@InterfaceAudience.Public @InterfaceStability.Evolving
See: Description
Interface | Description |
---|---|
MetricsCollector |
The metrics collector interface
|
MetricsInfo |
Interface to provide immutable metainfo for metrics.
|
MetricsPlugin |
The plugin interface for the metrics framework
|
MetricsRecord |
An immutable snapshot of metrics with a timestamp
|
MetricsSink |
The metrics sink interface.
|
MetricsSource |
The source of metrics information.
|
MetricsSystemMXBean |
The JMX interface to the metrics system
|
MetricsVisitor |
A visitor interface for metrics
|
Class | Description |
---|---|
AbstractMetric |
The immutable metric
|
MetricsFilter |
The metrics filter interface.
|
MetricsRecordBuilder |
The metrics record builder interface
|
MetricsSystem |
The metrics system interface.
|
MetricsTag |
Immutable tag for metrics (for grouping on host/queue/username etc.)
|
Exception | Description |
---|---|
MetricsException |
A general metrics exception wrapper
|
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
MetricsSource
interface
or the even simpler and more concise and declarative metrics annotations.
The consumers of metrics just need to implement the simple
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.
org.apache.hadoop.metrics2.annotation
org.apache.hadoop.metrics2.impl
org.apache.hadoop.metrics2.lib
Gauge
*|
Counter
*|
Stat
] and
MetricsRegistry
.
org.apache.hadoop.metrics2.filter
GlobFilter
and
RegexFilter
.
org.apache.hadoop.metrics2.source
JvmMetrics
.
org.apache.hadoop.metrics2.sink
FileSink
.
org.apache.hadoop.metrics2.util
MetricsCache
.
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
annotation is
used to indicate that the class is a metrics source.
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 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.
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:
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());
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.
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(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:
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.
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.)
Copyright © 2015 Apache Software Foundation. All rights reserved.