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/*
* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
* or more contributor license agreements. Licensed under the Elastic License
* 2.0; you may not use this file except in compliance with the Elastic License
* 2.0.
*/
package org.elasticsearch.xpack.core.ml.job.results;
import org.elasticsearch.index.get.GetResult;
import org.elasticsearch.xpack.core.ml.datafeed.DatafeedTimingStats;
import org.elasticsearch.xpack.core.ml.job.config.Detector;
import org.elasticsearch.xpack.core.ml.job.config.Job;
import org.elasticsearch.xpack.core.ml.job.persistence.ElasticsearchMappings;
import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.DataCounts;
import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.ModelSizeStats;
import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.ModelSnapshot;
import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.ModelSnapshotField;
import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.TimingStats;
import org.elasticsearch.xpack.core.ml.utils.ExponentialAverageCalculationContext;
import java.util.Arrays;
import java.util.HashSet;
import java.util.Set;
import java.util.regex.Pattern;
/**
* Defines the field names that we use for our results.
* Fields from the raw data with these names are not added to any result. Even
* different types of results will not have raw data fields with reserved names
* added to them, as it could create confusion if in some results a given field
* contains raw data and in others it contains some aspect of our output.
*/
public final class ReservedFieldNames {
private static final Pattern DOT_PATTERN = Pattern.compile("\\.");
/**
* This array should be updated to contain all the field names that appear
* in any documents we store in our results index. (The reason it's any
* documents we store and not just results documents is that Elasticsearch
* 2.x requires mappings for given fields be consistent across all types
* in a given index.)
*/
private static final String[] RESERVED_RESULT_FIELD_NAME_ARRAY = {
ElasticsearchMappings.ALL_FIELD_VALUES,
Job.ID.getPreferredName(),
AnomalyCause.PROBABILITY.getPreferredName(),
AnomalyCause.OVER_FIELD_NAME.getPreferredName(),
AnomalyCause.OVER_FIELD_VALUE.getPreferredName(),
AnomalyCause.BY_FIELD_NAME.getPreferredName(),
AnomalyCause.BY_FIELD_VALUE.getPreferredName(),
AnomalyCause.CORRELATED_BY_FIELD_VALUE.getPreferredName(),
AnomalyCause.PARTITION_FIELD_NAME.getPreferredName(),
AnomalyCause.PARTITION_FIELD_VALUE.getPreferredName(),
AnomalyCause.FUNCTION.getPreferredName(),
AnomalyCause.FUNCTION_DESCRIPTION.getPreferredName(),
AnomalyCause.TYPICAL.getPreferredName(),
AnomalyCause.ACTUAL.getPreferredName(),
AnomalyCause.GEO_RESULTS.getPreferredName(),
AnomalyCause.INFLUENCERS.getPreferredName(),
AnomalyCause.FIELD_NAME.getPreferredName(),
AnomalyRecord.PROBABILITY.getPreferredName(),
AnomalyRecord.MULTI_BUCKET_IMPACT.getPreferredName(),
AnomalyRecord.BY_FIELD_NAME.getPreferredName(),
AnomalyRecord.BY_FIELD_VALUE.getPreferredName(),
AnomalyRecord.CORRELATED_BY_FIELD_VALUE.getPreferredName(),
AnomalyRecord.PARTITION_FIELD_NAME.getPreferredName(),
AnomalyRecord.PARTITION_FIELD_VALUE.getPreferredName(),
AnomalyRecord.FUNCTION.getPreferredName(),
AnomalyRecord.FUNCTION_DESCRIPTION.getPreferredName(),
AnomalyRecord.TYPICAL.getPreferredName(),
AnomalyRecord.ACTUAL.getPreferredName(),
AnomalyRecord.GEO_RESULTS.getPreferredName(),
AnomalyRecord.INFLUENCERS.getPreferredName(),
AnomalyRecord.FIELD_NAME.getPreferredName(),
AnomalyRecord.OVER_FIELD_NAME.getPreferredName(),
AnomalyRecord.OVER_FIELD_VALUE.getPreferredName(),
AnomalyRecord.CAUSES.getPreferredName(),
AnomalyRecord.RECORD_SCORE.getPreferredName(),
AnomalyRecord.INITIAL_RECORD_SCORE.getPreferredName(),
AnomalyRecord.BUCKET_SPAN.getPreferredName(),
GeoResults.TYPICAL_POINT.getPreferredName(),
GeoResults.ACTUAL_POINT.getPreferredName(),
Bucket.ANOMALY_SCORE.getPreferredName(),
Bucket.BUCKET_INFLUENCERS.getPreferredName(),
Bucket.BUCKET_SPAN.getPreferredName(),
Bucket.EVENT_COUNT.getPreferredName(),
Bucket.INITIAL_ANOMALY_SCORE.getPreferredName(),
Bucket.PROCESSING_TIME_MS.getPreferredName(),
Bucket.SCHEDULED_EVENTS.getPreferredName(),
BucketInfluencer.INITIAL_ANOMALY_SCORE.getPreferredName(), BucketInfluencer.ANOMALY_SCORE.getPreferredName(),
BucketInfluencer.RAW_ANOMALY_SCORE.getPreferredName(), BucketInfluencer.PROBABILITY.getPreferredName(),
CategoryDefinition.CATEGORY_ID.getPreferredName(),
CategoryDefinition.TERMS.getPreferredName(),
CategoryDefinition.REGEX.getPreferredName(),
CategoryDefinition.MAX_MATCHING_LENGTH.getPreferredName(),
CategoryDefinition.EXAMPLES.getPreferredName(),
CategoryDefinition.NUM_MATCHES.getPreferredName(),
CategoryDefinition.PREFERRED_TO_CATEGORIES.getPreferredName(),
DataCounts.PROCESSED_RECORD_COUNT.getPreferredName(),
DataCounts.PROCESSED_FIELD_COUNT.getPreferredName(),
DataCounts.INPUT_BYTES.getPreferredName(),
DataCounts.INPUT_RECORD_COUNT.getPreferredName(),
DataCounts.INPUT_FIELD_COUNT.getPreferredName(),
DataCounts.INVALID_DATE_COUNT.getPreferredName(),
DataCounts.MISSING_FIELD_COUNT.getPreferredName(),
DataCounts.OUT_OF_ORDER_TIME_COUNT.getPreferredName(),
DataCounts.EMPTY_BUCKET_COUNT.getPreferredName(),
DataCounts.SPARSE_BUCKET_COUNT.getPreferredName(),
DataCounts.BUCKET_COUNT.getPreferredName(),
DataCounts.LATEST_RECORD_TIME.getPreferredName(),
DataCounts.EARLIEST_RECORD_TIME.getPreferredName(),
DataCounts.LAST_DATA_TIME.getPreferredName(),
DataCounts.LATEST_EMPTY_BUCKET_TIME.getPreferredName(),
DataCounts.LATEST_SPARSE_BUCKET_TIME.getPreferredName(),
DataCounts.LOG_TIME.getPreferredName(),
Detector.DETECTOR_INDEX.getPreferredName(),
Influence.INFLUENCER_FIELD_NAME.getPreferredName(),
Influence.INFLUENCER_FIELD_VALUES.getPreferredName(),
Influencer.PROBABILITY.getPreferredName(),
Influencer.INFLUENCER_FIELD_NAME.getPreferredName(),
Influencer.INFLUENCER_FIELD_VALUE.getPreferredName(),
Influencer.INITIAL_INFLUENCER_SCORE.getPreferredName(),
Influencer.INFLUENCER_SCORE.getPreferredName(),
Influencer.BUCKET_SPAN.getPreferredName(),
ModelPlot.PARTITION_FIELD_NAME.getPreferredName(), ModelPlot.PARTITION_FIELD_VALUE.getPreferredName(),
ModelPlot.OVER_FIELD_NAME.getPreferredName(), ModelPlot.OVER_FIELD_VALUE.getPreferredName(),
ModelPlot.BY_FIELD_NAME.getPreferredName(), ModelPlot.BY_FIELD_VALUE.getPreferredName(),
ModelPlot.MODEL_FEATURE.getPreferredName(), ModelPlot.MODEL_LOWER.getPreferredName(),
ModelPlot.MODEL_UPPER.getPreferredName(), ModelPlot.MODEL_MEDIAN.getPreferredName(),
ModelPlot.ACTUAL.getPreferredName(),
Forecast.FORECAST_LOWER.getPreferredName(), Forecast.FORECAST_UPPER.getPreferredName(),
Forecast.FORECAST_PREDICTION.getPreferredName(),
Forecast.FORECAST_ID.getPreferredName(),
//re-use: TIMESTAMP
ForecastRequestStats.START_TIME.getPreferredName(),
ForecastRequestStats.END_TIME.getPreferredName(),
ForecastRequestStats.CREATE_TIME.getPreferredName(),
ForecastRequestStats.EXPIRY_TIME.getPreferredName(),
ForecastRequestStats.MESSAGES.getPreferredName(),
ForecastRequestStats.PROGRESS.getPreferredName(),
ForecastRequestStats.STATUS.getPreferredName(),
ForecastRequestStats.MEMORY_USAGE.getPreferredName(),
ModelSizeStats.MODEL_BYTES_FIELD.getPreferredName(),
ModelSizeStats.PEAK_MODEL_BYTES_FIELD.getPreferredName(),
ModelSizeStats.TOTAL_BY_FIELD_COUNT_FIELD.getPreferredName(),
ModelSizeStats.TOTAL_OVER_FIELD_COUNT_FIELD.getPreferredName(),
ModelSizeStats.TOTAL_PARTITION_FIELD_COUNT_FIELD.getPreferredName(),
ModelSizeStats.BUCKET_ALLOCATION_FAILURES_COUNT_FIELD.getPreferredName(),
ModelSizeStats.MEMORY_STATUS_FIELD.getPreferredName(),
ModelSizeStats.ASSIGNMENT_MEMORY_BASIS_FIELD.getPreferredName(),
ModelSizeStats.LOG_TIME_FIELD.getPreferredName(),
ModelSnapshot.DESCRIPTION.getPreferredName(),
ModelSnapshotField.SNAPSHOT_ID.getPreferredName(),
ModelSnapshot.SNAPSHOT_DOC_COUNT.getPreferredName(),
ModelSnapshot.LATEST_RECORD_TIME.getPreferredName(),
ModelSnapshot.LATEST_RESULT_TIME.getPreferredName(),
ModelSnapshot.RETAIN.getPreferredName(),
ModelSnapshot.MIN_VERSION.getPreferredName(),
Result.RESULT_TYPE.getPreferredName(),
Result.TIMESTAMP.getPreferredName(),
Result.IS_INTERIM.getPreferredName(),
TimingStats.BUCKET_COUNT.getPreferredName(),
TimingStats.MIN_BUCKET_PROCESSING_TIME_MS.getPreferredName(),
TimingStats.MAX_BUCKET_PROCESSING_TIME_MS.getPreferredName(),
TimingStats.AVG_BUCKET_PROCESSING_TIME_MS.getPreferredName(),
TimingStats.EXPONENTIAL_AVG_BUCKET_PROCESSING_TIME_MS.getPreferredName(),
TimingStats.EXPONENTIAL_AVG_CALCULATION_CONTEXT.getPreferredName(),
DatafeedTimingStats.SEARCH_COUNT.getPreferredName(),
DatafeedTimingStats.BUCKET_COUNT.getPreferredName(),
DatafeedTimingStats.TOTAL_SEARCH_TIME_MS.getPreferredName(),
DatafeedTimingStats.EXPONENTIAL_AVG_CALCULATION_CONTEXT.getPreferredName(),
ExponentialAverageCalculationContext.INCREMENTAL_METRIC_VALUE_MS.getPreferredName(),
ExponentialAverageCalculationContext.LATEST_TIMESTAMP.getPreferredName(),
ExponentialAverageCalculationContext.PREVIOUS_EXPONENTIAL_AVERAGE_MS.getPreferredName(),
GetResult._ID,
GetResult._INDEX,
GetResult._TYPE
};
/**
* Test if fieldName is one of the reserved result fieldnames or if it contains
* dots then that the segment before the first dot is not a reserved results
* fieldname. A fieldName containing dots represents nested fields in which
* case we only care about the top level.
*
* @param fieldName Document field name. This may contain dots '.'
* @return True if fieldName is not a reserved results fieldname or the top level segment
* is not a reserved name.
*/
public static boolean isValidFieldName(String fieldName) {
String[] segments = DOT_PATTERN.split(fieldName);
return RESERVED_RESULT_FIELD_NAMES.contains(segments[0]) == false;
}
/**
* A set of all reserved field names in our results. Fields from the raw
* data with these names are not added to any result.
*/
public static final Set RESERVED_RESULT_FIELD_NAMES = new HashSet<>(Arrays.asList(RESERVED_RESULT_FIELD_NAME_ARRAY));
private ReservedFieldNames() {
}
}
