jqueue.py

#
#

# Copyright (C) 2006, 2007, 2008 Google Inc.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
# 02110-1301, USA.


"""Module implementing the job queue handling.

Locking: there's a single, large lock in the L{JobQueue} class. It's
used by all other classes in this module.

@var JOBQUEUE_THREADS: the number of worker threads we start for
    processing jobs

"""

import os
import logging
import threading
import errno
import re
import time
import weakref

from ganeti import constants
from ganeti import serializer
from ganeti import workerpool
from ganeti import opcodes
from ganeti import errors
from ganeti import mcpu
from ganeti import utils
from ganeti import jstore
from ganeti import rpc


JOBQUEUE_THREADS = 25
JOBS_PER_ARCHIVE_DIRECTORY = 10000


class CancelJob(Exception):
  """Special exception to cancel a job.

  """


def TimeStampNow():
  """Returns the current timestamp.

  @rtype: tuple
  @return: the current time in the (seconds, microseconds) format

  """
  return utils.SplitTime(time.time())


class _QueuedOpCode(object):
  """Encapsulates an opcode object.

  @ivar log: holds the execution log and consists of tuples
  of the form C{(log_serial, timestamp, level, message)}
  @ivar input: the OpCode we encapsulate
  @ivar status: the current status
  @ivar result: the result of the LU execution
  @ivar start_timestamp: timestamp for the start of the execution
  @ivar exec_timestamp: timestamp for the actual LU Exec() function invocation
  @ivar stop_timestamp: timestamp for the end of the execution

  """
  __slots__ = ["input", "status", "result", "log",
               "start_timestamp", "exec_timestamp", "end_timestamp",
               "__weakref__"]

  def __init__(self, op):
    """Constructor for the _QuededOpCode.

    @type op: L{opcodes.OpCode}
    @param op: the opcode we encapsulate

    """
    self.input = op
    self.status = constants.OP_STATUS_QUEUED
    self.result = None
    self.log = []
    self.start_timestamp = None
    self.exec_timestamp = None
    self.end_timestamp = None

  @classmethod
  def Restore(cls, state):
    """Restore the _QueuedOpCode from the serialized form.

    @type state: dict
    @param state: the serialized state
    @rtype: _QueuedOpCode
    @return: a new _QueuedOpCode instance

    """
    obj = _QueuedOpCode.__new__(cls)
    obj.input = opcodes.OpCode.LoadOpCode(state["input"])
    obj.status = state["status"]
    obj.result = state["result"]
    obj.log = state["log"]
    obj.start_timestamp = state.get("start_timestamp", None)
    obj.exec_timestamp = state.get("exec_timestamp", None)
    obj.end_timestamp = state.get("end_timestamp", None)
    return obj

  def Serialize(self):
    """Serializes this _QueuedOpCode.

    @rtype: dict
    @return: the dictionary holding the serialized state

    """
    return {
      "input": self.input.__getstate__(),
      "status": self.status,
      "result": self.result,
      "log": self.log,
      "start_timestamp": self.start_timestamp,
      "exec_timestamp": self.exec_timestamp,
      "end_timestamp": self.end_timestamp,
      }


class _QueuedJob(object):
  """In-memory job representation.

  This is what we use to track the user-submitted jobs. Locking must
  be taken care of by users of this class.

  @type queue: L{JobQueue}
  @ivar queue: the parent queue
  @ivar id: the job ID
  @type ops: list
  @ivar ops: the list of _QueuedOpCode that constitute the job
  @type log_serial: int
  @ivar log_serial: holds the index for the next log entry
  @ivar received_timestamp: the timestamp for when the job was received
  @ivar start_timestmap: the timestamp for start of execution
  @ivar end_timestamp: the timestamp for end of execution
  @ivar lock_status: In-memory locking information for debugging
  @ivar change: a Condition variable we use for waiting for job changes

  """
  # pylint: disable-msg=W0212
  __slots__ = ["queue", "id", "ops", "log_serial",
               "received_timestamp", "start_timestamp", "end_timestamp",
               "lock_status", "change",
               "__weakref__"]

  def __init__(self, queue, job_id, ops):
    """Constructor for the _QueuedJob.

    @type queue: L{JobQueue}
    @param queue: our parent queue
    @type job_id: job_id
    @param job_id: our job id
    @type ops: list
    @param ops: the list of opcodes we hold, which will be encapsulated
        in _QueuedOpCodes

    """
    if not ops:
      # TODO: use a better exception
      raise Exception("No opcodes")

    self.queue = queue
    self.id = job_id
    self.ops = [_QueuedOpCode(op) for op in ops]
    self.log_serial = 0
    self.received_timestamp = TimeStampNow()
    self.start_timestamp = None
    self.end_timestamp = None

    # In-memory attributes
    self.lock_status = None

    # Condition to wait for changes
    self.change = threading.Condition(self.queue._lock)

  def __repr__(self):
    status = ["%s.%s" % (self.__class__.__module__, self.__class__.__name__),
              "id=%s" % self.id,
              "ops=%s" % ",".join([op.input.Summary() for op in self.ops])]

    return "<%s at %#x>" % (" ".join(status), id(self))

  @classmethod
  def Restore(cls, queue, state):
    """Restore a _QueuedJob from serialized state:

    @type queue: L{JobQueue}
    @param queue: to which queue the restored job belongs
    @type state: dict
    @param state: the serialized state
    @rtype: _JobQueue
    @return: the restored _JobQueue instance

    """
    obj = _QueuedJob.__new__(cls)
    obj.queue = queue
    obj.id = state["id"]
    obj.received_timestamp = state.get("received_timestamp", None)
    obj.start_timestamp = state.get("start_timestamp", None)
    obj.end_timestamp = state.get("end_timestamp", None)

    # In-memory attributes
    obj.lock_status = None

    obj.ops = []
    obj.log_serial = 0
    for op_state in state["ops"]:
      op = _QueuedOpCode.Restore(op_state)
      for log_entry in op.log:
        obj.log_serial = max(obj.log_serial, log_entry[0])
      obj.ops.append(op)

    # Condition to wait for changes
    obj.change = threading.Condition(obj.queue._lock)

    return obj

  def Serialize(self):
    """Serialize the _JobQueue instance.

    @rtype: dict
    @return: the serialized state

    """
    return {
      "id": self.id,
      "ops": [op.Serialize() for op in self.ops],
      "start_timestamp": self.start_timestamp,
      "end_timestamp": self.end_timestamp,
      "received_timestamp": self.received_timestamp,
      }

  def CalcStatus(self):
    """Compute the status of this job.

    This function iterates over all the _QueuedOpCodes in the job and
    based on their status, computes the job status.

    The algorithm is:
      - if we find a cancelled, or finished with error, the job
        status will be the same
      - otherwise, the last opcode with the status one of:
          - waitlock
          - canceling
          - running

        will determine the job status

      - otherwise, it means either all opcodes are queued, or success,
        and the job status will be the same

    @return: the job status

    """
    status = constants.JOB_STATUS_QUEUED

    all_success = True
    for op in self.ops:
      if op.status == constants.OP_STATUS_SUCCESS:
        continue

      all_success = False

      if op.status == constants.OP_STATUS_QUEUED:
        pass
      elif op.status == constants.OP_STATUS_WAITLOCK:
        status = constants.JOB_STATUS_WAITLOCK
      elif op.status == constants.OP_STATUS_RUNNING:
        status = constants.JOB_STATUS_RUNNING
      elif op.status == constants.OP_STATUS_CANCELING:
        status = constants.JOB_STATUS_CANCELING
        break
      elif op.status == constants.OP_STATUS_ERROR:
        status = constants.JOB_STATUS_ERROR
        # The whole job fails if one opcode failed
        break
      elif op.status == constants.OP_STATUS_CANCELED:
        status = constants.OP_STATUS_CANCELED
        break

    if all_success:
      status = constants.JOB_STATUS_SUCCESS

    return status

  def GetLogEntries(self, newer_than):
    """Selectively returns the log entries.

    @type newer_than: None or int
    @param newer_than: if this is None, return all log entries,
        otherwise return only the log entries with serial higher
        than this value
    @rtype: list
    @return: the list of the log entries selected

    """
    if newer_than is None:
      serial = -1
    else:
      serial = newer_than

    entries = []
    for op in self.ops:
      entries.extend(filter(lambda entry: entry[0] > serial, op.log))

    return entries

  def MarkUnfinishedOps(self, status, result):
    """Mark unfinished opcodes with a given status and result.

    This is an utility function for marking all running or waiting to
    be run opcodes with a given status. Opcodes which are already
    finalised are not changed.

    @param status: a given opcode status
    @param result: the opcode result

    """
    not_marked = True
    for op in self.ops:
      if op.status in constants.OPS_FINALIZED:
        assert not_marked, "Finalized opcodes found after non-finalized ones"
        continue
      op.status = status
      op.result = result
      not_marked = False


class _OpExecCallbacks(mcpu.OpExecCbBase):
  def __init__(self, queue, job, op):
    """Initializes this class.

    @type queue: L{JobQueue}
    @param queue: Job queue
    @type job: L{_QueuedJob}
    @param job: Job object
    @type op: L{_QueuedOpCode}
    @param op: OpCode

    """
    assert queue, "Queue is missing"
    assert job, "Job is missing"
    assert op, "Opcode is missing"

    self._queue = queue
    self._job = job
    self._op = op

  def NotifyStart(self):
    """Mark the opcode as running, not lock-waiting.

    This is called from the mcpu code as a notifier function, when the LU is
    finally about to start the Exec() method. Of course, to have end-user
    visible results, the opcode must be initially (before calling into
    Processor.ExecOpCode) set to OP_STATUS_WAITLOCK.

    """
    self._queue.acquire()
    try:
      assert self._op.status in (constants.OP_STATUS_WAITLOCK,
                                 constants.OP_STATUS_CANCELING)

      # All locks are acquired by now
      self._job.lock_status = None

      # Cancel here if we were asked to
      if self._op.status == constants.OP_STATUS_CANCELING:
        raise CancelJob()

      self._op.status = constants.OP_STATUS_RUNNING
      self._op.exec_timestamp = TimeStampNow()
    finally:
      self._queue.release()

  def Feedback(self, *args):
    """Append a log entry.

    """
    assert len(args) < 3

    if len(args) == 1:
      log_type = constants.ELOG_MESSAGE
      log_msg = args[0]
    else:
      (log_type, log_msg) = args

    # The time is split to make serialization easier and not lose
    # precision.
    timestamp = utils.SplitTime(time.time())

    self._queue.acquire()
    try:
      self._job.log_serial += 1
      self._op.log.append((self._job.log_serial, timestamp, log_type, log_msg))

      self._job.change.notifyAll()
    finally:
      self._queue.release()

  def ReportLocks(self, msg):
    """Write locking information to the job.

    Called whenever the LU processor is waiting for a lock or has acquired one.

    """
    # Not getting the queue lock because this is a single assignment
    self._job.lock_status = msg


class _JobQueueWorker(workerpool.BaseWorker):
  """The actual job workers.

  """
  def RunTask(self, job): # pylint: disable-msg=W0221
    """Job executor.

    This functions processes a job. It is closely tied to the _QueuedJob and
    _QueuedOpCode classes.

    @type job: L{_QueuedJob}
    @param job: the job to be processed

    """
    logging.info("Processing job %s", job.id)
    proc = mcpu.Processor(self.pool.queue.context, job.id)
    queue = job.queue
    try:
      try:
        count = len(job.ops)
        for idx, op in enumerate(job.ops):
          op_summary = op.input.Summary()
          if op.status == constants.OP_STATUS_SUCCESS:
            # this is a job that was partially completed before master
            # daemon shutdown, so it can be expected that some opcodes
            # are already completed successfully (if any did error
            # out, then the whole job should have been aborted and not
            # resubmitted for processing)
            logging.info("Op %s/%s: opcode %s already processed, skipping",
                         idx + 1, count, op_summary)
            continue
          try:
            logging.info("Op %s/%s: Starting opcode %s", idx + 1, count,
                         op_summary)

            queue.acquire()
            try:
              if op.status == constants.OP_STATUS_CANCELED:
                raise CancelJob()
              assert op.status == constants.OP_STATUS_QUEUED
              op.status = constants.OP_STATUS_WAITLOCK
              op.result = None
              op.start_timestamp = TimeStampNow()
              if idx == 0: # first opcode
                job.start_timestamp = op.start_timestamp
              queue.UpdateJobUnlocked(job)

              input_opcode = op.input
            finally:
              queue.release()

            # Make sure not to hold queue lock while calling ExecOpCode
            result = proc.ExecOpCode(input_opcode,
                                     _OpExecCallbacks(queue, job, op))

            queue.acquire()
            try:
              op.status = constants.OP_STATUS_SUCCESS
              op.result = result
              op.end_timestamp = TimeStampNow()
              queue.UpdateJobUnlocked(job)
            finally:
              queue.release()

            logging.info("Op %s/%s: Successfully finished opcode %s",
                         idx + 1, count, op_summary)
          except CancelJob:
            # Will be handled further up
            raise
          except Exception, err:
            queue.acquire()
            try:
              try:
                op.status = constants.OP_STATUS_ERROR
                if isinstance(err, errors.GenericError):
                  op.result = errors.EncodeException(err)
                else:
                  op.result = str(err)
                op.end_timestamp = TimeStampNow()
                logging.info("Op %s/%s: Error in opcode %s: %s",
                             idx + 1, count, op_summary, err)
              finally:
                queue.UpdateJobUnlocked(job)
            finally:
              queue.release()
            raise

      except CancelJob:
        queue.acquire()
        try:
          queue.CancelJobUnlocked(job)
        finally:
          queue.release()
      except errors.GenericError, err:
        logging.exception("Ganeti exception")
      except:
        logging.exception("Unhandled exception")
    finally:
      queue.acquire()
      try:
        try:
          job.lock_status = None
          job.end_timestamp = TimeStampNow()
          queue.UpdateJobUnlocked(job)
        finally:
          job_id = job.id
          status = job.CalcStatus()
      finally:
        queue.release()

      logging.info("Finished job %s, status = %s", job_id, status)


class _JobQueueWorkerPool(workerpool.WorkerPool):
  """Simple class implementing a job-processing workerpool.

  """
  def __init__(self, queue):
    super(_JobQueueWorkerPool, self).__init__("JobQueue",
                                              JOBQUEUE_THREADS,
                                              _JobQueueWorker)
    self.queue = queue


def _RequireOpenQueue(fn):
  """Decorator for "public" functions.

  This function should be used for all 'public' functions. That is,
  functions usually called from other classes. Note that this should
  be applied only to methods (not plain functions), since it expects
  that the decorated function is called with a first argument that has
  a '_queue_lock' argument.

  @warning: Use this decorator only after utils.LockedMethod!

  Example::
    @utils.LockedMethod
    @_RequireOpenQueue
    def Example(self):
      pass

  """
  def wrapper(self, *args, **kwargs):
    # pylint: disable-msg=W0212
    assert self._queue_lock is not None, "Queue should be open"
    return fn(self, *args, **kwargs)
  return wrapper


class JobQueue(object):
  """Queue used to manage the jobs.

  @cvar _RE_JOB_FILE: regex matching the valid job file names

  """
  _RE_JOB_FILE = re.compile(r"^job-(%s)$" % constants.JOB_ID_TEMPLATE)

  def __init__(self, context):
    """Constructor for JobQueue.

    The constructor will initialize the job queue object and then
    start loading the current jobs from disk, either for starting them
    (if they were queue) or for aborting them (if they were already
    running).

    @type context: GanetiContext
    @param context: the context object for access to the configuration
        data and other ganeti objects

    """
    self.context = context
    self._memcache = weakref.WeakValueDictionary()
    self._my_hostname = utils.HostInfo().name

    # Locking
    self._lock = threading.Lock()
    self.acquire = self._lock.acquire
    self.release = self._lock.release

    # Initialize
    self._queue_lock = jstore.InitAndVerifyQueue(must_lock=True)

    # Read serial file
    self._last_serial = jstore.ReadSerial()
    assert self._last_serial is not None, ("Serial file was modified between"
                                           " check in jstore and here")

    # Get initial list of nodes
    self._nodes = dict((n.name, n.primary_ip)
                       for n in self.context.cfg.GetAllNodesInfo().values()
                       if n.master_candidate)

    # Remove master node
    try:
      del self._nodes[self._my_hostname]
    except KeyError:
      pass

    # TODO: Check consistency across nodes

    # Setup worker pool
    self._wpool = _JobQueueWorkerPool(self)
    try:
      # We need to lock here because WorkerPool.AddTask() may start a job while
      # we're still doing our work.
      self.acquire()
      try:
        logging.info("Inspecting job queue")

        all_job_ids = self._GetJobIDsUnlocked()
        jobs_count = len(all_job_ids)
        lastinfo = time.time()
        for idx, job_id in enumerate(all_job_ids):
          # Give an update every 1000 jobs or 10 seconds
          if (idx % 1000 == 0 or time.time() >= (lastinfo + 10.0) or
              idx == (jobs_count - 1)):
            logging.info("Job queue inspection: %d/%d (%0.1f %%)",
                         idx, jobs_count - 1, 100.0 * (idx + 1) / jobs_count)
            lastinfo = time.time()

          job = self._LoadJobUnlocked(job_id)

          # a failure in loading the job can cause 'None' to be returned
          if job is None:
            continue

          status = job.CalcStatus()

          if status in (constants.JOB_STATUS_QUEUED, ):
            self._wpool.AddTask(job)

          elif status in (constants.JOB_STATUS_RUNNING,
                          constants.JOB_STATUS_WAITLOCK,
                          constants.JOB_STATUS_CANCELING):
            logging.warning("Unfinished job %s found: %s", job.id, job)
            try:
              job.MarkUnfinishedOps(constants.OP_STATUS_ERROR,
                                    "Unclean master daemon shutdown")
            finally:
              self.UpdateJobUnlocked(job)

        logging.info("Job queue inspection finished")
      finally:
        self.release()
    except:
      self._wpool.TerminateWorkers()
      raise

  @utils.LockedMethod
  @_RequireOpenQueue
  def AddNode(self, node):
    """Register a new node with the queue.

    @type node: L{objects.Node}
    @param node: the node object to be added

    """
    node_name = node.name
    assert node_name != self._my_hostname

    # Clean queue directory on added node
    result = rpc.RpcRunner.call_jobqueue_purge(node_name)
    msg = result.fail_msg
    if msg:
      logging.warning("Cannot cleanup queue directory on node %s: %s",
                      node_name, msg)

    if not node.master_candidate:
      # remove if existing, ignoring errors
      self._nodes.pop(node_name, None)
      # and skip the replication of the job ids
      return

    # Upload the whole queue excluding archived jobs
    files = [self._GetJobPath(job_id) for job_id in self._GetJobIDsUnlocked()]

    # Upload current serial file
    files.append(constants.JOB_QUEUE_SERIAL_FILE)

    for file_name in files:
      # Read file content
      content = utils.ReadFile(file_name)

      result = rpc.RpcRunner.call_jobqueue_update([node_name],
                                                  [node.primary_ip],
                                                  file_name, content)
      msg = result[node_name].fail_msg
      if msg:
        logging.error("Failed to upload file %s to node %s: %s",
                      file_name, node_name, msg)

    self._nodes[node_name] = node.primary_ip

  @utils.LockedMethod
  @_RequireOpenQueue
  def RemoveNode(self, node_name):
    """Callback called when removing nodes from the cluster.

    @type node_name: str
    @param node_name: the name of the node to remove

    """
    try:
      # The queue is removed by the "leave node" RPC call.
      del self._nodes[node_name]
    except KeyError:
      pass

  @staticmethod
  def _CheckRpcResult(result, nodes, failmsg):
    """Verifies the status of an RPC call.

    Since we aim to keep consistency should this node (the current
    master) fail, we will log errors if our rpc fail, and especially
    log the case when more than half of the nodes fails.

    @param result: the data as returned from the rpc call
    @type nodes: list
    @param nodes: the list of nodes we made the call to
    @type failmsg: str
    @param failmsg: the identifier to be used for logging

    """
    failed = []
    success = []

    for node in nodes:
      msg = result[node].fail_msg
      if msg:
        failed.append(node)
        logging.error("RPC call %s (%s) failed on node %s: %s",
                      result[node].call, failmsg, node, msg)
      else:
        success.append(node)

    # +1 for the master node
    if (len(success) + 1) < len(failed):
      # TODO: Handle failing nodes
      logging.error("More than half of the nodes failed")

  def _GetNodeIp(self):
    """Helper for returning the node name/ip list.

    @rtype: (list, list)
    @return: a tuple of two lists, the first one with the node
        names and the second one with the node addresses

    """
    name_list = self._nodes.keys()
    addr_list = [self._nodes[name] for name in name_list]
    return name_list, addr_list

  def _WriteAndReplicateFileUnlocked(self, file_name, data):
    """Writes a file locally and then replicates it to all nodes.

    This function will replace the contents of a file on the local
    node and then replicate it to all the other nodes we have.

    @type file_name: str
    @param file_name: the path of the file to be replicated
    @type data: str
    @param data: the new contents of the file

    """
    utils.WriteFile(file_name, data=data)

    names, addrs = self._GetNodeIp()
    result = rpc.RpcRunner.call_jobqueue_update(names, addrs, file_name, data)
    self._CheckRpcResult(result, self._nodes,
                         "Updating %s" % file_name)

  def _RenameFilesUnlocked(self, rename):
    """Renames a file locally and then replicate the change.

    This function will rename a file in the local queue directory
    and then replicate this rename to all the other nodes we have.

    @type rename: list of (old, new)
    @param rename: List containing tuples mapping old to new names

    """
    # Rename them locally
    for old, new in rename:
      utils.RenameFile(old, new, mkdir=True)

    # ... and on all nodes
    names, addrs = self._GetNodeIp()
    result = rpc.RpcRunner.call_jobqueue_rename(names, addrs, rename)
    self._CheckRpcResult(result, self._nodes, "Renaming files (%r)" % rename)

  @staticmethod
  def _FormatJobID(job_id):
    """Convert a job ID to string format.

    Currently this just does C{str(job_id)} after performing some
    checks, but if we want to change the job id format this will
    abstract this change.

    @type job_id: int or long
    @param job_id: the numeric job id
    @rtype: str
    @return: the formatted job id

    """
    if not isinstance(job_id, (int, long)):
      raise errors.ProgrammerError("Job ID '%s' not numeric" % job_id)
    if job_id < 0:
      raise errors.ProgrammerError("Job ID %s is negative" % job_id)

    return str(job_id)

  @classmethod
  def _GetArchiveDirectory(cls, job_id):
    """Returns the archive directory for a job.

    @type job_id: str
    @param job_id: Job identifier
    @rtype: str
    @return: Directory name

    """
    return str(int(job_id) / JOBS_PER_ARCHIVE_DIRECTORY)

  def _NewSerialsUnlocked(self, count):
    """Generates a new job identifier.

    Job identifiers are unique during the lifetime of a cluster.

    @type count: integer
    @param count: how many serials to return
    @rtype: str
    @return: a string representing the job identifier.

    """
    assert count > 0
    # New number
    serial = self._last_serial + count

    # Write to file
    self._WriteAndReplicateFileUnlocked(constants.JOB_QUEUE_SERIAL_FILE,
                                        "%s\n" % serial)

    result = [self._FormatJobID(v)
              for v in range(self._last_serial, serial + 1)]
    # Keep it only if we were able to write the file
    self._last_serial = serial

    return result

  @staticmethod
  def _GetJobPath(job_id):
    """Returns the job file for a given job id.

    @type job_id: str
    @param job_id: the job identifier
    @rtype: str
    @return: the path to the job file

    """
    return utils.PathJoin(constants.QUEUE_DIR, "job-%s" % job_id)

  @classmethod
  def _GetArchivedJobPath(cls, job_id):
    """Returns the archived job file for a give job id.

    @type job_id: str
    @param job_id: the job identifier
    @rtype: str
    @return: the path to the archived job file

    """
    return utils.PathJoin(constants.JOB_QUEUE_ARCHIVE_DIR,
                          cls._GetArchiveDirectory(job_id), "job-%s" % job_id)

  @classmethod
  def _ExtractJobID(cls, name):
    """Extract the job id from a filename.

    @type name: str
    @param name: the job filename
    @rtype: job id or None
    @return: the job id corresponding to the given filename,
        or None if the filename does not represent a valid
        job file

    """
    m = cls._RE_JOB_FILE.match(name)
    if m:
      return m.group(1)
    else:
      return None

  def _GetJobIDsUnlocked(self, archived=False):
    """Return all known job IDs.

    If the parameter archived is True, archived jobs IDs will be
    included. Currently this argument is unused.

    The method only looks at disk because it's a requirement that all
    jobs are present on disk (so in the _memcache we don't have any
    extra IDs).

    @rtype: list
    @return: the list of job IDs

    """
    # pylint: disable-msg=W0613
    jlist = [self._ExtractJobID(name) for name in self._ListJobFiles()]
    jlist = utils.NiceSort(jlist)
    return jlist

  def _ListJobFiles(self):
    """Returns the list of current job files.

    @rtype: list
    @return: the list of job file names

    """
    return [name for name in utils.ListVisibleFiles(constants.QUEUE_DIR)
            if self._RE_JOB_FILE.match(name)]

  def _LoadJobUnlocked(self, job_id):
    """Loads a job from the disk or memory.

    Given a job id, this will return the cached job object if
    existing, or try to load the job from the disk. If loading from
    disk, it will also add the job to the cache.

    @param job_id: the job id
    @rtype: L{_QueuedJob} or None
    @return: either None or the job object

    """
    job = self._memcache.get(job_id, None)
    if job:
      logging.debug("Found job %s in memcache", job_id)
      return job

    filepath = self._GetJobPath(job_id)
    logging.debug("Loading job from %s", filepath)
    try:
      raw_data = utils.ReadFile(filepath)
    except IOError, err:
      if err.errno in (errno.ENOENT, ):
        return None
      raise

    data = serializer.LoadJson(raw_data)

    try:
      job = _QueuedJob.Restore(self, data)
    except Exception, err: # pylint: disable-msg=W0703
      new_path = self._GetArchivedJobPath(job_id)
      if filepath == new_path:
        # job already archived (future case)
        logging.exception("Can't parse job %s", job_id)
      else:
        # non-archived case
        logging.exception("Can't parse job %s, will archive.", job_id)
        self._RenameFilesUnlocked([(filepath, new_path)])
      return None

    self._memcache[job_id] = job
    logging.debug("Added job %s to the cache", job_id)
    return job

  def _GetJobsUnlocked(self, job_ids):
    """Return a list of jobs based on their IDs.

    @type job_ids: list
    @param job_ids: either an empty list (meaning all jobs),
        or a list of job IDs
    @rtype: list
    @return: the list of job objects

    """
    if not job_ids:
      job_ids = self._GetJobIDsUnlocked()

    return [self._LoadJobUnlocked(job_id) for job_id in job_ids]

  @staticmethod
  def _IsQueueMarkedDrain():
    """Check if the queue is marked from drain.

    This currently uses the queue drain file, which makes it a
    per-node flag. In the future this can be moved to the config file.

    @rtype: boolean
    @return: True of the job queue is marked for draining

    """
    return os.path.exists(constants.JOB_QUEUE_DRAIN_FILE)

  @staticmethod
  def SetDrainFlag(drain_flag):
    """Sets the drain flag for the queue.

    This is similar to the function L{backend.JobQueueSetDrainFlag},
    and in the future we might merge them.

    @type drain_flag: boolean
    @param drain_flag: Whether to set or unset the drain flag

    """
    if drain_flag:
      utils.WriteFile(constants.JOB_QUEUE_DRAIN_FILE, data="", close=True)
    else:
      utils.RemoveFile(constants.JOB_QUEUE_DRAIN_FILE)
    return True

  @_RequireOpenQueue
  def _SubmitJobUnlocked(self, job_id, ops):
    """Create and store a new job.

    This enters the job into our job queue and also puts it on the new
    queue, in order for it to be picked up by the queue processors.

    @type job_id: job ID
    @param job_id: the job ID for the new job
    @type ops: list
    @param ops: The list of OpCodes that will become the new job.
    @rtype: job ID
    @return: the job ID of the newly created job
    @raise errors.JobQueueDrainError: if the job is marked for draining

    """
    if self._IsQueueMarkedDrain():
      raise errors.JobQueueDrainError("Job queue is drained, refusing job")

    # Check job queue size
    size = len(self._ListJobFiles())
    if size >= constants.JOB_QUEUE_SIZE_SOFT_LIMIT:
      # TODO: Autoarchive jobs. Make sure it's not done on every job
      # submission, though.
      #size = ...
      pass

    if size >= constants.JOB_QUEUE_SIZE_HARD_LIMIT:
      raise errors.JobQueueFull()

    job = _QueuedJob(self, job_id, ops)

    # Write to disk
    self.UpdateJobUnlocked(job)

    logging.debug("Adding new job %s to the cache", job_id)
    self._memcache[job_id] = job

    # Add to worker pool
    self._wpool.AddTask(job)

    return job.id

  @utils.LockedMethod
  @_RequireOpenQueue
  def SubmitJob(self, ops):
    """Create and store a new job.

    @see: L{_SubmitJobUnlocked}

    """
    job_id = self._NewSerialsUnlocked(1)[0]
    return self._SubmitJobUnlocked(job_id, ops)

  @utils.LockedMethod
  @_RequireOpenQueue
  def SubmitManyJobs(self, jobs):
    """Create and store multiple jobs.

    @see: L{_SubmitJobUnlocked}

    """
    results = []
    all_job_ids = self._NewSerialsUnlocked(len(jobs))