Sumコネクター 🔗

The Splunk Distribution of the OpenTelemetry Collector uses the Sum connector to sum attribute values from spans, span events, metrics, data points, and log records.

As a receiver, the supported pipeline types are metrics, traces and logs. As an exporter, the supported pipeline type is metrics. See パイプラインでデータを処理する for more information.

注釈

Values found within an attribute are converted into a float regardless of their original type before being summed and output as a metric value. Non-convertible strings are dropped and not included.

はじめに 🔗

以下の手順に従って、コンポーネントの設定とアクティベーションを行ってください：

Splunk Distribution of the OpenTelemetry Collector をホストまたはコンテナプラットフォームにデプロイします：

インストーラ・スクリプトを使用して Linux 用 Collector をインストールします。

インストーラ・スクリプトを使用して Collector for Windows をインストールします。

Helmを使用してCollector for Kubernetesをインストールする

次のセクションで説明するように、コネクターを設定します。
Collector を再起動します。

サンプル構成 🔗

To activate the connector, add sum to the connectors section of your configuration file.

例：

connectors:
  sum:

To complete the configuration, add the connector in the service section of your configuration file according to the pipelines you want to use, for example:

service:
  pipelines:
    metrics/sum:
       receivers: [sum]
    traces:
       exporters: [sum]

設定オプション 🔗

以下の設定が必要です：

Telemetry type. Nested below the sum: connector declaration. Can be any of spans or spanevents for traces, datapoints for metrics, or logs.
- In Configuration example: Sum attribute values, it’s declared as spans.
Metric name. Nested below the telemetry type; this is the metric name the sum connector will output summed values to.
- In Configuration example: Sum attribute values, it’s declared as my.example.metric.name.
source_attribute. A specific attribute to search for within the source telemetry being fed to the connector. This attribute is where the connector looks for numerical values to sum into the output metric value.
- In Configuration example: Sum attribute values, it’s declared as attribute.with.numerical.value.

オプションで以下の設定が可能です：

conditions. You can use OTTL syntax to provide conditions for processing incoming telemetry. Conditions are ORed together, so if any condition is met the attribute’s value is included in the resulting sum. For more information see OTTL grammar in GitHub.
attributes. Declaration of attributes to include. Any of these attributes found will generate a separate sum for each set of unique combination of attribute values and output as its own datapoint in the metric time series.
- key. Required for attributes. The attribute name to match against.
- default_value. Optional for attributes. A default value for the attribute when no matches are found. The default_value value can be a string, integer, or float.

Configuration example: Sum attribute values 🔗

This example configuration sums numerical values found within the attribute attribute.with.numerical.value of any span telemetry routed to the connector and outputs a metric time series with the name my.example.metric.name with those summed values.

receivers:
  foo:
connectors:
  sum:
    spans:
      my.example.metric.name:
        source_attribute: attribute.with.numerical.value

exporters:
  bar:

service:
  pipelines:
    metrics/sum:
       receivers: [sum]
       exporters: [bar]
    traces:
       receivers: [foo]
       exporters: [sum]

Configuration example: Check payment logs 🔗

In this example the Sum connector ingests logs and creates an output metric named checkout.total with numerical values found in the source_attribute total.payment. It also checks any incoming log telemetry for values present in the attribute payment.processor and creates a datapoint within the metric time series for each unique value.

It also makes sure that:

The attribute total.payment is not NULL.
Any logs without values in payment.processor are included in a datapoint with the default_value of unspecified_processor.

receivers:
  foo:
connectors:
  sum:
    logs:
      checkout.total:
        source_attribute: total.payment
        conditions:
          - attributes["total.payment"] != "NULL"
        attributes:
          - key: payment.processor
            default_value: unspecified_processor
exporters:
  bar:

service:
  pipelines:
    metrics/sum:
       receivers: [sum]
       exporters: [bar]
    logs:
       receivers: [foo]
       exporters: [sum]

Logs to metrics 🔗

For log-to-metrics connection, if your logs contain all values in their body rather than in attributes, use a トランスフォームプロセッサー in your pipeline to upsert parsed key/value pairs into attributes attached to the log.

For example, for a JSON payload:

processors:
  transform/logs:
    log_statements:
      - context: log
        statements:
          - merge_maps(attributes, ParseJSON(body), "upsert")

トラブルシューティング 🔗

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このページは 2025年02月11日に最終更新されました。

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