Apache Spark receiver

The Apache Spark receiver fetches metrics for an Apache Spark cluster through the Apache Spark REST API.

The Apache Spark receiver monitors Apache Spark clusters and the applications running on them through the collection of performance metrics like memory utilization, CPU utilization, shuffle operations, and more. The supported pipeline type is metrics. See Process your data with pipelines for more information.

Note: Out-of-the-box dashboards and navigators aren’t supported for the Apache Spark receiver yet, but are planned for a future release.

The receiver retrieves metrics through the Apache Spark REST API using the following endpoints: /metrics/json, /api/v1/applications/[app-id]/stages, /api/v1/applications/[app-id]/executors, and /api/v1/applications/[app-id]/jobs endpoints.

Prerequisites

This receiver supports Apache Spark versions 3.3.2 or higher.

Get started

Follow these steps to configure and activate the component:

Deploy the Splunk Distribution of the OpenTelemetry Collector to your host or container platform:
Configure the receiver as described in the next section.
Restart the Collector.

Sample configuration

To activate the Apache Spark receiver, add apachespark to the receivers section of your configuration file:

receivers:
  apachespark:
    collection_interval: 60s
    endpoint: http://localhost:4040
    application_names:
    - PythonStatusAPIDemo
    - PythonLR

To complete the configuration, include the receiver in the metrics pipeline of the service section of your configuration file:

service:
  pipelines:
    metrics:
      receivers: [apachespark]

Configuration options

The following settings are optional:

collection_interval. 60s by default. Sets the interval this receiver collects metrics on.
- This value must be a string readable by Golang’s time.ParseDuration. Learn more at Go’s official documentation at https://pkg.go.dev/time#ParseDuration.
- Valid time units are ns, us (or µs), ms, s, m, h.
- initial_delay. 1s by default. Determines how long this receiver waits before collecting metrics for the first time.
endpoint. http://localhost:4040 by default. Apache Spark endpoint to connect to in the form of [http][://]{host}[:{port}].
application_names. An array of Spark application names for which metrics are collected from. If no application names are specified, metrics are collected for all Spark applications running on the cluster at the specified endpoint.

Settings

The full list of settings exposed for this receiver are documented in the Apache Spark receiver config repo in GitHub.

Metrics

The following metrics, resource attributes, and attributes are available.

Note: The SignalFx exporter excludes some available metrics by default. Learn more about default metric filters in List of metrics excluded by default.

included

https://raw.githubusercontent.com/splunk/collector-config-tools/main/metric-metadata/apachesparkreceiver.yaml

Activate or deactivate specific metrics

You can activate or deactivate specific metrics by setting the enabled field in the metrics section for each metric. For example:

receivers:
  samplereceiver:
    metrics:
      metric-one:
        enabled: true
      metric-two:
        enabled: false

The following is an example of host metrics receiver configuration with activated metrics:

receivers:
  hostmetrics:
    scrapers:
      process:
        metrics:
          process.cpu.utilization:
            enabled: true

Note: Deactivated metrics aren’t sent to Splunk Observability Cloud.

Billing

If you’re in a MTS-based subscription, all metrics count towards metrics usage.
If you’re in a host-based plan, metrics listed as active (Active: Yes) on this document are considered default and are included free of charge.

Learn more at Infrastructure Monitoring subscription usage (Host and metric plans).

Troubleshooting

If you are a Splunk Observability Cloud customer and are not able to see your data in Splunk Observability Cloud, you can get help in the following ways.

Available to Splunk Observability Cloud customers

Submit a case in the Splunk Support Portal.
Contact Splunk Support.

Available to prospective customers and free trial users

Ask a question and get answers through community support at Splunk Answers.
Join the Splunk #observability user group Slack channel to communicate with customers, partners, and Splunk employees worldwide. To join, see Chat groups.

Documentation