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/**
Metrics 2.0
- Overview
- Getting Started
- Configuration
- Metrics Filtering
- Metrics Instrumentation Strategy
- Migration from previous system
Overview
This package provides a framework for metrics instrumentation
and publication.
The framework provides a variety of ways to implement metrics
instrumentation easily via the simple
{@link org.apache.hadoop.metrics2.MetricsSource} interface
or the even simpler and more concise and declarative metrics annotations.
The consumers of metrics just need to implement the simple
{@link org.apache.hadoop.metrics2.MetricsSink} interface. 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. All the metrics are also published and queryable via the
standard JMX MBean interface. This document targets the framework users.
Framework developers could also consult the
design
document for architecture and implementation notes.
Sub-packages
org.apache.hadoop.metrics2.annotation- Public annotation interfaces for simpler metrics instrumentation.
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
Mutable[{@link org.apache.hadoop.metrics2.lib.MutableGauge Gauge}*|
{@link org.apache.hadoop.metrics2.lib.MutableCounter Counter}*|
{@link org.apache.hadoop.metrics2.lib.MutableStat Stat}] and
{@link org.apache.hadoop.metrics2.lib.MetricsRegistry}.
-
org.apache.hadoop.metrics2.filter
- Builtin metrics filter implementations include the
{@link org.apache.hadoop.metrics2.filter.GlobFilter} and
{@link org.apache.hadoop.metrics2.filter.RegexFilter}.
org.apache.hadoop.metrics2.source- Builtin metrics source implementations including the
{@link org.apache.hadoop.metrics2.source.JvmMetrics}.
-
org.apache.hadoop.metrics2.sink
- Builtin metrics sink implementations including the
{@link org.apache.hadoop.metrics2.sink.FileSink}.
-
org.apache.hadoop.metrics2.util
- General utilities for implementing metrics sinks etc., including the
{@link org.apache.hadoop.metrics2.util.MetricsCache}.
Getting started
Implementing metrics sources
Using annotations Using MetricsSource interface
@Metrics(context="MyContext")
class MyStat {
@Metric("My metric description")
public int getMyMetric() {
return 42;
}
}
class MyStat implements MetricsSource {
@Override
public void getMetrics(MetricsCollector collector, boolean all) {
collector.addRecord("MyStat")
.setContext("MyContext")
.addGauge(info("MyMetric", "My metric description"), 42);
}
}
In this example we introduced the following:
- @Metrics
- The {@link org.apache.hadoop.metrics2.annotation.Metrics} annotation is
used to indicate that the class is a metrics source.
- MyContext
- The optional context name typically identifies either the
application, or a group of modules within an application or
library.
- MyStat
- The class name is used (by default, or specified by name=value parameter
in the Metrics annotation) as the metrics record name 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.
- @Metric
- The {@link org.apache.hadoop.metrics2.annotation.Metric} annotation
identifies a particular metric, which in this case, is the
result of the method call getMyMetric of the "gauge" (default) type,
which means it can vary in both directions, compared with a "counter"
type, which can only increase or stay the same. The name of the metric
is "MyMetric" (inferred from getMyMetric method name by default.) The 42
here is the value of the metric which can be substituted with any valid
java expressions.
Note, the {@link org.apache.hadoop.metrics2.MetricsSource} interface is
more verbose but more flexible,
allowing generated metrics names and multiple records. In fact, the
annotation interface is implemented with the MetricsSource interface
internally.
Implementing metrics sinks
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 "MyStat" 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.register(new MyStat());
Metrics system configuration
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 jvm, rpc, hdfs and mapred, 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
metric.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:
@Metrics(about="My metrics description", context="MyContext")
class MyMetrics extends MyInstrumentation {
@Metric("My gauge description") MutableGaugeInt gauge0;
@Metric("My counter description") MutableCounterLong counter0;
@Metric("My rate description") MutableRate rate0;
@Override public void setGauge0(int value) { gauge0.set(value); }
@Override public void incrCounter0() { counter0.incr(); }
@Override public void addRate0(long elapsed) { rate0.add(elapsed); }
}
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 could be a mechanism to allow different metrics
systems to be used at runtime via configuration.
- Mutable[Gauge*|Counter*|Rate]
- 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 MutableRate
in particular, provides a way to measure latency and throughput of an
operation. In this particular case, it produces a long counter
"Rate0NumOps" and double gauge "Rate0AvgTime" 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.)
*/
@InterfaceAudience.Public
@InterfaceStability.Evolving
package org.apache.hadoop.metrics2;
import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;