Examples with ThroughputInfo com.alibaba.otter.manager.biz.statistics.throughput.param.ThroughputInfo used on opensource projects

Example 1 with ThroughputInfo

use of com.alibaba.otter.manager.biz.statistics.throughput.param.ThroughputInfo in project otter by alibaba.

the class ThroughputStatServiceImpl method listRealtimeThroughput.

/**
     * 3种时间间隔的统计信息
     */
public Map<AnalysisType, ThroughputInfo> listRealtimeThroughput(RealtimeThroughputCondition condition) {
    Assert.assertNotNull(condition);
    Map<AnalysisType, ThroughputInfo> throughputInfos = new HashMap<AnalysisType, ThroughputInfo>();
    TimelineThroughputCondition timelineCondition = new TimelineThroughputCondition();
    Date realtime = new Date(System.currentTimeMillis());
    timelineCondition.setPipelineId(condition.getPipelineId());
    timelineCondition.setType(condition.getType());
    timelineCondition.setStart(new Date(realtime.getTime() - condition.getMax() * 60 * 1000));
    timelineCondition.setEnd(realtime);
    List<ThroughputStatDO> throughputStatDOs = throughputDao.listTimelineThroughputStat(timelineCondition);
    for (AnalysisType analysisType : condition.getAnalysisType()) {
        ThroughputInfo throughputInfo = new ThroughputInfo();
        List<ThroughputStat> throughputStat = new ArrayList<ThroughputStat>();
        for (ThroughputStatDO throughputStatDO : throughputStatDOs) {
            if (realtime.getTime() - throughputStatDO.getEndTime().getTime() <= analysisType.getValue() * 60 * 1000) {
                throughputStat.add(throughputStatDOToModel(throughputStatDO));
            }
        }
        throughputInfo.setItems(throughputStat);
        throughputInfo.setSeconds(analysisType.getValue() * 60L);
        throughputInfos.put(analysisType, throughputInfo);
    }
    return throughputInfos;
}

Example 2 with ThroughputInfo

use of com.alibaba.otter.manager.biz.statistics.throughput.param.ThroughputInfo in project otter by alibaba.

the class ThroughputStatServiceImpl method listTimelineThroughput.

/**
     * <pre>
     * 列出pipeLineId下，start-end时间段下的throughputStat 
     * 首先从数据库中取出这一段时间所以数据，该数据都是根据end_time倒排序的, 每隔1分钟将这些数据分组
     * </pre>
     */
public Map<Long, ThroughputInfo> listTimelineThroughput(TimelineThroughputCondition condition) {
    Assert.assertNotNull(condition);
    Map<Long, ThroughputInfo> throughputInfos = new LinkedHashMap<Long, ThroughputInfo>();
    List<ThroughputStatDO> throughputStatDOs = throughputDao.listTimelineThroughputStat(condition);
    int size = throughputStatDOs.size();
    int k = size - 1;
    for (Long i = condition.getStart().getTime(); i <= condition.getEnd().getTime(); i += 60 * 1000) {
        ThroughputInfo throughputInfo = new ThroughputInfo();
        List<ThroughputStat> throughputStat = new ArrayList<ThroughputStat>();
        // 取出每个时间点i以内的数据，k是一个游标，每次遍历时前面已经取过了的数据就不用再遍历了
        for (int j = k; j >= 0; --j) {
            if ((i - throughputStatDOs.get(j).getEndTime().getTime() <= 60 * 1000) && (i - throughputStatDOs.get(j).getEndTime().getTime() >= 0)) {
                throughputStat.add(throughputStatDOToModel(throughputStatDOs.get(j)));
                k = j - 1;
            } else // 如果不满足if条件，则后面的数据也不用再遍历
            {
                break;
            }
        }
        if (throughputStat.size() > 0) {
            throughputInfo.setItems(throughputStat);
            throughputInfo.setSeconds(1 * 60L);
            throughputInfos.put(i, throughputInfo);
        }
    }
    return throughputInfos;
}

Example 3 with ThroughputInfo

use of com.alibaba.otter.manager.biz.statistics.throughput.param.ThroughputInfo in project otter by alibaba.

the class AnalysisThroughputHistory method execute.

public void execute(@Param("d5221") String startTime, @Param("d5222") String endTime, @Param("pipelineId") Long pipelineId, HttpSession session, Context context) throws Exception {
    Date end = null;
    Date start = null;
    SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm");
    if (StringUtils.isEmpty(startTime) || StringUtils.isEmpty(endTime)) {
        start = new Date(System.currentTimeMillis() / 60000 * 60000 - 24 * 60 * 60 * 1000);
        end = new Date(System.currentTimeMillis() / 60000 * 60000);
    } else {
        // 当前24小时，时间取整分钟
        sdf.setLenient(false);
        if (null != startTime && null != endTime) {
            start = sdf.parse(startTime);
            end = sdf.parse(endTime);
        }
    }
    Channel channel = channelService.findByPipelineId(pipelineId);
    Map<Long, ThroughputInfo> throughputInfos1 = new LinkedHashMap<Long, ThroughputInfo>();
    Map<Long, ThroughputInfo> throughputInfos2 = new LinkedHashMap<Long, ThroughputInfo>();
    TimelineThroughputCondition condition1 = new TimelineThroughputCondition();
    TimelineThroughputCondition condition2 = new TimelineThroughputCondition();
    if (null != start && null != end) {
        condition1.setStart(start);
        condition1.setEnd(end);
        condition1.setType(ThroughputType.ROW);
        condition1.setPipelineId(pipelineId);
        condition2.setStart(start);
        condition2.setEnd(end);
        condition2.setType(ThroughputType.FILE);
        condition2.setPipelineId(pipelineId);
        throughputInfos1 = throughputStatService.listTimelineThroughput(condition1);
        throughputInfos2 = throughputStatService.listTimelineThroughput(condition2);
    }
    Long totalRecord1 = 0L;
    Long totalRecord2 = 0L;
    Long totalSize1 = 0L;
    Long totalSize2 = 0L;
    for (ThroughputInfo info : throughputInfos1.values()) {
        totalRecord1 += info.getNumber();
        totalSize1 += info.getSize();
    }
    for (ThroughputInfo info : throughputInfos2.values()) {
        totalRecord2 += info.getNumber();
        totalSize2 += info.getSize();
    }
    context.put("throughputInfos1", throughputInfos1);
    context.put("throughputInfos2", throughputInfos2);
    context.put("totalRecord1", totalRecord1);
    context.put("totalRecord2", totalRecord2);
    context.put("totalSize1", totalSize1);
    context.put("totalSize2", totalSize2);
    context.put("channel", channel);
    context.put("pipelineId", pipelineId);
    context.put("start", sdf.format(start));
    context.put("end", sdf.format(end));
}

Example 4 with ThroughputInfo

use of com.alibaba.otter.manager.biz.statistics.throughput.param.ThroughputInfo in project otter by alibaba.

the class AnalysisThroughputStat method execute.

public void execute(@Param("pipelineId") Long pipelineId, Context context) throws Exception {
    Channel channel = channelService.findByPipelineId(pipelineId);
    RealtimeThroughputCondition condition1 = new RealtimeThroughputCondition();
    RealtimeThroughputCondition condition2 = new RealtimeThroughputCondition();
    ThroughputCondition condition11 = new ThroughputCondition();
    ThroughputCondition condition22 = new ThroughputCondition();
    List<AnalysisType> analysisType = new ArrayList<AnalysisType>();
    analysisType.add(AnalysisType.ONE_MINUTE);
    analysisType.add(AnalysisType.FIVE_MINUTE);
    analysisType.add(AnalysisType.FIFTEEN_MINUTE);
    condition1.setPipelineId(pipelineId);
    condition1.setAnalysisType(analysisType);
    condition1.setType(ThroughputType.FILE);
    condition2.setPipelineId(pipelineId);
    condition2.setAnalysisType(analysisType);
    condition2.setType(ThroughputType.ROW);
    condition11.setPipelineId(pipelineId);
    condition11.setType(ThroughputType.FILE);
    condition22.setPipelineId(pipelineId);
    condition22.setType(ThroughputType.ROW);
    Map<AnalysisType, ThroughputInfo> throughputInfos1 = throughputStatService.listRealtimeThroughput(condition1);
    Map<AnalysisType, ThroughputInfo> throughputInfos2 = throughputStatService.listRealtimeThroughput(condition2);
    ThroughputStat throughputStat1 = throughputStatService.findThroughputStatByPipelineId(condition11);
    ThroughputStat throughputStat2 = throughputStatService.findThroughputStatByPipelineId(condition22);
    context.put("throughputInfos1", throughputInfos1);
    context.put("throughputInfos2", throughputInfos2);
    context.put("channel", channel);
    context.put("pipelineId", pipelineId);
    context.put("throughputStat1", throughputStat1);
    context.put("throughputStat2", throughputStat2);
    context.put("one", AnalysisType.ONE_MINUTE);
    context.put("five", AnalysisType.FIVE_MINUTE);
    context.put("fifteen", AnalysisType.FIFTEEN_MINUTE);
}