logging improvements for Hadoop
-------------------------------
Key: HADOOP-211
URL: http://issues.apache.org/jira/browse/HADOOP-211
Project: Hadoop
Type: Improvement
Versions: 0.2
Reporter: Sameer Paranjpye
Assigned to: Sameer Paranjpye
Priority: Minor
Fix For: 0.3
Here's a proposal for some impovements to the way Hadoop does logging. It
advocates 3
broad changes to the way logging is currently done, these being:
- The use of a uniform logging format by all Hadoop subsystems
- The use of Apache commons logging as a facade above an underlying logging
framework
- The use of Log4J as the underlying logging framework instead of
java.util.logging
This is largely polishing work, but it seems like it would make log analysis
and debugging
easier in the short term. In the long term, it would future proof logging to
the extent of
allowing the logging framework used to change while requiring minimal code
change. The
propos changes are motivated by the following requirements which we think
Hadoops
logging should meet:
- Hadoops logs should be amenable to analysis by tools like grep, sed, awk etc.
- Log entries should be clearly annotated with a timestamp and a logging level
- Log entries should be traceable to the subsystem from which they originated
- The logging implementation should allow log entries to be annotated with
source code
location information like classname, methodname, file and line number, without
requiring
code changes
- It should be possible to change the logging implementation used without
having to change
thousands of lines of code
- The mapping of loggers to destinations (files, directories, servers etc.)
should be
specified and modifiable via configuration
Uniform logging format:
All Hadoop logs should have the following structure.
<Header>\n
<LogEntry>\n [<Exception>\n]
.
.
.
where the header line specifies the format of each log entry. The header line
has the format:
'# <Fieldname> <Fieldname>...\n'.
The default format of each log entry is: '# Timestamp Level LoggerName
Message', where:
- Timestamp is a date and time in the format MM/DD/YYYY:HH:MM:SS
- Level is the logging level (FATAL, WARN, DEBUG, TRACE, etc.)
- LoggerName is the short name of the logging subsystem from which the message
originated e.g.
fs.FSNamesystem, dfs.Datanode etc.
- Message is the log message produced
Why Apache commons logging and Log4J?
Apache commons logging is a facade meant to be used as a wrapper around an
underlying logging
implementation. Bridges from Apache commons logging to popular logging
implementations
(Java logging, Log4J, Avalon etc.) are implemented and available as part of the
commons logging
distribution. Implementing a bridge to an unsupported implementation is fairly
striaghtforward
and involves the implementation of subclasses of the commons logging LogFactory
and Logger
classes. Using Apache commons logging and making all logging calls through it
enables us to
move to a different logging implementation by simply changing configuration in
the best case.
Even otherwise, it incurs minimal code churn overhead.
Log4J offers a few benefits over java.util.logging that make it a more
desirable choice for the
logging back end.
- Configuration Flexibility: The mapping of loggers to destinations (files,
sockets etc.)
can be completely specified in configuration. It is possible to do this with
Java logging as
well, however, configuration is a lot more restrictive. For instance, with Java
logging all
log files must have names derived from the same pattern. For the namenode, log
files could
be named with the pattern "%h/namenode%u.log" which would put log files in the
user.home
directory with names like namenode0.log etc. With Log4J it would be possible to
configure
the namenode to emit log files with different names, say heartbeats.log,
namespace.log,
clients.log etc. Configuration variables in Log4J can also have the values of
system
properties embedded in them.
- Takes wrappers into account: Log4J takes into account the possibility that an
application
may be invoking it via a wrapper, such as Apache commons logging. This is
important because
logging event objects must be able to infer the context of the logging call
such as classname,
methodname etc. Inferring context is a relatively expensive operation that
involves creating
an exception and examining the stack trace to find the frame just before the
first frame
of the logging framework. It is therefore done lazily only when this
information actually
needs to be logged. Log4J can be instructed to look for the frame corresponding
to the wrapper
class, Java logging cannot. In the case of Java logging this means that a) the
bridge from
Apache commons logging is responsible for inferring the calling context and
setting it in the
logging event and b) this inference has to be done on every logging call
regardless of whether
or not it is needed.
- More handy features: Log4J has some handy features that Java logging doesn't.
A couple
of examples of these:
a) Date based rolling of log files
b) Format control through configuration. Log4J has a PatternLayout class that
can be
configured to generate logs with a user specified pattern. The logging format
described
above can be described as "%d{MM/dd/yyyy:HH:mm:SS} %c{2} %p %m". The format
specifiers
indicate that each log line should have the date and time followed by the
logger name followed
by the logging level or priority followed by the application generated message.
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