Package co.elastic.clients.elasticsearch.cat

Enum CatAnomalyDetectorColumn

java.lang.Object
java.lang.Enum<CatAnomalyDetectorColumn>
co.elastic.clients.elasticsearch.cat.CatAnomalyDetectorColumn
All Implemented Interfaces:
JsonEnum, JsonpSerializable, java.io.Serializable, java.lang.Comparable<CatAnomalyDetectorColumn>, java.lang.constant.Constable
@JsonpDeserializable
public enum CatAnomalyDetectorColumn
extends java.lang.Enum<CatAnomalyDetectorColumn>
implements JsonEnum
See Also:
API specification

  • Nested Class Summary

    Nested classes/interfaces inherited from class java.lang.Enum

    java.lang.Enum.EnumDesc<E extends java.lang.Enum<E>>

    Nested classes/interfaces inherited from interface co.elastic.clients.json.JsonEnum

    JsonEnum.Deserializer<T extends JsonEnum>

  • Enum Constant Summary

    Enum Constants
    Enum Constant Description
    AssignmentExplanation
    For open anomaly detection jobs only, contains messages relating to the selection of a node to run the job.
    BucketsCount
    The number of bucket results produced by the job.
    BucketsTimeExpAvg
    Exponential moving average of all bucket processing times, in milliseconds.
    BucketsTimeExpAvgHour
    Exponentially-weighted moving average of bucket processing times calculated in a 1 hour time window, in milliseconds.
    BucketsTimeMax
    Maximum among all bucket processing times, in milliseconds.
    BucketsTimeMin
    Minimum among all bucket processing times, in milliseconds.
    BucketsTimeTotal
    Sum of all bucket processing times, in milliseconds.
    DataBuckets
    The number of buckets processed.
    DataEarliestRecord
    The timestamp of the earliest chronologically input document.
    DataEmptyBuckets
    The number of buckets which did not contain any data.
    DataInputBytes
    The number of bytes of input data posted to the anomaly detection job.
    DataInputFields
    The total number of fields in input documents posted to the anomaly detection job.
    DataInputRecords
    The number of input documents posted to the anomaly detection job.
    DataInvalidDates
    The number of input documents with either a missing date field or a date that could not be parsed.
    DataLast
    The timestamp at which data was last analyzed, according to server time.
    DataLastEmptyBucket
    The timestamp of the last bucket that did not contain any data.
    DataLastSparseBucket
    The timestamp of the last bucket that was considered sparse.
    DataLatestRecord
    The timestamp of the latest chronologically input document.
    DataMissingFields
    The number of input documents that are missing a field that the anomaly detection job is configured to analyze.
    DataOutOfOrderTimestamps
    The number of input documents that have a timestamp chronologically preceding the start of the current anomaly detection bucket offset by the latency window.
    DataProcessedFields
    The total number of fields in all the documents that have been processed by the anomaly detection job.
    DataProcessedRecords
    The number of input documents that have been processed by the anomaly detection job.
    DataSparseBuckets
    The number of buckets that contained few data points compared to the expected number of data points.
    ForecastsMemoryAvg
    The average memory usage in bytes for forecasts related to the anomaly detection job.
    ForecastsMemoryMax
    The maximum memory usage in bytes for forecasts related to the anomaly detection job.
    ForecastsMemoryMin
    The minimum memory usage in bytes for forecasts related to the anomaly detection job.
    ForecastsMemoryTotal
    The total memory usage in bytes for forecasts related to the anomaly detection job.
    ForecastsRecordsAvg
    The average number of model_forecast` documents written for forecasts related to the anomaly detection job.
    ForecastsRecordsMax
    The maximum number of model_forecast documents written for forecasts related to the anomaly detection job.
    ForecastsRecordsMin
    The minimum number of model_forecast documents written for forecasts related to the anomaly detection job.
    ForecastsRecordsTotal
    The total number of model_forecast documents written for forecasts related to the anomaly detection job.
    ForecastsTimeAvg
    The average runtime in milliseconds for forecasts related to the anomaly detection job.
    ForecastsTimeMax
    The maximum runtime in milliseconds for forecasts related to the anomaly detection job.
    ForecastsTimeMin
    The minimum runtime in milliseconds for forecasts related to the anomaly detection job.
    ForecastsTimeTotal
    The total runtime in milliseconds for forecasts related to the anomaly detection job.
    ForecastsTotal
    The number of individual forecasts currently available for the job.
    Id
    Identifier for the anomaly detection job.
    ModelBucketAllocationFailures
    The number of buckets for which new entities in incoming data were not processed due to insufficient model memory.
    ModelByFields
    The number of by field values that were analyzed by the models.
    ModelBytes
    The number of bytes of memory used by the models.
    ModelBytesExceeded
    The number of bytes over the high limit for memory usage at the last allocation failure.
    ModelCategorizationStatus
    The status of categorization for the job: ok or warn.
    ModelCategorizedDocCount
    The number of documents that have had a field categorized.
    ModelDeadCategoryCount
    The number of categories created by categorization that will never be assigned again because another category’s definition makes it a superset of the dead category.
    ModelFailedCategoryCount
    The number of times that categorization wanted to create a new category but couldn’t because the job had hit its model memory limit.
    ModelFrequentCategoryCount
    The number of categories that match more than 1% of categorized documents.
    ModelLogTime
    The timestamp when the model stats were gathered, according to server time.
    ModelMemoryLimit
    The timestamp when the model stats were gathered, according to server time.
    ModelMemoryStatus
    The status of the mathematical models: ok, soft_limit, or hard_limit.
    ModelOverFields
    The number of over field values that were analyzed by the models.
    ModelPartitionFields
    The number of partition field values that were analyzed by the models.
    ModelRareCategoryCount
    The number of categories that match just one categorized document.
    ModelTimestamp
    The timestamp of the last record when the model stats were gathered.
    ModelTotalCategoryCount
    The number of categories created by categorization.
    NodeAddress
    The network address of the node that runs the job.
    NodeEphemeralId
    The ephemeral ID of the node that runs the job.
    NodeId
    The unique identifier of the node that runs the job.
    NodeName
    The name of the node that runs the job.
    OpenedTime
    For open jobs only, the elapsed time for which the job has been open.
    State
    The status of the anomaly detection job: closed, closing, failed, opened, or opening.

  • Field Summary

    Fields
    Modifier and Type Field Description
    static JsonEnum.Deserializer<CatAnomalyDetectorColumn> _DESERIALIZER  

  • Method Summary

    Modifier and Type Method Description
    java.lang.String[] aliases()  
    java.lang.String jsonValue()  
    static CatAnomalyDetectorColumn valueOf​(java.lang.String name)
    Returns the enum constant of this type with the specified name.
    static CatAnomalyDetectorColumn[] values()
    Returns an array containing the constants of this enum type, in the order they are declared.

    Methods inherited from class java.lang.Enum

    clone, compareTo, describeConstable, equals, finalize, getDeclaringClass, hashCode, name, ordinal, toString, valueOf

    Methods inherited from class java.lang.Object

    getClass, notify, notifyAll, wait, wait, wait

    Methods inherited from interface co.elastic.clients.json.JsonEnum

    serialize

  • Enum Constant Details

    • AssignmentExplanation

      public static final CatAnomalyDetectorColumn AssignmentExplanation
      For open anomaly detection jobs only, contains messages relating to the selection of a node to run the job.

    • BucketsCount

      public static final CatAnomalyDetectorColumn BucketsCount
      The number of bucket results produced by the job.

    • BucketsTimeExpAvg

      public static final CatAnomalyDetectorColumn BucketsTimeExpAvg
      Exponential moving average of all bucket processing times, in milliseconds.

    • BucketsTimeExpAvgHour

      public static final CatAnomalyDetectorColumn BucketsTimeExpAvgHour
      Exponentially-weighted moving average of bucket processing times calculated in a 1 hour time window, in milliseconds.

    • BucketsTimeMax

      public static final CatAnomalyDetectorColumn BucketsTimeMax
      Maximum among all bucket processing times, in milliseconds.

    • BucketsTimeMin

      public static final CatAnomalyDetectorColumn BucketsTimeMin
      Minimum among all bucket processing times, in milliseconds.

    • BucketsTimeTotal

      public static final CatAnomalyDetectorColumn BucketsTimeTotal
      Sum of all bucket processing times, in milliseconds.

    • DataBuckets

      public static final CatAnomalyDetectorColumn DataBuckets
      The number of buckets processed.

    • DataEarliestRecord

      public static final CatAnomalyDetectorColumn DataEarliestRecord
      The timestamp of the earliest chronologically input document.

    • DataEmptyBuckets

      public static final CatAnomalyDetectorColumn DataEmptyBuckets
      The number of buckets which did not contain any data.

    • DataInputBytes

      public static final CatAnomalyDetectorColumn DataInputBytes
      The number of bytes of input data posted to the anomaly detection job.

    • DataInputFields

      public static final CatAnomalyDetectorColumn DataInputFields
      The total number of fields in input documents posted to the anomaly detection job. This count includes fields that are not used in the analysis. However, be aware that if you are using a datafeed, it extracts only the required fields from the documents it retrieves before posting them to the job.

    • DataInputRecords

      public static final CatAnomalyDetectorColumn DataInputRecords
      The number of input documents posted to the anomaly detection job.

    • DataInvalidDates

      public static final CatAnomalyDetectorColumn DataInvalidDates
      The number of input documents with either a missing date field or a date that could not be parsed.

    • DataLast

      public static final CatAnomalyDetectorColumn DataLast
      The timestamp at which data was last analyzed, according to server time.

    • DataLastEmptyBucket

      public static final CatAnomalyDetectorColumn DataLastEmptyBucket
      The timestamp of the last bucket that did not contain any data.

    • DataLastSparseBucket

      public static final CatAnomalyDetectorColumn DataLastSparseBucket
      The timestamp of the last bucket that was considered sparse.

    • DataLatestRecord

      public static final CatAnomalyDetectorColumn DataLatestRecord
      The timestamp of the latest chronologically input document.

    • DataMissingFields

      public static final CatAnomalyDetectorColumn DataMissingFields
      The number of input documents that are missing a field that the anomaly detection job is configured to analyze. Input documents with missing fields are still processed because it is possible that not all fields are missing.

    • DataOutOfOrderTimestamps

      public static final CatAnomalyDetectorColumn DataOutOfOrderTimestamps
      The number of input documents that have a timestamp chronologically preceding the start of the current anomaly detection bucket offset by the latency window. This information is applicable only when you provide data to the anomaly detection job by using the post data API. These out of order documents are discarded, since jobs require time series data to be in ascending chronological order.

    • DataProcessedFields

      public static final CatAnomalyDetectorColumn DataProcessedFields
      The total number of fields in all the documents that have been processed by the anomaly detection job. Only fields that are specified in the detector configuration object contribute to this count. The timestamp is not included in this count.

    • DataProcessedRecords

      public static final CatAnomalyDetectorColumn DataProcessedRecords
      The number of input documents that have been processed by the anomaly detection job. This value includes documents with missing fields, since they are nonetheless analyzed. If you use datafeeds and have aggregations in your search query, the processed record count is the number of aggregation results processed, not the number of Elasticsearch documents.

    • DataSparseBuckets

      public static final CatAnomalyDetectorColumn DataSparseBuckets
      The number of buckets that contained few data points compared to the expected number of data points.

    • ForecastsMemoryAvg

      public static final CatAnomalyDetectorColumn ForecastsMemoryAvg
      The average memory usage in bytes for forecasts related to the anomaly detection job.

    • ForecastsMemoryMax

      public static final CatAnomalyDetectorColumn ForecastsMemoryMax
      The maximum memory usage in bytes for forecasts related to the anomaly detection job.

    • ForecastsMemoryMin

      public static final CatAnomalyDetectorColumn ForecastsMemoryMin
      The minimum memory usage in bytes for forecasts related to the anomaly detection job.

    • ForecastsMemoryTotal

      public static final CatAnomalyDetectorColumn ForecastsMemoryTotal
      The total memory usage in bytes for forecasts related to the anomaly detection job.

    • ForecastsRecordsAvg

      public static final CatAnomalyDetectorColumn ForecastsRecordsAvg
      The average number of model_forecast` documents written for forecasts related to the anomaly detection job.

    • ForecastsRecordsMax

      public static final CatAnomalyDetectorColumn ForecastsRecordsMax
      The maximum number of model_forecast documents written for forecasts related to the anomaly detection job.

    • ForecastsRecordsMin

      public static final CatAnomalyDetectorColumn ForecastsRecordsMin
      The minimum number of model_forecast documents written for forecasts related to the anomaly detection job.

    • ForecastsRecordsTotal

      public static final CatAnomalyDetectorColumn ForecastsRecordsTotal
      The total number of model_forecast documents written for forecasts related to the anomaly detection job.

    • ForecastsTimeAvg

      public static final CatAnomalyDetectorColumn ForecastsTimeAvg
      The average runtime in milliseconds for forecasts related to the anomaly detection job.

    • ForecastsTimeMax

      public static final CatAnomalyDetectorColumn ForecastsTimeMax
      The maximum runtime in milliseconds for forecasts related to the anomaly detection job.

    • ForecastsTimeMin

      public static final CatAnomalyDetectorColumn ForecastsTimeMin
      The minimum runtime in milliseconds for forecasts related to the anomaly detection job.

    • ForecastsTimeTotal

      public static final CatAnomalyDetectorColumn ForecastsTimeTotal
      The total runtime in milliseconds for forecasts related to the anomaly detection job.

    • ForecastsTotal

      public static final CatAnomalyDetectorColumn ForecastsTotal
      The number of individual forecasts currently available for the job.

    • Id

      public static final CatAnomalyDetectorColumn Id
      Identifier for the anomaly detection job.

    • ModelBucketAllocationFailures

      public static final CatAnomalyDetectorColumn ModelBucketAllocationFailures
      The number of buckets for which new entities in incoming data were not processed due to insufficient model memory.

    • ModelByFields

      public static final CatAnomalyDetectorColumn ModelByFields
      The number of by field values that were analyzed by the models. This value is cumulative for all detectors in the job.

    • ModelBytes

      public static final CatAnomalyDetectorColumn ModelBytes
      The number of bytes of memory used by the models. This is the maximum value since the last time the model was persisted. If the job is closed, this value indicates the latest size.

    • ModelBytesExceeded

      public static final CatAnomalyDetectorColumn ModelBytesExceeded
      The number of bytes over the high limit for memory usage at the last allocation failure.

    • ModelCategorizationStatus

      public static final CatAnomalyDetectorColumn ModelCategorizationStatus
      The status of categorization for the job: ok or warn. If ok, categorization is performing acceptably well (or not being used at all). If warn, categorization is detecting a distribution of categories that suggests the input data is inappropriate for categorization. Problems could be that there is only one category, more than 90% of categories are rare, the number of categories is greater than 50% of the number of categorized documents, there are no frequently matched categories, or more than 50% of categories are dead.

    • ModelCategorizedDocCount

      public static final CatAnomalyDetectorColumn ModelCategorizedDocCount
      The number of documents that have had a field categorized.

    • ModelDeadCategoryCount

      public static final CatAnomalyDetectorColumn ModelDeadCategoryCount
      The number of categories created by categorization that will never be assigned again because another category’s definition makes it a superset of the dead category. Dead categories are a side effect of the way categorization has no prior training.

    • ModelFailedCategoryCount

      public static final CatAnomalyDetectorColumn ModelFailedCategoryCount
      The number of times that categorization wanted to create a new category but couldn’t because the job had hit its model memory limit. This count does not track which specific categories failed to be created. Therefore, you cannot use this value to determine the number of unique categories that were missed.

    • ModelFrequentCategoryCount

      public static final CatAnomalyDetectorColumn ModelFrequentCategoryCount
      The number of categories that match more than 1% of categorized documents.

    • ModelLogTime

      public static final CatAnomalyDetectorColumn ModelLogTime
      The timestamp when the model stats were gathered, according to server time.

    • ModelMemoryLimit

      public static final CatAnomalyDetectorColumn ModelMemoryLimit
      The timestamp when the model stats were gathered, according to server time.

    • ModelMemoryStatus

      public static final CatAnomalyDetectorColumn ModelMemoryStatus
      The status of the mathematical models: ok, soft_limit, or hard_limit. If ok, the models stayed below the configured value. If soft_limit, the models used more than 60% of the configured memory limit and older unused models will be pruned to free up space. Additionally, in categorization jobs no further category examples will be stored. If hard_limit, the models used more space than the configured memory limit. As a result, not all incoming data was processed.

    • ModelOverFields

      public static final CatAnomalyDetectorColumn ModelOverFields
      The number of over field values that were analyzed by the models. This value is cumulative for all detectors in the job.

    • ModelPartitionFields

      public static final CatAnomalyDetectorColumn ModelPartitionFields
      The number of partition field values that were analyzed by the models. This value is cumulative for all detectors in the job.

    • ModelRareCategoryCount

      public static final CatAnomalyDetectorColumn ModelRareCategoryCount
      The number of categories that match just one categorized document.

    • ModelTimestamp

      public static final CatAnomalyDetectorColumn ModelTimestamp
      The timestamp of the last record when the model stats were gathered.

    • ModelTotalCategoryCount

      public static final CatAnomalyDetectorColumn ModelTotalCategoryCount
      The number of categories created by categorization.

    • NodeAddress

      public static final CatAnomalyDetectorColumn NodeAddress
      The network address of the node that runs the job. This information is available only for open jobs.

    • NodeEphemeralId

      public static final CatAnomalyDetectorColumn NodeEphemeralId
      The ephemeral ID of the node that runs the job. This information is available only for open jobs.

    • NodeId

      public static final CatAnomalyDetectorColumn NodeId
      The unique identifier of the node that runs the job. This information is available only for open jobs.

    • NodeName

      public static final CatAnomalyDetectorColumn NodeName
      The name of the node that runs the job. This information is available only for open jobs.

    • OpenedTime

      public static final CatAnomalyDetectorColumn OpenedTime
      For open jobs only, the elapsed time for which the job has been open.

    • State

      public static final CatAnomalyDetectorColumn State
      The status of the anomaly detection job: closed, closing, failed, opened, or opening. If closed, the job finished successfully with its model state persisted. The job must be opened before it can accept further data. If closing, the job close action is in progress and has not yet completed. A closing job cannot accept further data. If failed, the job did not finish successfully due to an error. This situation can occur due to invalid input data, a fatal error occurring during the analysis, or an external interaction such as the process being killed by the Linux out of memory (OOM) killer. If the job had irrevocably failed, it must be force closed and then deleted. If the datafeed can be corrected, the job can be closed and then re-opened. If opened, the job is available to receive and process data. If opening, the job open action is in progress and has not yet completed.

  • Field Details

  • Method Details

    • values

      public static CatAnomalyDetectorColumn[] values()
      Returns an array containing the constants of this enum type, in the order they are declared.
      Returns:
      an array containing the constants of this enum type, in the order they are declared

    • valueOf

      public static CatAnomalyDetectorColumn valueOf​(java.lang.String name)
      Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)
      Parameters:
      name - the name of the enum constant to be returned.
      Returns:
      the enum constant with the specified name
      Throws:
      java.lang.IllegalArgumentException - if this enum type has no constant with the specified name
      java.lang.NullPointerException - if the argument is null

    • jsonValue

      public java.lang.String jsonValue()
      Specified by:
      jsonValue in interface JsonEnum

    • aliases

      public java.lang.String[] aliases()
      Specified by:
      aliases in interface JsonEnum