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OpenSearch Query Input Plugin

plugins/inputs/opensearch_query/README.md

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OpenSearch Query Input Plugin

This plugin queries OpenSearch endpoints to derive metrics from data stored in an OpenSearch cluster like the number of hits for a search query, statistics on numeric fields, document counts, etc.

[!NOTE] This plugins is tested against OpenSearch 2.5.0 and 1.3.7 but newer version should also work.

⭐ Telegraf v1.26.0 🏷️ datastore 💻 all

Global configuration options <!-- @/docs/includes/plugin_config.md -->

Plugins support additional global and plugin configuration settings for tasks such as modifying metrics, tags, and fields, creating aliases, and configuring plugin ordering. See CONFIGURATION.md for more details.

Configuration

toml
# Derive metrics from aggregating OpenSearch query results
[[inputs.opensearch_query]]
  ## OpenSearch cluster endpoint(s). Multiple urls can be specified as part
  ## of the same cluster.  Only one successful call will be made per interval.
  urls = [ "https://node1.os.example.com:9200" ] # required.

  ## OpenSearch client timeout, defaults to "5s".
  # timeout = "5s"

  ## HTTP basic authentication details
  # username = "admin"
  # password = "admin"

  ## Skip TLS validation.  Useful for local testing and self-signed certs.
  # insecure_skip_verify = false

  [[inputs.opensearch_query.aggregation]]
    ## measurement name for the results of the aggregation query
    measurement_name = "measurement"

    ## OpenSearch index or index pattern to search
    index = "index-*"

    ## The date/time field in the OpenSearch index (mandatory).
    date_field = "@timestamp"

    ## If the field used for the date/time field in OpenSearch is also using
    ## a custom date/time format it may be required to provide the format to
    ## correctly parse the field.
    ##
    ## If using one of the built in OpenSearch formats this is not required.
    ## https://opensearch.org/docs/2.4/opensearch/supported-field-types/date/#built-in-formats
    # date_field_custom_format = ""

    ## Time window to query (eg. "1m" to query documents from last minute).
    ## Normally should be set to same as collection interval
    query_period = "1m"

    ## Lucene query to filter results
    # filter_query = "*"

    ## Fields to aggregate values (must be numeric fields)
    # metric_fields = ["metric"]

    ## Aggregation function to use on the metric fields
    ## Must be set if 'metric_fields' is set
    ## Valid values are: avg, sum, min, max, sum
    # metric_function = "avg"

    ## Fields to be used as tags.  Must be text, non-analyzed fields. Metric
    ## aggregations are performed per tag
    # tags = ["field.keyword", "field2.keyword"]

    ## Set to true to not ignore documents when the tag(s) above are missing
    # include_missing_tag = false

    ## String value of the tag when the tag does not exist
    ## Required when include_missing_tag is true
    # missing_tag_value = "null"

Supported queries

The following queries are supported:

  • return number of hits for a search query
  • calculate the avg/max/min/sum for a numeric field, filtered by a query, aggregated per tag
  • value_count returns the number of documents for a particular field
  • stats (returns sum, min, max, avg, and value_count in one query)
  • extended_stats (stats plus stats such as sum of squares, variance, and standard deviation)
  • percentiles returns the 1st, 5th, 25th, 50th, 75th, 95th, and 99th percentiles

Required parameters

  • measurement_name: The target measurement to be stored the results of the aggregation query.
  • index: The index name to query on OpenSearch
  • query_period: The time window to query (eg. "1m" to query documents from last minute). Normally should be set to same as collection
  • date_field: The date/time field in the OpenSearch index

Optional parameters

  • date_field_custom_format: Not needed if using one of the built in date/time formats of OpenSearch, but may be required if using a custom date/time format. The format syntax uses the Joda date format.
  • filter_query: Lucene query to filter the results (default: "*")
  • metric_fields: The list of fields to perform metric aggregation (these must be indexed as numeric fields)
  • metric_function: The single-value metric aggregation function to be performed on the metric_fields defined. Currently supported aggregations are "avg", "min", "max", "sum", "value_count", "stats", "extended_stats", "percentiles". (see the aggregation docs)
  • tags: The list of fields to be used as tags (these must be indexed as non-analyzed fields). A "terms aggregation" will be done per tag defined
  • include_missing_tag: Set to true to not ignore documents where the tag(s) specified above does not exist. (If false, documents without the specified tag field will be ignored in doc_count and in the metric aggregation)
  • missing_tag_value: The value of the tag that will be set for documents in which the tag field does not exist. Only used when include_missing_tag is set to true.

Example configurations

Search the average response time, per URI and per response status code

toml
[[inputs.opensearch_query.aggregation]]
  measurement_name = "http_logs"
  index = "my-index-*"
  filter_query = "*"
  metric_fields = ["response_time"]
  metric_function = "avg"
  tags = ["URI.keyword", "response.keyword"]
  include_missing_tag = true
  missing_tag_value = "null"
  date_field = "@timestamp"
  query_period = "1m"

Search the maximum response time per method and per URI

toml
[[inputs.opensearch_query.aggregation]]
  measurement_name = "http_logs"
  index = "my-index-*"
  filter_query = "*"
  metric_fields = ["response_time"]
  metric_function = "max"
  tags = ["method.keyword","URI.keyword"]
  include_missing_tag = false
  missing_tag_value = "null"
  date_field = "@timestamp"
  query_period = "1m"

Search number of documents matching a filter query in all indices

toml
[[inputs.opensearch_query.aggregation]]
  measurement_name = "http_logs"
  index = "*"
  filter_query = "product_1 AND HEAD"
  query_period = "1m"
  date_field = "@timestamp"

Search number of documents matching a filter query, returning per response status code

toml
[[inputs.opensearch_query.aggregation]]
  measurement_name = "http_logs"
  index = "*"
  filter_query = "downloads"
  tags = ["response.keyword"]
  include_missing_tag = false
  date_field = "@timestamp"
  query_period = "1m"

Search all documents and generate common statistics, returning per response status code

toml
[[inputs.opensearch_query.aggregation]]
  measurement_name = "http_logs"
  index = "*"
  tags = ["response.keyword"]
  include_missing_tag = false
  date_field = "@timestamp"
  query_period = "1m"

Metrics

All metrics derive from aggregating OpenSearch query results. Queries must conform to appropriate OpenSearch Aggregations for more information.

Metric names are composed of a combination of the field name, metric aggregation function, and the result field name.

For simple metrics, the result field name is value, and so getting the avg on a field named size would produce the result size_value_avg.

For functions with multiple metrics, we use the resulting field. For example, the stats function returns five different results, so for a field size, we would see five metric fields, named size_stats_min, size_stats_max, size_stats_sum, size_stats_avg, and size_stats_count.

Nested results will build on their parent field names, for example, results for percentile take the form:

json
{
  "aggregations" : {
  "size_percentiles" : {
    "values" : {
      "1.0" : 21.984375,
      "5.0" : 27.984375,
      "25.0" : 44.96875,
      "50.0" : 64.22061688311689,
      "75.0" : 93.0,
      "95.0" : 156.0,
      "99.0" : 222.0
    }
  }
 }
}

Thus, our results would take the form size_percentiles_values_1.0. This structure applies to percentiles and extended_stats functions.

Note: extended_stats is currently limited to 2 standard deviations only.

Example Output

toml
[[inputs.opensearch_query.aggregation]]
    measurement_name = "bytes_stats"
    index = "opensearch_dashboards_sample_data_logs"
    date_field = "timestamp"
    query_period = "10m"
    filter_query = "*"
    metric_fields = ["bytes"]
    metric_function = "stats"
    tags = ["response.keyword"]
text
bytes_stats,host=localhost,response_keyword=200 bytes_stats_sum=22231,doc_count=4i,bytes_stats_count=4,bytes_stats_min=941,bytes_stats_max=9544,bytes_stats_avg=5557.75 1672327840000000000
bytes_stats,host=localhost,response_keyword=404 bytes_stats_min=5330,bytes_stats_max=5330,bytes_stats_avg=5330,doc_count=1i,bytes_stats_sum=5330,bytes_stats_count=1 1672327840000000000