聊聊jdbc的batch操作-优快云博客

序

本文主要研究一下jdbc的batch的使用以及jpa的batch设置

batch

statement的batch操作，可以批量进行insert或update操作，提升操作性能，特别是在大数据量的insert或update的时候。

使用方式

    @Test
    public void testSqlInjectSafeBatch(){
        String sql = "insert into employee (name, city, phone) values (?, ?, ?)";

        Connection conn = null;
        PreparedStatement pstmt = null;

        try{
            conn = dataSource.getConnection();
            conn.setAutoCommit(false);
            pstmt = conn.prepareStatement(sql);

            for (int i=0;i<3;i++) {
                pstmt.setString(1,"name"+i);
                pstmt.setString(2,"city"+i);
                pstmt.setString(3,"iphone"+i);
                pstmt.addBatch();
            }
            pstmt.executeBatch();

            conn.commit();

        }catch (SQLException e){
            e.printStackTrace();
            try {
                conn.rollback();
            } catch (SQLException e1) {
                e1.printStackTrace();
            }
        }finally {
            DbUtils.closeQuietly(pstmt);
            DbUtils.closeQuietly(conn);
        }
    }
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主要就是每条操作参数设置完之后，调用addBatch方法，然后再所有操作都pstmt.addBatch()完之后，调用pstmt.executeBatch() 这种方式有个缺陷就是数据量大容易消耗内存，因此建议再分批次处理

@Test
    public void testSqlInjectSafeAndOOMSafeBatch(){
        String sql = "insert into employee (name, city, phone) values (?, ?, ?)";

        Connection conn = null;
        PreparedStatement pstmt = null;

        final int batchSize = 1000;
        int count = 0;

        try{
            conn = dataSource.getConnection();
            pstmt = conn.prepareStatement(sql);

            for (int i=0;i<10000;i++) {
                pstmt.setString(1,"name"+i);
                pstmt.setString(2,"city"+i);
                pstmt.setString(3,"iphone"+i);
                pstmt.addBatch();

                //小批量提交,避免OOM
                if(++count % batchSize == 0) {
                    pstmt.executeBatch();
                }
            }

            pstmt.executeBatch(); //提交剩余的数据

        }catch (SQLException e){
            e.printStackTrace();
        }finally {
            DbUtils.closeQuietly(pstmt);
            DbUtils.closeQuietly(conn);
        }
    }
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jpa的batch设置

spring:
  jpa:
    database-platform: org.hibernate.dialect.PostgreSQLDialect
    hibernate:
      ddl-auto: update
      naming:
        implicit-strategy: org.springframework.boot.orm.jpa.hibernate.SpringImplicitNamingStrategy
        physical-strategy: org.springframework.boot.orm.jpa.hibernate.SpringPhysicalNamingStrategy
    show-sql: true
    properties:
      hibernate:
        format_sql: true
        jdbc:
          batch_size: 5000
          batch_versioned_data: true
        order_inserts: true
        order_updates: true
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通过设置spring.jpa.properties.hibernate.jdbc.batch_size来设置批量

实例测试

    @Test
	public void testJpaBatch() {
		List<DemoUser> demoUsers = new ArrayList<>();
		for(int i=0;i<10;i++){
			DemoUser demoUser = new DemoUser();
			demoUser.setPrincipal("demo");
			demoUser.setAccessToken(UUID.randomUUID().toString());
			demoUser.setAuthType(UUID.randomUUID().toString());
			demoUser.setDeptName(UUID.randomUUID().toString());
			demoUser.setOrgName(UUID.randomUUID().toString());
			demoUsers.add(demoUser);
		}
		StopWatch stopWatch = new StopWatch("jpa batch");
		stopWatch.start();
		demoUserDao.save(demoUsers);
		stopWatch.stop();
		System.out.println(stopWatch.prettyPrint());
	}
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调整batch_size参数的测试结果

     没有设置批量
	 * StopWatch 'jpa batch': running time (millis) = 21383
	 -----------------------------------------
	 ms     %     Task name
	 -----------------------------------------
	 21383  100%

	 设置批量500
	 StopWatch 'jpa batch': running time (millis) = 16790
	 -----------------------------------------
	 ms     %     Task name
	 -----------------------------------------
	 16790  100%

	 批量1000
	 StopWatch 'jpa batch': running time (millis) = 12317
	 -----------------------------------------
	 ms     %     Task name
	 -----------------------------------------
	 12317  100%

	 批量5000
	 StopWatch 'jpa batch': running time (millis) = 13190
	 -----------------------------------------
	 ms     %     Task name
	 -----------------------------------------
	 13190  100%
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