jdbcType=VARCHAR},
			#{eo.productNo			,jdbcType=NUMERIC},
			#{eo.bankNo				,jdbcType=NUMERIC},
			#{eo.bankName			,jdbcType=VARCHAR},
			#{eo.channelNo			,jdbcType=VARCHAR},
			#{eo.channelName		,jdbcType=VARCHAR},
			#{eo.merchantCode		,jdbcType=VARCHAR},
			#{eo.orderAmount		,jdbcType=NUMERIC},
			#{eo.cost				,jdbcType=NUMERIC},
			#{eo.settleAmount		,jdbcType=NUMERIC},
			#{eo.fundsReconStatus	,jdbcType=NUMERIC},
			#{eo.aprrovalStatus		,jdbcType=NUMERIC},
			#{eo.submitBy			,jdbcType=VARCHAR},
			#{eo.submitDetail		,jdbcType=VARCHAR},
			#{eo.submitTime			,jdbcType=TIMESTAMP},
			#{eo.approvalBy			,jdbcType=VARCHAR},
			#{eo.aprrovalDetail		,jdbcType=VARCHAR},
			#{eo.aprrovalTime		,jdbcType=TIMESTAMP},
			#{eo.memo				,jdbcType=VARCHAR},
			#{eo.crtTime			,jdbcType=TIMESTAMP},
			#{eo.updTime			,jdbcType=TIMESTAMP},
			#{eo.uploadId			,jdbcType=NUMERIC},
			#{eo.oraTid			    ,jdbcType=NUMERIC},
			#{eo.idTxn			    ,jdbcType=VARCHAR},
			#{eo.errorTransCode	    ,jdbcType=VARCHAR},
			#{eo.oldTransType	    ,jdbcType=NUMERIC},
			#{eo.accountBankName    ,jdbcType=VARCHAR},
			#{eo.accountBankFullName ,jdbcType=VARCHAR},
			#{eo.payee               ,jdbcType=VARCHAR},
			#{eo.failReason         ,jdbcType=VARCHAR},
			#{eo.bankReturnDate     ,jdbcType=TIMESTAMP},
			#{eo.accountBank        ,jdbcType=VARCHAR},
			#{eo.traceNo        ,jdbcType=VARCHAR}
			FROM DUAL
		</foreach>
		) RC
	</insert>