DATAX
DataX 是阿里巴巴集团内被广泛使用的离线数据同步工具/平台,实现包括 MySQL、Oracle、SqlServer、Postgre、HDFS、Hive、ADS、HBase、TableStore(OTS)、MaxCompute(ODPS)、DRDS 等各种异构数据源之间高效的数据同步功能。
datax的详细介绍
引言
因为业务需要,需要使用到datax把数据从文本写入到数据库,原来的做法都是使用python通过datax.py去调用脚本,阿文为了能更好的管控datax的任务,阿文要求我们对datax进行改造,使用java集成的方式去调用datax,并返回任务执行的详细信息。
datax源码跟踪
从github下完源码开始改造,datax的启动类在datax-core包下Engine类的entry方法,该方法是一个静态方法。
public static void entry(final String[] args) throws Throwable { Options options = new Options(); options.addOption("job", true, "Job config."); options.addOption("jobid", true, "Job unique id."); options.addOption("mode", true, "Job runtime mode."); BasicParser parser = new BasicParser(); CommandLine cl = parser.parse(options, args); String jobPath = cl.getOptionValue("job"); // 如果用户没有明确指定jobid, 则 datax.py 会指定 jobid 默认值为-1 String jobIdString = cl.getOptionValue("jobid"); RUNTIME_MODE = cl.getOptionValue("mode"); Configuration configuration = ConfigParser.parse(jobPath); long jobId; if (!"-1".equalsIgnoreCase(jobIdString)) { jobId = Long.parseLong(jobIdString); } else { // only for dsc & ds & datax 3 update String dscJobUrlPatternString = "/instance/(\\d{1,})/config.xml"; String dsJobUrlPatternString = "/inner/job/(\\d{1,})/config"; String dsTaskGroupUrlPatternString = "/inner/job/(\\d{1,})/taskGroup/"; List<String> patternStringList = Arrays.asList(dscJobUrlPatternString, dsJobUrlPatternString, dsTaskGroupUrlPatternString); jobId = parseJobIdFromUrl(patternStringList, jobPath); } boolean isStandAloneMode = "standalone".equalsIgnoreCase(RUNTIME_MODE); if (!isStandAloneMode && jobId == -1) { // 如果不是 standalone 模式,那么 jobId 一定不能为-1 throw DataXException.asDataXException(FrameworkErrorCode.CONFIG_ERROR, "非 standalone 模式必须在 URL 中提供有效的 jobId."); } configuration.set(CoreConstant.DATAX_CORE_CONTAINER_JOB_ID, jobId); //打印vmInfo VMInfo vmInfo = VMInfo.getVmInfo(); if (vmInfo != null) { LOG.info(vmInfo.toString()); } LOG.info("\n" + Engine.filterJobConfiguration(configuration) + "\n"); LOG.debug(configuration.toJSON()); ConfigurationValidate.doValidate(configuration); Engine engine = new Engine(); engine.start(configuration); }
里面最后通过调用engine.start(configuration) 开始启动,我们点进去,最后会发现在里面是调用JobContainer 的start() 方法。
@Override public void start() { LOG.info("DataX jobContainer starts job."); boolean hasException = false; boolean isDryRun = false; try { this.startTimeStamp = System.currentTimeMillis(); isDryRun = configuration.getBool(CoreConstant.DATAX_JOB_SETTING_DRYRUN, false); if (isDryRun) { LOG.info("jobContainer starts to do preCheck ..."); this.preCheck(); } else { userConf = configuration.clone(); LOG.debug("jobContainer starts to do preHandle ..."); this.preHandle(); LOG.debug("jobContainer starts to do init ..."); this.init(); LOG.info("jobContainer starts to do prepare ..."); this.prepare(); LOG.info("jobContainer starts to do split ..."); this.totalStage = this.split(); LOG.info("jobContainer starts to do schedule ..."); this.schedule(); LOG.debug("jobContainer starts to do post ..."); this.post(); LOG.debug("jobContainer starts to do postHandle ..."); this.postHandle(); LOG.info("DataX jobId [{}] completed successfully.", this.jobId); this.invokeHooks(); } } catch (Throwable e) { LOG.error("Exception when job run", e); hasException = true; if (e instanceof OutOfMemoryError) { this.destroy(); System.gc(); } if (super.getContainerCommunicator() == null) { // 由于 containerCollector 是在 scheduler() 中初始化的,所以当在 scheduler() 之前出现异常时,需要在此处对 containerCollector 进行初始化 AbstractContainerCommunicator tempContainerCollector; // standalone tempContainerCollector = new StandAloneJobContainerCommunicator(configuration); super.setContainerCommunicator(tempContainerCollector); } Communication communication = super.getContainerCommunicator().collect(); // 汇报前的状态,不需要手动进行设置 // communication.setState(State.FAILED); communication.setThrowable(e); communication.setTimestamp(this.endTimeStamp); Communication tempComm = new Communication(); tempComm.setTimestamp(this.startTransferTimeStamp); Communication reportCommunication = CommunicationTool.getReportCommunication(communication, tempComm, this.totalStage); super.getContainerCommunicator().report(reportCommunication); throw DataXException.asDataXException( FrameworkErrorCode.RUNTIME_ERROR, e); } finally { if (!isDryRun) { this.destroy(); this.endTimeStamp = System.currentTimeMillis(); if (!hasException) { //最后打印cpu的平均消耗,GC的统计 VMInfo vmInfo = VMInfo.getVmInfo(); if (vmInfo != null) { vmInfo.getDelta(false); LOG.info(vmInfo.totalString()); } LOG.info(PerfTrace.getInstance().summarizeNoException()); this.logStatistics(); } } } }
而我们需要的任务信息就在this.logStatistics() 中
private void logStatistics() { long totalCosts = (this.endTimeStamp - this.startTimeStamp) / 1000; long transferCosts = (this.endTransferTimeStamp - this.startTransferTimeStamp) / 1000; if (0L == transferCosts) { transferCosts = 1L; } if (super.getContainerCommunicator() == null) { return; } Communication communication = super.getContainerCommunicator().collect(); communication.setTimestamp(this.endTimeStamp); Communication tempComm = new Communication(); tempComm.setTimestamp(this.startTransferTimeStamp); Communication reportCommunication = CommunicationTool.getReportCommunication(communication, tempComm, this.totalStage); // 字节速率 long byteSpeedPerSecond = communication.getLongCounter(CommunicationTool.READ_SUCCEED_BYTES) / transferCosts; long recordSpeedPerSecond = communication.getLongCounter(CommunicationTool.READ_SUCCEED_RECORDS) / transferCosts; reportCommunication.setLongCounter(CommunicationTool.BYTE_SPEED, byteSpeedPerSecond); reportCommunication.setLongCounter(CommunicationTool.RECORD_SPEED, recordSpeedPerSecond); super.getContainerCommunicator().report(reportCommunication); LOG.info(String.format( "\n" + "%-26s: %-18s\n" + "%-26s: %-18s\n" + "%-26s: %19s\n" + "%-26s: %19s\n" + "%-26s: %19s\n" + "%-26s: %19s\n" + "%-26s: %19s\n", "任务启动时刻", dateFormat.format(startTimeStamp), "任务结束时刻", dateFormat.format(endTimeStamp), "任务总计耗时", String.valueOf(totalCosts) + "s", "任务平均流量", StrUtil.stringify(byteSpeedPerSecond) + "/s", "记录写入速度", String.valueOf(recordSpeedPerSecond) + "rec/s", "读出记录总数", String.valueOf(CommunicationTool.getTotalReadRecords(communication)), "读写失败总数", String.valueOf(CommunicationTool.getTotalErrorRecords(communication)) )); LOG.info("task-total-info:" + dateFormat.format(startTimeStamp) + "|" + dateFormat.format(endTimeStamp) + "|" + String.valueOf(totalCosts) + "|" + StrUtil.stringify(byteSpeedPerSecond) + "|" + String.valueOf(recordSpeedPerSecond) + "|" + String.valueOf(CommunicationTool.getTotalReadRecords(communication)) + "|" + String.valueOf(CommunicationTool.getTotalErrorRecords(communication)) ); if (communication.getLongCounter(CommunicationTool.TRANSFORMER_SUCCEED_RECORDS) > 0 || communication.getLongCounter(CommunicationTool.TRANSFORMER_FAILED_RECORDS) > 0 || communication.getLongCounter(CommunicationTool.TRANSFORMER_FILTER_RECORDS) > 0) { LOG.info(String.format( "\n" + "%-26s: %19s\n" + "%-26s: %19s\n" + "%-26s: %19s\n", "Transformer成功记录总数", communication.getLongCounter(CommunicationTool.TRANSFORMER_SUCCEED_RECORDS), "Transformer失败记录总数", communication.getLongCounter(CommunicationTool.TRANSFORMER_FAILED_RECORDS), "Transformer过滤记录总数", communication.getLongCounter(CommunicationTool.TRANSFORMER_FILTER_RECORDS) )); } }
改造开始
新增返回实体DataxResult (get、set省略)
public class DataxResult { //任务启动时刻 private long startTimeStamp; //任务结束时刻 private long endTimeStamp; //任务总时耗 private long totalCosts; //任务平均流量 private long byteSpeedPerSecond; //记录写入速度 private long recordSpeedPerSecond; //读出记录总数 private long totalReadRecords; //读写失败总数 private long totalErrorRecords; //成功记录总数 private long transformerSucceedRecords; // 失败记录总数 private long transformerFailedRecords; // 过滤记录总数 private long transformerFilterRecords; //字节数 private long readSucceedBytes; //转换开始时间 private long endTransferTimeStamp; //转换结束时间 private long startTransferTimeStamp; //转换总耗时 private long transferCosts;
重写logStatistics方法,返回该实体。
private DataxResult logStatistics(DataxResult resultMsg) { long totalCosts = (this.endTimeStamp - this.startTimeStamp) / 1000; long transferCosts = (this.endTransferTimeStamp - this.startTransferTimeStamp) / 1000; if (0L == transferCosts) { transferCosts = 1L; } if (super.getContainerCommunicator() == null) { return resultMsg; } Communication communication = super.getContainerCommunicator().collect(); long byteSpeedPerSecond = communication.getLongCounter(CommunicationTool.READ_SUCCEED_BYTES) / transferCosts; long recordSpeedPerSecond = communication.getLongCounter(CommunicationTool.READ_SUCCEED_RECORDS) / transferCosts; return resultMsg.getResultMsg(startTimeStamp, endTimeStamp, totalCosts, byteSpeedPerSecond, recordSpeedPerSecond, communication.getLongCounter(CommunicationTool.TRANSFORMER_SUCCEED_RECORDS), communication.getLongCounter(CommunicationTool.TRANSFORMER_FAILED_RECORDS), communication.getLongCounter(CommunicationTool.TRANSFORMER_FILTER_RECORDS), communication.getLongCounter(CommunicationTool.TRANSFORMER_FAILED_RECORDS), communication.getLongCounter(CommunicationTool.TRANSFORMER_FILTER_RECORDS), communication.getLongCounter(CommunicationTool.READ_SUCCEED_BYTES), this.endTransferTimeStamp, this.startTransferTimeStamp, transferCosts ); }
还需要重写JobContainer的**start()**方法。
@Override public DataxResult start(DataxResult dataxResult) { ... DataxResult result = new DataxResult(); result = logStatistics(dataxResult); ... return result; }
然后在Engine 类中添加模拟测试方法mockentry
public DataxResult mockstart(Configuration allConf) { ... DataxResult dataxResult = new DataxResult(); return container.start(dataxResult); }
开始测试
在com.alibaba.datax.core.util.container.CoreConstant里修改datax_home 为本地路径
该datax_home路径下有以下几个目录
public class test { public static void main(String[] args) { String[] datxArgs = {"-job", CoreConstant.DATAX_HOME + "\\job\\job2.json", "-mode", "standalone", "-jobid", "-1"}; try { DataxResult dataxResult= Engine.mockentry(datxArgs); } catch (Throwable e) { e.printStackTrace(); } } }
执行结果为
3
大功告成!
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