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Posted to commits@pinot.apache.org by xh...@apache.org on 2019/04/02 17:18:23 UTC
[incubator-pinot] branch revert_early_termination created (now
b888e35)
This is an automated email from the ASF dual-hosted git repository.
xhsun pushed a change to branch revert_early_termination
in repository https://gitbox.apache.org/repos/asf/incubator-pinot.git.
at b888e35 [TE] revert early termination in detection loop
This branch includes the following new commits:
new b888e35 [TE] revert early termination in detection loop
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[incubator-pinot] 01/01: [TE] revert early termination in detection
loop
Posted by xh...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
xhsun pushed a commit to branch revert_early_termination
in repository https://gitbox.apache.org/repos/asf/incubator-pinot.git
commit b888e35495db677ce8170ccb24a9ac3ce22f6fde
Author: Xiaohui Sun <xh...@xhsun-mn3.linkedin.biz>
AuthorDate: Tue Apr 2 10:18:05 2019 -0700
[TE] revert early termination in detection loop
---
.../detection/wrapper/AnomalyDetectorWrapper.java | 25 +++++-----------------
1 file changed, 5 insertions(+), 20 deletions(-)
diff --git a/thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/wrapper/AnomalyDetectorWrapper.java b/thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/wrapper/AnomalyDetectorWrapper.java
index b888379..909c47a 100644
--- a/thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/wrapper/AnomalyDetectorWrapper.java
+++ b/thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/wrapper/AnomalyDetectorWrapper.java
@@ -160,9 +160,12 @@ public class AnomalyDetectorWrapper extends DetectionPipeline {
List<MergedAnomalyResultDTO> anomalies = new ArrayList<>();
int totalWindows = monitoringWindows.size();
int successWindows = 0;
- Exception lastException = null;
for (int i = 0; i < totalWindows; i++) {
- earlyTerminate(i, successWindows, totalWindows, lastException);
+ if (i == EARLY_TERMINATE_WINDOW && successWindows == 0) {
+ LOG.error("Successive first {}/{} detection windows failed for config {} metricUrn {}. Discard remaining windows",
+ EARLY_TERMINATE_WINDOW, totalWindows, config.getId(), metricUrn);
+ break;
+ }
// run detection
Interval window = monitoringWindows.get(i);
@@ -177,22 +180,14 @@ public class AnomalyDetectorWrapper extends DetectionPipeline {
successWindows++;
}
catch (DetectorDataInsufficientException e) {
- lastException = e;
LOG.warn("[DetectionConfigID{}] Insufficient data ro run detection for window {} to {}.", this.config.getId(), window.getStart(), window.getEnd());
}
catch (Exception e) {
- lastException = e;
LOG.warn("[DetectionConfigID{}] detecting anomalies for window {} to {} failed.", this.config.getId(), window.getStart(), window.getEnd(), e);
}
anomalies.addAll(anomaliesForOneWindow);
}
- // throw exception if all windows failed
- if (successWindows == 0 && totalWindows > 0) {
- LOG.error("All {} detection windows failed for config {} metricUrn {}.", totalWindows, config.getId(), metricUrn);
- throw new DetectorException("All " + totalWindows + " detection windows failed.", lastException);
- }
-
for (MergedAnomalyResultDTO anomaly : anomalies) {
anomaly.setDetectionConfigId(this.config.getId());
anomaly.setMetricUrn(this.metricUrn);
@@ -206,16 +201,6 @@ public class AnomalyDetectorWrapper extends DetectionPipeline {
Collectors.toList()), lastTimeStamp);
}
- private void earlyTerminate(int currentWindows, int successWindows, int totalWindows, Exception lastException)
- throws DetectorException {
- // early termination if first of the EARLY_TERMINATE_WINDOW all failed
- if (currentWindows == EARLY_TERMINATE_WINDOW && successWindows == 0) {
- LOG.error("Successive first {} detection windows failed for config {} metricUrn {}.", EARLY_TERMINATE_WINDOW, config.getId(), metricUrn);
- throw new DetectorException(String.format("Successive first %d/%d detection windows failed.", EARLY_TERMINATE_WINDOW, totalWindows),
- lastException);
- }
- }
-
// guess-timate next time stamp
// there are two cases. If the data is complete, next detection starts from the end time of this detection
// If data is incomplete, next detection starts from the latest available data's time stamp plus the one time granularity.
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