假设场景:A与B表是一对多关系,现在多个A和多个B进行批量入库。
A的主键用某个序列JOB_SEQUENCE.nextval,B表的外键字段存A表的主键。
如果A和B在同一个事务保存里,应该怎么操作呢?
之前的做法是:
@H_301_8@ public static int newMeasurementJobId(IntHolder jobId) { Connection conn = getConnection(); if (conn == null) { logger.error("newMeasurementJobId:Failed to get DBConnection"); return 0; } Statement stmt = null; ResultSet rset = null; try { String sql = "select PM_JOB_SEQUENCE.nextval job_id from dual"; stmt = conn.createStatement(); rset = stmt.executeQuery(sql); if (rset.next()) { jobId.value = rset.getInt("job_id"); } return 1; } catch (sqlException e) { return 2; } finally { closeDataBaseConnection(conn,stmt,rset); } }然后for循环里调用newMeasurementJobId(IntHolder jobId)获取主键值,分别填充A和B表模型Bean的相应字段。
这个做法,有个问题是会大量open/close 数据库的IO,频繁操作对数据库的影响是非常大的。
若用UUID做主键是没有这个问题的,因为都是本地生成的。
那么有没有什么办法一次性获取大量的序列值呢。
有个非常绝妙的办法:
select PM_JOB_SEQUENCE.nextval job_id from (select 1 from all_objects where rownum <= 10)
其中all_objects为系统表,基本上都有几十万条数据,如果不够用,可以重复执行几次。
这样就可以一次获取10条递增的唯一序列值,且不用担心并发问题,oracle数据库已经帮你规避。
可以写个简单的测试程序,测试一下并发的场景:
假设有10个程序,同时获取同一个序列的5个值,看看是不是会有重复值呢?
Test线程类:
class Test implements Runnable { private String name; private List<String> list; public Test(String name,List<String> list){ this.name = name; this.list = list; } public void run() { String sql = "select PM_JOB_SEQUENCE.nextval job_id from (select 1 from all_objects where rownum <= 5)"; Connection conn = null; PreparedStatement pstmt = null; ResultSet rs = null; try { conn = dataSource.getConnection(); pstmt = conn.prepareStatement(sql); rs = pstmt.executeQuery(); while (rs.next()) { list.add(name+"_"+rs.getInt("job_id")); } } catch (sqlException e) { e.printStackTrace(); } finally { try { rs.close(); pstmt.close(); conn.close(); } catch (sqlException e) { e.printStackTrace(); } } } }测试方法:
public void test() throws Exception{ List<String> list = Collections.synchronizedList(new ArrayList<String>()); for (int i = 0; i < 10; i++) { Test test = new Test("Thread"+String.valueOf(i),list); Thread t = new Thread(test); t.start(); t.join(); } for(String val : list){ System.out.println(val); } System.out.println("==========================="); Collections.sort(list); for(String value : list){ System.out.println(value); } }运行结果:
Thread0_62443290 Thread0_62443291 Thread0_62443292 Thread0_62443293 Thread0_62443294 Thread1_62443295 Thread1_62443296 Thread1_62443297 Thread1_62443298 Thread1_62443299 Thread2_62443300 Thread2_62443301 Thread2_62443302 Thread2_62443303 Thread2_62443304 Thread3_62443305 Thread3_62443306 Thread3_62443307 Thread3_62443308 Thread3_62443309 Thread4_62443310 Thread4_62443311 Thread4_62443312 Thread4_62443313 Thread4_62443314 Thread5_62443315 Thread5_62443316 Thread5_62443317 Thread5_62443318 Thread5_62443319 Thread6_62443320 Thread6_62443321 Thread6_62443322 Thread6_62443323 Thread6_62443324 Thread7_62443325 Thread7_62443326 Thread7_62443327 Thread7_62443328 Thread7_62443329 Thread8_62443330 Thread8_62443331 Thread8_62443332 Thread8_62443333 Thread8_62443334 Thread9_62443335 Thread9_62443336 Thread9_62443337 Thread9_62443338 Thread9_62443339 =========================== Thread0_62443290 Thread0_62443291 Thread0_62443292 Thread0_62443293 Thread0_62443294 Thread1_62443295 Thread1_62443296 Thread1_62443297 Thread1_62443298 Thread1_62443299 Thread2_62443300 Thread2_62443301 Thread2_62443302 Thread2_62443303 Thread2_62443304 Thread3_62443305 Thread3_62443306 Thread3_62443307 Thread3_62443308 Thread3_62443309 Thread4_62443310 Thread4_62443311 Thread4_62443312 Thread4_62443313 Thread4_62443314 Thread5_62443315 Thread5_62443316 Thread5_62443317 Thread5_62443318 Thread5_62443319 Thread6_62443320 Thread6_62443321 Thread6_62443322 Thread6_62443323 Thread6_62443324 Thread7_62443325 Thread7_62443326 Thread7_62443327 Thread7_62443328 Thread7_62443329 Thread8_62443330 Thread8_62443331 Thread8_62443332 Thread8_62443333 Thread8_62443334 Thread9_62443335 Thread9_62443336 Thread9_62443337 Thread9_62443338 Thread9_62443339
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