[GitHub] [incubator-pinot] vincentchenjl commented on a change in pull request #5398: [TE] Added generic support for configuring Data Quality rules like SLA from Yaml

[GitBox <gi...@apache.org>]

vincentchenjl commented on a change in pull request #5398:
URL: https://github.com/apache/incubator-pinot/pull/5398#discussion_r428858170



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File path: thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/dataquality/components/DataSlaQualityChecker.java
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@@ -0,0 +1,216 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.pinot.thirdeye.detection.dataquality.components;
+
+import com.google.common.collect.ArrayListMultimap;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import org.apache.commons.lang3.StringUtils;
+import org.apache.pinot.thirdeye.anomaly.AnomalyType;
+import org.apache.pinot.thirdeye.common.time.TimeGranularity;
+import org.apache.pinot.thirdeye.constant.AnomalyResultSource;
+import org.apache.pinot.thirdeye.dataframe.DataFrame;
+import org.apache.pinot.thirdeye.dataframe.util.MetricSlice;
+import org.apache.pinot.thirdeye.datalayer.dto.DatasetConfigDTO;
+import org.apache.pinot.thirdeye.datalayer.dto.MergedAnomalyResultDTO;
+import org.apache.pinot.thirdeye.detection.DetectionUtils;
+import org.apache.pinot.thirdeye.detection.InputDataFetcher;
+import org.apache.pinot.thirdeye.detection.annotation.Components;
+import org.apache.pinot.thirdeye.detection.annotation.DetectionTag;
+import org.apache.pinot.thirdeye.detection.annotation.Param;
+import org.apache.pinot.thirdeye.detection.annotation.PresentationOption;
+import org.apache.pinot.thirdeye.detection.dataquality.spec.DataSlaQualityCheckerSpec;
+import org.apache.pinot.thirdeye.detection.spi.components.AnomalyDetector;
+import org.apache.pinot.thirdeye.detection.spi.components.BaselineProvider;
+import org.apache.pinot.thirdeye.detection.spi.model.DetectionResult;
+import org.apache.pinot.thirdeye.detection.spi.model.InputData;
+import org.apache.pinot.thirdeye.detection.spi.model.InputDataSpec;
+import org.apache.pinot.thirdeye.detection.spi.model.TimeSeries;
+import org.apache.pinot.thirdeye.rootcause.impl.MetricEntity;
+import org.joda.time.DateTime;
+import org.joda.time.DateTimeZone;
+import org.joda.time.Interval;
+import org.joda.time.Period;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+
+/**
+ * Performs data sla checks for the window and generates DATA_SLA anomalies.
+ *
+ * Data SLA is verified based on the following information.
+ * a. The dataset refresh timestamp updated by the event based data availability pipeline (if applicable).
+ * b. Otherwise, we will query the data source and run sla checks.
+ */
+@Components(title = "Data Sla Quality Checker",
+    type = "DATA_SLA",
+    tags = {DetectionTag.RULE_DETECTION},
+    description = "Checks if data is missing or not based on the configured sla",
+    presentation = {
+        @PresentationOption(name = "data sla", template = "is ${sla}")
+    },
+    params = {
+        @Param(name = "sla", placeholder = "value")
+    })
+public class DataSlaQualityChecker implements AnomalyDetector<DataSlaQualityCheckerSpec>, BaselineProvider<DataSlaQualityCheckerSpec> {
+  private static final Logger LOG = LoggerFactory.getLogger(DataSlaQualityChecker.class);
+
+  private String sla;
+  private InputDataFetcher dataFetcher;
+  private final String DEFAULT_DATA_SLA = "3_DAYS";

Review comment:
       Should we use Duration or TimeGranularity instead of String, since we are converting it anyway?




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