# Metrics 2.0

## Overview

This package provides a framework for metrics instrumentation and publication.

The instrumentation of metrics just need to implement the simple `MetricsSource` interface with a single `getMetrics` method; The consumers of metrics just need to implement the simple `MetricsSink` interface with a `putMetrics` method along with the `init` and `flush` methods. Producers register the metrics sources with a metrics system, while consumers register the sinks. A default metrics system is provided to marshal metrics from sources to sinks based on (per source/sink) configuration options. Metrics from `getMetrics` would also be published and queryable via the standard JMX mechanism. This document targets the framework users. Framework developers could consult the design document for architecture and implementation notes.

### Sub-packages

`org.apache.hadoop.metrics2.impl`
  Implementation classes of the framework for interface and/or abstract classes defined in the top-level package. Sink plugin code usually does not need to reference any class here.
`org.apache.hadoop.metrics2.lib`
  Convenience classes for implementing metrics sources, including the `MetricMutable[Gauge*|Counter*|Stat]` and `MetricsRegistry`.
`org.apache.hadoop.metrics2.filter`
  Builtin metrics filter implementations include the `GlobFilter` and `RegexFilter`.
`org.apache.hadoop.metrics2.source`
  Builtin metrics source implementations including the `JvmMetricsSource`.
`org.apache.hadoop.metrics2.sink`
  Builtin metrics sink implementations including the `FileSink`.

## Getting started

Here is a simple MetricsSource:

        class MyMetrics implements MetricsSource {
          public void getMetrics(MetricsBuilder builder, boolean all) {
            builder.addRecord("myRecord").setContext("myContext")
                   .addGauge("myMetric", "My metrics description", 42);
          }
        }

In this example there are three names:

myContext
  The optional context name typically identifies either the application, or a group of modules within an application or library.
myRecord
  The record name generally identifies some entity for which a set of metrics are to be reported. For example, you could have a record named "cacheStat" for reporting a number of statistics relating to the usage of some cache in your application.
myMetric
  This identifies a particular metric. In this case the metric is a "gauge" type, which means it can vary in both directions, compared with a "counter" type, which can only increase or stay the same. The 42 here is the value of the metric, which can be substituted a variable or a non-blocking method call returning a number.

Note, the boolean argument `all`, if true, means that the source should send all the metrics it defines, even if the metrics are unchanged since last `getMetrics` call. This enable an optimization for less copying for metrics that don't change much (total capacity of something etc. which only changes when new resources (nodes or disks) are being added.)

Here is a simple MetricsSink:

        public class MySink implements MetricsSink {
          public void putMetrics(MetricsRecord record) {
            System.out.print(record);
          }
          public void init(SubsetConfiguration conf) {}
          public void flush() {}
        }

In this example there are three additional concepts:

record
  This object corresponds to the record created in metrics sources e.g., the "myRecord" in previous example.
conf
  The configuration object for the sink instance with prefix removed. So you can get any sink specific configuration using the usual get* method.
flush
  This method is called for each update cycle, which may involve more than one record. The sink should try to flush any buffered metrics to its backend upon the call. But it's not required that the implementation is synchronous.

In order to make use our `MyMetrics` and `MySink`, they need to be hooked up to a metrics system. In this case (and most cases), the `DefaultMetricsSystem` would suffice.

        DefaultMetricsSystem.initialize("test"); // called once per application
        DefaultMetricsSystem.INSTANCE.register("MyMetrics", "my metrics description",
                                               new MyMetrics());

Sinks are usually specified in a configuration file, say, "hadoop-metrics2-test.properties", as:

        test.sink.mysink0.class=com.example.hadoop.metrics.MySink

The configuration syntax is:

        [prefix].[source|sink|jmx|].[instance].[option]

In the previous example, `test` is the prefix and `mysink0` is an instance name. `DefaultMetricsSystem` would try to load `hadoop-metrics2-[prefix].properties` first, and if not found, try the default `hadoop-metrics2.properties` in the class path. Note, the `[instance]` is an arbitrary name to uniquely identify a particular sink instance. The asterisk (`*`) can be used to specify default options.

Consult the metrics instrumentation in {@link org.apache.hadoop.metrics2.source.JvmMetricsSource}, {@link org.apache.hadoop.ipc.metrics.RpcInstrumentation}, etc. for more examples.

## Metrics Filtering

One of the features of the default metrics system is metrics filtering configuration by source, context, record/tags and metrics. The least expensive way to filter out metrics would be at the source level, e.g., filtering out source named "MyMetrics". The most expensive way would be per metric filtering.

Here are some examples:

        test.sink.file0.class=org.apache.hadoop.metrics2.sink.FileSink
        test.sink.file0.context=foo

In this example, we configured one sink instance that would accept metrics from context `foo` only.

        *.source.filter.class=org.apache.hadoop.metrics2.filter.GlobFilter
        test.*.source.filter.include=foo
        test.*.source.filter.exclude=bar

In this example, we specify a source filter that includes source `foo` and excludes `bar`. When only include patterns are specified, the filter operates in the white listing mode, where only matched sources are included. Likewise, when only exclude patterns are specified, only matched sources are excluded. Sources that are not matched in either patterns are included as well when both patterns are present. Note, the include patterns have precedence over the exclude patterns.

Similarly, you can specify the `record.filter` and `metrics.filter` options, which operate at record and metric level, respectively. Filters can be combined to optimize the filtering efficiency.

## Metrics instrumentation strategy

In previous examples, we showed a minimal example to use the metrics framework. In a larger system (like Hadoop) that allows custom metrics instrumentation, we recommend the following strategy:

        class MyMetrics extends MyInstrumentation implements MetricsSource {

          final MetricsRegistry registry = new MetricsRegistry("myRecord");
          final MetricMutableGaugeInt gauge0 =
              registry.newGauge("myGauge", "my gauge description", 0);
          final MetricMutableCounterLong counter0 =
              registry.newCounter("myCounter", "my metric description", 0L);
          final MetricMutaleStat stat0 =
              registry.newStat("myStat", "my stat description", "ops", "time");

          @Override public void setGauge0(int value) { gauge0.set(value); }
          @Override public void incrCounter0() { counter0.incr(); }
          @Override public void addStat0(long elapsed) { stat0.add(elapsed); }

          public void getMetrics(MetricsBuilder builder, boolean all) {
            registry.snapshot(builder.addRecord(registry.name()), all);
          }

        }

Note, in this example we introduced the following:

MyInstrumentation
  This is usually an abstract class (or interface) to define an instrumentation interface (incrCounter0 etc.) that allows different implementations. This is a mechanism to allow different metrics systems to be used at runtime via configuration.
MetricsRegistry
  This is a library class for easy creation and manipulation of mutable metrics.
MetricMutable[Gauge*|Counter*|Stat]
  These are library classes to manage mutable metrics for implementations of metrics sources. They produce immutable gauge and counters (Metric[Gauge*|Counter*]) for downstream consumption (sinks) upon `snapshot`. The `MetricMutableStat` in particular, provides a way to measure latency and throughput of an operation. In this particular case, it produces a long counter "myStat_num_ops" and double gauge "myStat_avg_time" when snapshotted.

## Migration from previous system

Users of the previous metrics system would notice the lack of `context` prefix in the configuration examples. The new metrics system decouples the concept for context (for grouping) with the implementation where a particular context object does the updating and publishing of metrics, which causes problems when you want to have a single context to be consumed by multiple backends. You would also have to configure an implementation instance per context, even if you have a backend that can handle multiple contexts (file, gangalia etc.):

Before | After
--- | ---
        context1.class=org.hadoop.metrics.file.FileContext
        context2.class=org.hadoop.metrics.file.FileContext
        ...
        contextn.class=org.hadoop.metrics.file.FileContext
        myprefix.sink.file.class=org.hadoop.metrics2.sink.FileSink

In the new metrics system, you can simulate the previous behavior by using the context option in the sink options like the following:

Before | After
--- | ---
        context0.class=org.hadoop.metrics.file.FileContext
        context0.fileName=context0.out
        context1.class=org.hadoop.metrics.file.FileContext
        context1.fileName=context1.out
        ...
        contextn.class=org.hadoop.metrics.file.FileContext
        contextn.fileName=contextn.out
        myprefix.sink.*.class=org.apache.hadoop.metrics2.sink.FileSink
        myprefix.sink.file0.context=context0
        myprefix.sink.file0.filename=context1.out
        myprefix.sink.file1.context=context1
        myprefix.sink.file1.filename=context1.out
        ...
        myprefix.sink.filen.context=contextn
        myprefix.sink.filen.filename=contextn.out

to send metrics of a particular context to a particular backend. Note, `myprefix` is an arbitrary prefix for configuration groupings, typically they are the name of a particular process (`namenode`, `jobtracker`, etc.)