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From Apache Wiki <wikidi...@apache.org>
Subject [Lucene-hadoop Wiki] Update of "HadoopMapRedClasses" by KimoonKim
Date Sat, 16 Sep 2006 01:05:50 GMT
Dear Wiki user,

You have subscribed to a wiki page or wiki category on "Lucene-hadoop Wiki" for change notification.

The following page has been changed by KimoonKim:
http://wiki.apache.org/lucene-hadoop/HadoopMapRedClasses

New page:
== JobInProgress ==

!JobInProgress represents a job as it is being tracked by !JobTracker.

!JobInProgress contains two sets of !TaskInProgress instances: 

   * !TaskInProgress maps[], an array holding one tip per split
   * !TaskInProgress reduces[], an array holding one tip per partition

Method initTask() fills out those tips. initTask also creates:

   * hostMaps[], which cotains a mapping from a host to file split
     id's that the host is holding on DFS.

!JobInProgress also offers two methods for creating a !Task instance to
run, out of maps[] and reduces[]:

   * obtainNewMapTask() returns a map task for a given !TaskTracker to run.
   * obtainNewReduceTask() returns a reduce task.

Both delegate implementation to findNewTask(), which searches for a tip
in order below:

   * cachedTasks for a tip whose input is hosted on the given
     host. still skip if the input is already processed by other task
     or the input has failed once on the host.
   * regular task, which means a tip with an input that hasn't run.
   * speculative tasks, which means a tip with an input that's already
     being run by other task, but the progress is slow.
   * a failed tip, which means a tip with a input that was run by a failed task.
To randomize it a bit, search after cachedTasks starts with
firstMapsToTry or firstReduceToTry, which is set to recently failed
task's input + 1.

!Task status is updated normally when !JobTracker calls !JobInProgress.updateTaskStatus()
as
!JobTracker.emitHeartbeat() processes a !TaskTracker's heartbeat. updateTaskStatus then calls
!TaskInProgress.updateStatus(). If the tip says success or failure,
updateTaskStatus() calls completedTask() or
failedTask(). completeTask() checks if the tip is last partition, and
if so declares job finish. failedTask() sees if the tip wants to give
up after too many failed attempts, then declares job failure.

failedTask() can be directly called by !JobTracker when a launching
task is timed out without any heartbeat from task tracker, or when a
task tracker is found to be lost. (There must be a third event where a
map output is found to be corrupt or impossible to copy for whatever
reason)

A job's schedule status is updated in:

   * !JobStatus status

== TaskInProgress ==

!TaskInProgress represents a set of tasks for a given unique input, where input is a split
for map
task or a partition for reduce task.

Usually there would be only one task per tip, but speculative
execution and retry mechanism can create multiple tasks for a given
input.

!TaskInProgress has two constructor, one that takes input !FileSplit
(for map task), and another that takes partition number (for reduce
task). These two are invoked by !JobInProgress.initTask().

!TaskInProgress contains:

   * recentTasks, instance(s) of !Task in flight for the given input

method getTaskToRun() populates recentTasks with either !MapTask or
!ReduceTask instance and then returns the !Task to caller. !Task ids are
obtained from a field usableTaskids.

Note there is also:

   * taskStatuses, a set of !TaskStatus instances that contains status
     per task. keyed by task id.

updateStatus() puts latest status of a task into taskStatues when a
tasktracer emits heartbeat containing the task status.

method completed() or failedSubTask() wraps up the life of a task by
removing it from recentTasks. Each is called by
!JobInProgress.completeTask() or failedTask() respectively.

Note there is a class !TaskTracker.TaskInProgress, which is internal to
!TaskTracker. !TaskTracker.TaskInProgress, unlike the other one, has 1:1 
mapping with a !Task. i.e. It represents only one !Task.

== TaskTrackerStatus ==

!TaskTrackerStatus represents a status of a task tracker daemon as it's
monitored inside !JobTracker.

It also is used as a parameter to certain methods as representative of
task tracker node. Example is obtainNewMapTask() or
obtainNewReduceTask() of !TaskInProgress.

It contains a set of task reports in:

   * Vector taskReports, a vector of !TaskStatus instances.

, when !JobTracker.emitHeartBeat() is invoked with a !TaskTrackerStatus
instance.

== TaskTracker ==

!TaskTracker is a daemon process running on each of worker node.

!TaskTracker communicates with !JobTracker via two RPC agents:

   * taskReportServer, for reporting to !JobTracker's requests for task status (?)
   * jobClient, for getting new task from and sending heartbeats to !JobTracker.

!TaskTracker contains instances of !TaskTracker.TaskInProgress in two fields:

   * tasks, for all tasks in consideration indexed by taskid strings.
   * runningTasks, for subset of tasks that are being run.

A new instance of !Task is obtained by calling
jobClient.pollForNewTasks(), which will drive !JobTracker to eventually
call !TaskInProgress.getTaskToRun(). Note again that an instance of
!TaskTracker.TaskInProgress is created, containing the new !Task, then
gets added into tasks and runningTasks.

method startNewTask() takes the new !Task then starts the actual
sequence for running user code for the task. Eventually, the user code
is executed in a child process. Child process communicates with the
parent !TaskTracker daemon via RPC. The interface for the RPC is
!TaskUmblicalProtocal. !TaskTracker inherts and implements this
protocol.

== TaskTracker.TaskInProgress ==

!TaskTracker.TaskInProgress represents a single task as it's being
tracked by !TaskTracker daemon.

It contains an instance of a !Task. It also contains an instance of
!TaskRunner, a shadow thread that monitors the !Task as it's run in
child process.


== TaskRunner ==

!TaskRunner has two subclasses, !MapTaskRunner and !ReduceTaskRunner,
which are instantiated by !Task.createRunner, when !MapTask or
!ReduceTask is entity under the !Task interface.

!TaskRunner.run(), which is the thread entry point, first invokes
prepare(). !ReduceTaskRunner heavily implements prepare() to fetch all
input files for the reduce work. Note they are produced by map tasks,
so come from many different nodes.

Then !TaskRunner.run() loads user code Jar files, and calls
runChild(), which creates child process. In child java process,
!TaskTracker.Child.main() is passed as process entry point, along with
taskid string, and a port for !TaskTracker's !TaskUmblicalProtocal.

== TaskTracker.Child.main() ==

!TaskTracker.Child.main() offers entry point for child java process so
that user code for map or reduce work can be called.

!TaskTracker.Child.main() first gets an instance of !Task and job config
via RPC using the !TaskUmblicalProtocol. Then it calls !Task.run().


== MapTask ==

!MapTask offers method run() that calls !MapRunner.run(), which in turn
calls the user-supplied Mapper.map().

== ReduceTask ==

Similarly to !MapTask, !ReduceTask offers run() that sorts input files
using !SequenceFile.Sorter.sort(), and then calls user-supplied
Reducer.reduce().

== ReduceTaskRunner ==

Key contribution is prepare() that copies all input files from many hosts.
Note this code is not part of child process. only !Task.run()() is run by child.


== InputFormat ==

!InputFormat is an interface for instantiating file splits and the
readers for map task.

   * !FileSplit[] getSplits(), creates an array of !FileSplit for the
     job. A !FileSplit is a span of a given file.
   * !RecordReader getRecordReader(), creates a reader for a given split.

Note the resuling split count can be more than what the config says,
as a split boundary can be drawn around DFS block. This is actually
implementation offered by !InputFormatBase, which then gets specialized
into !SequenceFileInputFormat.

== OutputFormat ==

!OutputFormat is an interface for instatiating writer for consuming
output of reduce task.

   * !RecordWriter getRecordWriter(), creates a writer for a given job.

== io.SequenceFile.Sorter ==

Key method is sort() which calls mergePass() as 1st pass, then
repeatedly calls sortPass() until it has one output file. 

One thing to note is that this class uses the output file in unoffical
way. A pysical file contains multiple segments that becomes input for
merge for next phase. Each segment is in !SequenceFile format. 

The container file is named with numeric suffix that represents pass
id.  sortPass() thus creates file.0 that contains a large number of
segments. Then each of next pass reduces the segments by merging a
subset of segments from the input file.

== JobTracker ==

!JobTracker is a daemon per pool that administers all aspects of mapred
activities.

===== jobs =====

!JobTracker keeps all the current jobs by containing instances of !JobInProgress in:

   * jobs: map from jobid string to !JobInProgress
   * jobsByArrival: same set of !JobInProgress ordered by arrival time

Main methods that access the two above are:

   * submitJob(): creates/adds a !JobInProgress to jobs and jobsByArrival
   * pollForNewTask(): takes a task tracker id and finds a task by
     going through jobsByArrival. A job is selected only when its
     predecessor is running.
   
===== task tracker and tasks: =====

   * taskTrackers: map from task tracker id string to !TaskTrackerStatus
   * trackerToTaskMap: map from task tracker id string to a set of task id strings
   * taskidToTrackerMap: reverse of the above. map from taskid to tracker id string.

Note there is no map from taskid string to !Task instances.

===== TaskInProgress: =====

   * taskidToTIPMap: map from task id string to TIP instance

Note !JobInProgress also has all tip's.

===== Asynchronous works =====

!JobTracker is event-driven. It maintains a couple of active entities:

   * interTrackerServer: an RPC agent for driving !JobTracker's
     implementation of !InterTrackerProtocol and !JobSubmissionProtocol(?)
   * initJobsThread, initJobs: thread for initializing !JobInProgress
     as arriving at jobInitQueue.
   * retireJobsThread, retireJobs: to scan jobs and to remove ones
     that finished long time ago. This is the only way that a job gets
     removed from jobs and jobsByArrival.
   * expireTrackersThread, expireTracker, trackerExpiryQueue: to
     remove task trackers that seem dead
   * expireLaunchingTasksThread, expireLaunchingTasks: to timeout a
     task that has never reported back.



== id strings ==

===== job id  =====

Job id is a string that uses format below:

   * jobId: "job_" uniqueId

uniqueId is a unique numeric sequence id, which is basically 
!JobTracker.nextJobId++. The code is in !JobTracker.createUniqueId().

uniqueId is then set to !JobInProgress.uniqueString, and then passed to
!TaskInProgress's constructors.

===== TaskInProgress id string =====

Tip id is a string that uses format below:

   * map tip: "tip_" !JobInProgress.uniqueString "_m_" splitId
   * reduce tip: "tip_" !JobInProgress.uniqueString "_r_" partitionId

Tip id is set to !TaskInProgress.id. The code is in !TaskInProgress.init().

===== task id string =====

!Task id is a string:

   * map task id: "task_" !JobInProgress.uniqueString "_m_" splitId "_" i
   * reduce task id: "task_" !JobInProgress.uniqueString "_r_" partitionId "_" i

Above, i is 0 to max-1, where max is !TaskInProgress.MAX_TASK_EXECS +
MAX_TASK_FAILURES.

!TaskInProgress.init() also creates all these task ids, and set them to
!TaskInProgress.totalTaskIds[] and usuableTaskIds.
   
== work dirs and path ==

===== JobTracker =====

!JobTracker has a home dir called "jobTracker" on local file system,
which is value of !JobTracker.SUBDIR.

Under the dir, each !JobInProgress copies two files from user-submitted
location:

   * job file: "jobTracker/" jobId ".xml"
   * jar file: "jobTracker/" jobid ".jar"

These two paths are then set to !JobInProgress.localJobFile and
localJobFile, respectively.

===== TaskTracker =====

Similarly, !TaskTracker has a home dir called "taskTracker". Under
there, each task creates a subdir:

   * task dir: "taskTracker/"  taskId

Under task dir, jobFile and jarFile are created as:

   * job file: "taskTracker/" taskId "/job.xml"
   * jar file: "taskTracker/" taskId "/job.jar"
 
Jar file is just a verbatim copy. But job file is a localized one to
the task, as it's modified by !Task.localizeConfiguration(). Also the
local jar file's path is set in the config as the only location of
jar. Then !Task.jobFile and !Task.conf all are set to this localized one.

Code sequence for above starts with
!TaskTracker.TaskInProgress.launchTask().

Each task also has workdir at top level. Map output files go under this dir as:

   * map output for a partition: taskId "/part-" partitionId ".out"

Above, taskId has "_m_" in it as its map task id.

When the map outputs for a partition is copied to the reduce task, the
local files are created as:

   * reduce input from a split: taskId  "/map_" splitId ".out"

Above, taskId has "_r_" in it, as it's reduce task id. Near the end,
reduce creates a single sort file named:

   * sort output: taskId "/all.2"

Interlim merge pass file for the sort will be:

   * pass file: taskId "/all.2." passId

, where passId starts with 0.

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