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    org.apache.hadoop.metrics
  

This package defines an API for reporting performance metric information.

The API is abstract so that it can be implemented on top of
a variety of metrics client libraries.  The choice of 
client library is a configuration option, and different 
modules within the same application can use
different metrics implementation libraries.

Sub-packages:

    org.apache.hadoop.metrics.spi
    The abstract Server Provider Interface package. Those wishing to
    integrate the metrics API with a particular metrics client library should 
    extend this package.
    
    org.apache.hadoop.metrics.file
    An implementation package which writes the metric data to 
    a file, or sends it to the standard output stream.
 
     org.apache.hadoop.metrics.ganglia
    An implementation package which sends metric data to 
    Ganglia.


Introduction to the Metrics API

Here is a simple example of how to use this package to report a single
metric value:
    private ContextFactory contextFactory = ContextFactory.getFactory();
    
    void reportMyMetric(float myMetric) {
        MetricsContext myContext = contextFactory.getContext("myContext");
        MetricsRecord myRecord = myContext.getRecord("myRecord");
        myRecord.setMetric("myMetric", myMetric);
        myRecord.update();
    }

  
In this example there are three names:

  myContext
  The context name will typically identify either the application, or else a
  module 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 
  "cacheStats" for reporting a number of statistics relating to the usage of
  some cache in your application.
  
  myMetric
  This identifies a particular metric.  For example, you might have metrics
  named "cache_hits" and "cache_misses".
  


Tags

In some cases it is useful to have multiple records with the same name. For 
example, suppose that you want to report statistics about each disk on a computer. 
In this case, the record name would be something like "diskStats", but you also
need to identify the disk which is done by adding a tag to the record.
The code could look something like this:
    private MetricsRecord diskStats =
            contextFactory.getContext("myContext").getRecord("diskStats");
            
    void reportDiskMetrics(String diskName, float diskBusy, float diskUsed) {
        diskStats.setTag("diskName", diskName);
        diskStats.setMetric("diskBusy", diskBusy);
        diskStats.setMetric("diskUsed", diskUsed);
        diskStats.update();
    }


Buffering and Callbacks

Data is not sent immediately to the metrics system when 
MetricsRecord.update() is called. Instead it is stored in an
internal table, and the contents of the table are sent periodically.
This can be important for two reasons:

    It means that a programmer is free to put calls to this API in an 
    inner loop, since updates can be very frequent without slowing down
    the application significantly.
    Some implementations can gain efficiency by combining many metrics 
    into a single UDP message.


The API provides a timer-based callback via the 
registerUpdater() method.  The benefit of this
versus using java.util.Timer is that the callbacks will be done 
immediately before sending the data, making the data as current as possible.

Configuration

It is possible to programmatically examine and modify configuration data
before creating a context, like this:
    ContextFactory factory = ContextFactory.getFactory();
    ... examine and/or modify factory attributes ...
    MetricsContext context = factory.getContext("myContext");

The factory attributes can be examined and modified using the following
ContextFactorymethods:

    Object getAttribute(String attributeName)
    String[] getAttributeNames()
    void setAttribute(String name, Object value)
    void removeAttribute(attributeName)



ContextFactory.getFactory() initializes the factory attributes by
reading the properties file hadoop-metrics.properties if it exists 
on the class path.


A factory attribute named:
contextName.class

should have as its value the fully qualified name of the class to be 
instantiated by a call of the CodeFactory method
getContext(contextName).  If this factory attribute is not 
specified, the default is to instantiate 
org.apache.hadoop.metrics.file.FileContext.


Other factory attributes are specific to a particular implementation of this 
API and are documented elsewhere.  For example, configuration attributes for
the file and Ganglia implementations can be found in the javadoc for 
their respective packages.