[SPARK-32610][DOCS] Fix the link to metrics.dropwizard.io in monitoring.md to refer the proper version

### What changes were proposed in this pull request?

This PR fixes the link to metrics.dropwizard.io in monitoring.md to refer the proper version of the library.

### Why are the changes needed?

There are links to metrics.dropwizard.io in monitoring.md but the link targets refer the version 3.1.0, while we use 4.1.1.
Now that users can create their own metrics using the dropwizard library, it's better to fix the links to refer the proper version.

### Does this PR introduce _any_ user-facing change?

Yes. The modified links refer the version 4.1.1.

### How was this patch tested?

Build the docs and visit all the modified links.

Closes #29426 from sarutak/fix-dropwizard-url.

Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
This commit is contained in:
Kousuke Saruta 2020-08-16 12:07:37 -05:00 committed by Sean Owen
parent c280c7f529
commit 9a79bbc8b6
2 changed files with 8 additions and 4 deletions

View file

@ -758,7 +758,7 @@ The JSON end point is exposed at: `/applications/[app-id]/executors`, and the Pr
The Prometheus endpoint is experimental and conditional to a configuration parameter: `spark.ui.prometheus.enabled=true` (the default is `false`).
In addition, aggregated per-stage peak values of the executor memory metrics are written to the event log if
`spark.eventLog.logStageExecutorMetrics` is true.
Executor memory metrics are also exposed via the Spark metrics system based on the Dropwizard metrics library.
Executor memory metrics are also exposed via the Spark metrics system based on the [Dropwizard metrics library](http://metrics.dropwizard.io/4.1.1).
A list of the available metrics, with a short description:
<table class="table">
@ -962,7 +962,7 @@ keep the paths consistent in both modes.
# Metrics
Spark has a configurable metrics system based on the
[Dropwizard Metrics Library](http://metrics.dropwizard.io/).
[Dropwizard Metrics Library](http://metrics.dropwizard.io/4.1.1).
This allows users to report Spark metrics to a variety of sinks including HTTP, JMX, and CSV
files. The metrics are generated by sources embedded in the Spark code base. They
provide instrumentation for specific activities and Spark components.
@ -1056,7 +1056,7 @@ activates the JVM source:
## List of available metrics providers
Metrics used by Spark are of multiple types: gauge, counter, histogram, meter and timer,
see [Dropwizard library documentation for details](https://metrics.dropwizard.io/3.1.0/getting-started/).
see [Dropwizard library documentation for details](https://metrics.dropwizard.io/4.1.1/getting-started.html).
The following list of components and metrics reports the name and some details about the available metrics,
grouped per component instance and source namespace.
The most common time of metrics used in Spark instrumentation are gauges and counters.
@ -1284,7 +1284,7 @@ Notes:
`spark.metrics.staticSources.enabled` (default is true)
- This source is available for driver and executor instances and is also available for other instances.
- This source provides information on JVM metrics using the
[Dropwizard/Codahale Metric Sets for JVM instrumentation](https://metrics.dropwizard.io/3.1.0/manual/jvm/)
[Dropwizard/Codahale Metric Sets for JVM instrumentation](https://metrics.dropwizard.io/4.1.1/manual/jvm.html)
and in particular the metric sets BufferPoolMetricSet, GarbageCollectorMetricSet and MemoryUsageGaugeSet.
### Component instance = applicationMaster

View file

@ -145,6 +145,10 @@
<chill.version>0.9.5</chill.version>
<ivy.version>2.4.0</ivy.version>
<oro.version>2.0.8</oro.version>
<!--
If you changes codahale.metrics.version, you also need to change
the link to metrics.dropwizard.io in docs/monitoring.md.
-->
<codahale.metrics.version>4.1.1</codahale.metrics.version>
<avro.version>1.8.2</avro.version>
<avro.mapred.classifier>hadoop2</avro.mapred.classifier>