Source code for

Galaxy job handler, prepares, runs, tracks, and finishes Galaxy jobs

import datetime
import os
import time
from collections import defaultdict
from queue import (
from typing import (

from sqlalchemy.exc import OperationalError
from sqlalchemy.sql.expression import (

from galaxy import model
from galaxy.exceptions import ObjectNotFound
from import (
from import JobNotReadyException
from import get_jobs_to_check_at_startup
from galaxy.model.base import (
from galaxy.structured_app import MinimalManagerApp
from galaxy.util import unicodify
from galaxy.util.custom_logging import get_logger
from galaxy.util.monitors import Monitors
from galaxy.web_stack.handlers import HANDLER_ASSIGNMENT_METHODS

log = get_logger(__name__)

# States for running a job. These are NOT the same as data states
) = (
DEFAULT_JOB_RUNNER_FAILURE_MESSAGE = "Unable to run job due to a misconfiguration of the Galaxy job running system.  Please contact a site administrator."

[docs]class JobHandlerI:
[docs] def start(self): pass
[docs] def shutdown(self): pass
[docs]class JobHandler(JobHandlerI): """ Handle the preparation, running, tracking, and finishing of jobs """
[docs] def __init__(self, app): = app # The dispatcher launches the underlying job runners self.dispatcher = DefaultJobDispatcher(app) # Queues for starting and stopping jobs self.job_queue = JobHandlerQueue(app, self.dispatcher) self.job_stop_queue = JobHandlerStopQueue(app, self.dispatcher)
[docs] def start(self): self.dispatcher.start() self.job_queue.start() self.job_stop_queue.start()
[docs] def shutdown(self): self.job_queue.shutdown() self.job_stop_queue.shutdown()
[docs]class ItemGrabber: grab_model: Union[Type[model.Job], Type[model.WorkflowInvocation]]
[docs] def __init__( self, app, handler_assignment_method=None, max_grab=None, self_handler_tags=None, handler_tags=None, ): = app self.sa_session = app.model.context self.handler_assignment_method = handler_assignment_method self.self_handler_tags = self_handler_tags self.max_grab = max_grab self.handler_tags = handler_tags self._grab_query = None self._supports_returning =
[docs] def setup_query(self): if self.grab_model is model.Job: grab_condition = self.grab_model.state == self.grab_model.states.NEW elif self.grab_model is model.WorkflowInvocation: grab_condition = self.grab_model.state.in_((self.grab_model.states.NEW, self.grab_model.states.CANCELLING)) else: raise NotImplementedError(f"Grabbing {self.grab_model.__name__} not implemented") subq = ( select( .where( and_( self.grab_model.handler.in_(self.self_handler_tags), grab_condition, ) ) .order_by( ) if self.max_grab: subq = subq.limit(self.max_grab) if self.handler_assignment_method == HANDLER_ASSIGNMENT_METHODS.DB_SKIP_LOCKED: subq = subq.with_for_update(skip_locked=True) self._grab_query = ( self.grab_model.table.update() .where( .values( ) if self._supports_returning: self._grab_query = self._grab_query.returning( if self.handler_assignment_method == HANDLER_ASSIGNMENT_METHODS.DB_TRANSACTION_ISOLATION: self._grab_conn_opts["isolation_level"] = "SERIALIZABLE" "Handler job grabber initialized with '%s' assignment method for handler '%s', tag(s): %s", self.handler_assignment_method,, ", ".join(str(x) for x in self.handler_tags), )
[docs] @staticmethod def get_grabbable_handler_assignment_method(handler_assignment_methods): grabbable_methods = { HANDLER_ASSIGNMENT_METHODS.DB_TRANSACTION_ISOLATION, HANDLER_ASSIGNMENT_METHODS.DB_SKIP_LOCKED, } if handler_assignment_methods: try: return [m for m in handler_assignment_methods if m in grabbable_methods][0] except IndexError: return
[docs] def grab_unhandled_items(self): """ Attempts to assign unassigned jobs or invocaions to itself using DB serialization methods, if enabled. This simply sets `Job.handler` or `WorkflowInvocation.handler` to the current server name, which causes the job to be picked up by the appropriate handler. """ # an excellent discussion on PostgreSQL concurrency safety: # if self._grab_query is None: self.setup_query() with as conn: with conn.begin() as trans: try: proxy = conn.execute(self._grab_query) if self._supports_returning: rows = proxy.fetchall() if rows: log.debug( f"Grabbed {self.grab_model.__name__}(s): {', '.join(str(row[0]) for row in rows)}" ) else: trans.rollback() except OperationalError as e: # If this is a serialization failure on PostgreSQL, then e.orig is a psycopg2 TransactionRollbackError # and should have attribute `code`. Other engines should just report the message and move on. if int(getattr(e.orig, "pgcode", -1)) != 40001: log.debug( "Grabbing %s failed (serialization failures are ok): %s", self.grab_model.__name__, unicodify(e), ) trans.rollback()
[docs]class InvocationGrabber(ItemGrabber): grab_model = model.WorkflowInvocation
[docs]class JobGrabber(ItemGrabber): grab_model = model.Job
[docs]class StopSignalException(Exception): """Exception raised when queue returns a stop signal."""
[docs]class BaseJobHandlerQueue(Monitors): STOP_SIGNAL = object()
[docs] def __init__(self, app: MinimalManagerApp, dispatcher): """ Initializes the Queue, creates (unstarted) monitoring thread. """ = app self.dispatcher = dispatcher self.sa_session = app.model.context # scoped session registry self.track_jobs_in_database = # Keep track of the pid that started the job manager, only it has valid threads self.parent_pid = os.getpid() # This queue is not used if track_jobs_in_database is True. self.queue: Queue[Tuple[int, str]] = Queue()
[docs]class JobHandlerQueue(BaseJobHandlerQueue): """ Job Handler's Internal Queue, this is what actually implements waiting for jobs to be runnable and dispatching to a JobRunner. """
[docs] def __init__(self, app: MinimalManagerApp, dispatcher): super().__init__(app, dispatcher) # self.queue contains tuples: (job_id, tool_id) # Initialize structures for handling job limits self.__clear_job_count() # Contains job ids for jobs that are waiting (only use from monitor thread) self.waiting_jobs: List[int] = [] # Contains wrappers of jobs that are limited or ready (so they aren't created unnecessarily/multiple times) self.job_wrappers: Dict[int, JobWrapper] = {} name = "JobHandlerQueue.monitor_thread" self._init_monitor_thread(name, target=self.__monitor, config=app.config) self.job_grabber = None handler_assignment_method = JobGrabber.get_grabbable_handler_assignment_method( ) if handler_assignment_method: self.job_grabber = JobGrabber( app=app, handler_assignment_method=handler_assignment_method,,,, )
[docs] def start(self): """ Starts the JobHandler's thread after checking for any unhandled jobs. """ log.debug("Handler queue starting for jobs assigned to handler: %s", # Recover jobs at startup self.__check_jobs_at_startup() # Start the queue self.monitor_thread.start()"job handler queue started")
[docs] def job_wrapper(self, job, use_persisted_destination=False): return JobWrapper(job, self, use_persisted_destination=use_persisted_destination)
[docs] def job_pair_for_id(self, id): job = self.sa_session.query(model.Job).get(id) return job, self.job_wrapper(job, use_persisted_destination=True)
def __check_jobs_at_startup(self): """ Checks all jobs that are in the 'new', 'queued', 'running', or 'stopped' state in the database and requeues or cleans up as necessary. Only run as the job handler starts. In case the activation is enforced it will filter out the jobs of inactive users. """ with self.sa_session() as session: for job in get_jobs_to_check_at_startup(session, self.track_jobs_in_database, try: self._check_job_at_startup(job) except Exception: log.exception("Error while recovering job %s during application startup.", with transaction(session): session.commit() def _check_job_at_startup(self, job): if not, job.tool_version, exact=True): log.warning(f"({}) Tool '{job.tool_id}' removed from tool config, unable to recover job") self.job_wrapper(job).fail( "This tool was disabled before the job completed. Please contact your Galaxy administrator." ) elif job.job_runner_name is not None and job.job_runner_external_id is None: # This could happen during certain revisions of Galaxy where a runner URL was persisted before the job was dispatched to a runner. log.debug(f"({}) Job runner assigned but no external ID recorded, adding to the job handler queue") job.job_runner_name = None if self.track_jobs_in_database: job.set_state(model.Job.states.NEW) else: self.queue.put((, job.tool_id)) elif job.job_runner_name is not None and job.job_runner_external_id is not None and job.destination_id is None: # This is the first start after upgrading from URLs to destinations, convert the URL to a destination and persist job_wrapper = self.job_wrapper(job) job_destination = self.dispatcher.url_to_destination(job.job_runner_name) if is None: = "legacy_url" job_wrapper.set_job_destination(job_destination, job.job_runner_external_id) self.dispatcher.recover(job, job_wrapper)"({}) Converted job from a URL to a destination and recovered") elif job.job_runner_name is None: # Never (fully) dispatched log.debug( f"({}) No job runner assigned and job still in '{job.state}' state, adding to the job handler queue" ) if self.track_jobs_in_database: job.set_state(model.Job.states.NEW) else: self.queue.put((, job.tool_id)) else: # Already dispatched and running job_wrapper = self.__recover_job_wrapper(job) self.dispatcher.recover(job, job_wrapper) pass def __recover_job_wrapper(self, job): # Already dispatched and running job_wrapper = self.job_wrapper(job) # Use the persisted destination as its params may differ from # what's in the job config job_destination = JobDestination( id=job.destination_id, runner=job.job_runner_name, params=job.destination_params ) # resubmits are not persisted (it's a good thing) so they # should be added back to the in-memory destination on startup try: config_job_destination = job_destination.resubmit = config_job_destination.resubmit except KeyError: log.debug( "(%s) Recovered destination id (%s) does not exist in job config (but this may be normal in the case of a dynamically generated destination)",, job.destination_id, ) job_wrapper.job_runner_mapper.cached_job_destination = job_destination return job_wrapper def __monitor(self): """ Continually iterate the waiting jobs, checking is each is ready to run and dispatching if so. """ while self.monitor_running: try: # If jobs are locked, there's nothing to monitor and we skip # to the sleep. if not self.__monitor_step() except Exception: log.exception("Exception in monitor_step") # With sqlite backends we can run into locked databases occasionally # To avoid that the monitor step locks again we backoff a little longer. self._monitor_sleep(5) self._monitor_sleep( def __monitor_step(self): """ Called repeatedly by `monitor` to process waiting jobs. """ monitor_step_timer = "", "Job handler monitor step complete." ) if self.job_grabber is not None: self.job_grabber.grab_unhandled_items() try: self.__handle_waiting_jobs() except StopSignalException: pass finally: self.sa_session.remove() log.trace(monitor_step_timer.to_str()) def __handle_waiting_jobs(self): """ Gets any new jobs (either from the database or from its own queue), then iterates over all new and waiting jobs to check the state of the jobs each depends on. If the job has dependencies that have not finished, it goes to the waiting queue. If the job has dependencies with errors, it is marked as having errors and removed from the queue. If the job belongs to an inactive user it is ignored. Otherwise, the job is dispatched. """ check_database_connection(self.sa_session) # Pull all new jobs from the queue at once jobs_to_check = [] resubmit_jobs = [] if self.track_jobs_in_database: # Clear the session so we get fresh states for job and all datasets self.sa_session.expunge_all() # Fetch all new jobs hda_not_ready = ( self.sa_session.query( .enable_eagerloads(False) .join(model.JobToInputDatasetAssociation) .join(model.HistoryDatasetAssociation) .join(model.Dataset) .filter( and_( model.Job.state == model.Job.states.NEW, model.Dataset.state.in_(model.Dataset.non_ready_states) ) ) .subquery() ) ldda_not_ready = ( self.sa_session.query( .enable_eagerloads(False) .join(model.JobToInputLibraryDatasetAssociation) .join(model.LibraryDatasetDatasetAssociation) .join(model.Dataset) .filter( and_( model.Job.state == model.Job.states.NEW, model.Dataset.state.in_(model.Dataset.non_ready_states) ) ) .subquery() ) coalesce_exp = func.coalesce( model.Job.table.c.user_id, model.Job.table.c.session_id ) # accommodate jobs by anonymous users rank = func.rank().over(partition_by=coalesce_exp,"rank") job_filter_conditions = ( (model.Job.state == model.Job.states.NEW), (model.Job.handler ==,,, ) if job_filter_conditions = job_filter_conditions + ( or_((model.Job.user_id == null()), ( == true())), ) if == "sqlite": query_objects = (model.Job,) else: query_objects = (model.Job, rank) ready_query = ( self.sa_session.query(*query_objects) .enable_eagerloads(False) .outerjoin(model.User) .filter(and_(*job_filter_conditions)) .order_by( ) if == "sqlite": jobs_to_check = ready_query.all() else: ranked = ready_query.subquery() jobs_to_check = ( self.sa_session.query(model.Job) .join(ranked, == .filter(ranked.c.rank <= .all() ) # Filter jobs with invalid input states jobs_to_check = self.__filter_jobs_with_invalid_input_states(jobs_to_check) # Fetch all "resubmit" jobs resubmit_jobs = ( self.sa_session.query(model.Job) .enable_eagerloads(False) .filter( and_( (model.Job.state == model.Job.states.RESUBMITTED), (model.Job.handler ==, ) ) .order_by( .all() ) else: # Get job objects and append to watch queue for any which were # previously waiting for job_id in self.waiting_jobs: jobs_to_check.append(self.sa_session.query(model.Job).get(job_id)) try: while 1: message = self.queue.get_nowait() if message is self.STOP_SIGNAL: raise StopSignalException() # Unpack the message job_id, tool_id = message # Get the job object and append to watch queue jobs_to_check.append(self.sa_session.query(model.Job).get(job_id)) except Empty: pass # Ensure that we get new job counts on each iteration self.__clear_job_count() # Check resubmit jobs first so that limits of new jobs will still be enforced for job in resubmit_jobs: log.debug("(%s) Job was resubmitted and is being dispatched immediately", # Reassemble resubmit job destination from persisted value jw = self.__recover_job_wrapper(job) if jw.is_ready_for_resubmission(job): self.increase_running_job_count(job.user_id, self.dispatcher.put(jw) # Iterate over new and waiting jobs and look for any that are # ready to run new_waiting_jobs = [] for job in jobs_to_check: try: # Check the job's dependencies, requeue if they're not done. # Some of these states will only happen when using the in-memory job queue if job.copied_from_job_id: copied_from_job = self.sa_session.query(model.Job).get(job.copied_from_job_id) job.numeric_metrics = copied_from_job.numeric_metrics job.text_metrics = copied_from_job.text_metrics job.dependencies = copied_from_job.dependencies job.state = copied_from_job.state job.job_stderr = copied_from_job.job_stderr job.job_stdout = copied_from_job.job_stdout job.tool_stderr = copied_from_job.tool_stderr job.tool_stdout = copied_from_job.tool_stdout job.command_line = copied_from_job.command_line job.traceback = copied_from_job.traceback job.tool_version = copied_from_job.tool_version job.exit_code = copied_from_job.exit_code job.job_runner_name = copied_from_job.job_runner_name job.job_runner_external_id = copied_from_job.job_runner_external_id continue job_state = self.__check_job_state(job) if job_state == JOB_WAIT: new_waiting_jobs.append( elif job_state == JOB_INPUT_ERROR:"(%d) Job unable to run: one or more inputs in error state" % elif job_state == JOB_INPUT_DELETED:"(%d) Job unable to run: one or more inputs deleted" % elif job_state == JOB_READY: self.dispatcher.put(self.job_wrappers.pop("(%d) Job dispatched" % elif job_state == JOB_DELETED:"(%d) Job deleted by user while still queued" % elif job_state == JOB_ADMIN_DELETED:"(%d) Job deleted by admin while still queued" % elif job_state in (JOB_USER_OVER_QUOTA, JOB_USER_OVER_TOTAL_WALLTIME): if job_state == JOB_USER_OVER_QUOTA:"(%d) User (%s) is over quota: job paused" % (, job.user_id)) what = "your disk quota" else:"(%d) User (%s) is over total walltime limit: job paused" % (, job.user_id)) what = "your total job runtime" job.set_state(model.Job.states.PAUSED) for dataset_assoc in job.output_datasets + job.output_library_datasets: dataset_assoc.dataset.dataset.state = model.Dataset.states.PAUSED = f"Execution of this dataset's job is paused because you were over {what} at the time it was ready to run" self.sa_session.add(dataset_assoc.dataset.dataset) self.sa_session.add(job) elif job_state == JOB_ERROR: # A more informative message is shown wherever the job state is set to error pass else: log.error("(%d) Job in unknown state '%s'" % (, job_state)) new_waiting_jobs.append( except Exception: log.exception("failure running job %d", # Update the waiting list if not self.track_jobs_in_database: self.waiting_jobs = new_waiting_jobs # Remove cached wrappers for any jobs that are no longer being tracked for id in set(self.job_wrappers.keys()) - set(new_waiting_jobs): del self.job_wrappers[id] # Commit updated state with transaction(self.sa_session): self.sa_session.commit() def __filter_jobs_with_invalid_input_states(self, jobs): """ Takes list of jobs and filters out jobs whose input datasets are in invalid state and set these jobs and their dependent jobs to paused. """ job_ids_to_check = [ for j in jobs] queries = [] for job_to_input, input_association in [ (model.JobToInputDatasetAssociation, model.HistoryDatasetAssociation), (model.JobToInputLibraryDatasetAssociation, model.LibraryDatasetDatasetAssociation), ]: q = ( self.sa_session.query(, input_association.deleted, input_association._state,, model.Dataset.deleted, model.Dataset.purged, model.Dataset.state, ) .join(job_to_input.job) .join(input_association) .join(model.Dataset) .filter( .filter( or_( model.Dataset.deleted == true(), not_( or_( model.Dataset.state == model.Dataset.states.OK, model.Dataset.state == model.Dataset.states.DEFERRED, ) ), input_association.deleted == true(), input_association._state.in_( (input_association.states.FAILED_METADATA, input_association.states.SETTING_METADATA) ), ) ) .all() ) queries.extend(q) jobs_to_pause = defaultdict(list) jobs_to_fail = defaultdict(list) jobs_to_ignore = defaultdict(list) for job_id, hda_deleted, hda_state, hda_name, dataset_deleted, dataset_purged, dataset_state in queries: if hda_deleted or dataset_deleted: if dataset_purged: # If the dataset has been purged we can't resume the job by undeleting the input jobs_to_fail[job_id].append(f"Input dataset '{hda_name}' was deleted before the job started") else: jobs_to_pause[job_id].append(f"Input dataset '{hda_name}' was deleted before the job started") elif hda_state == model.HistoryDatasetAssociation.states.FAILED_METADATA: jobs_to_pause[job_id].append(f"Input dataset '{hda_name}' failed to properly set metadata") elif dataset_state == model.Dataset.states.PAUSED: jobs_to_pause[job_id].append(f"Input dataset '{hda_name}' was paused before the job started") elif dataset_state == model.Dataset.states.ERROR: jobs_to_pause[job_id].append(f"Input dataset '{hda_name}' is in error state") elif dataset_state != model.Dataset.states.OK: jobs_to_ignore[job_id].append(f"Input dataset '{hda_name}' is in {dataset_state} state") for job_id in sorted(jobs_to_pause): pause_message = ", ".join(jobs_to_pause[job_id]) pause_message = f"{pause_message}. To resume this job fix the input dataset(s)." job, job_wrapper = self.job_pair_for_id(job_id) try: job_wrapper.pause(job=job, message=pause_message) except Exception: log.exception("(%s) Caught exception while attempting to pause job.", job_id) for job_id in sorted(jobs_to_fail): fail_message = ", ".join(jobs_to_fail[job_id]) job, job_wrapper = self.job_pair_for_id(job_id) try: except Exception: log.exception("(%s) Caught exception while attempting to fail job.", job_id) jobs_to_ignore.update(jobs_to_pause) jobs_to_ignore.update(jobs_to_fail) return [j for j in jobs if not in jobs_to_ignore] def __check_job_state(self, job): """ Check if a job is ready to run by verifying that each of its input datasets is ready (specifically in the OK state). If any input dataset has an error, fail the job and return JOB_INPUT_ERROR. If any input dataset is deleted, fail the job and return JOB_INPUT_DELETED. If all input datasets are in OK state, return JOB_READY indicating that the job can be dispatched. Otherwise, return JOB_WAIT indicating that input datasets are still being prepared. """ if not self.track_jobs_in_database: in_memory_not_ready_state = self.__verify_in_memory_job_inputs(job) if in_memory_not_ready_state: return in_memory_not_ready_state # Else, if tracking in the database, job.state is guaranteed to be NEW and # the inputs are guaranteed to be OK. # Create the job wrapper so that the destination can be set job_id = job_wrapper = self.job_wrappers.get(job_id, None) if not job_wrapper: job_wrapper = self.job_wrapper(job) self.job_wrappers[job_id] = job_wrapper # If state == JOB_READY, assume job_destination also set - otherwise # in case of various error or cancelled states do not assume # destination has been set. state, job_destination = self.__verify_job_ready(job, job_wrapper) if state == JOB_READY: # PASS. increase usage by one job (if caching) so that multiple jobs aren't dispatched on this queue iteration self.increase_running_job_count(job.user_id, for job_to_input_dataset_association in job.input_datasets: # We record the input dataset version, now that we know the inputs are ready if job_to_input_dataset_association.dataset: job_to_input_dataset_association.dataset_version = job_to_input_dataset_association.dataset.version return state def __verify_job_ready(self, job, job_wrapper): """Compute job destination and verify job is ready at that destination by checking job limits and quota. If this method return a job state of JOB_READY - it MUST also return a job destination. """ job_destination = None try: assert ( job_wrapper.tool is not None ), "This tool was disabled before the job completed. Please contact your Galaxy administrator." # Cause the job_destination to be set and cached by the mapper job_destination = job_wrapper.job_destination except AssertionError as e: log.warning(f"({}) Tool '{job.tool_id}' removed from tool config, unable to run job") return JOB_ERROR, job_destination except JobNotReadyException as e: job_state = e.job_state or JOB_WAIT return job_state, None except Exception as e: failure_message = getattr(e, "failure_message", DEFAULT_JOB_RUNNER_FAILURE_MESSAGE) if failure_message == DEFAULT_JOB_RUNNER_FAILURE_MESSAGE: log.exception("Failed to generate job destination") else: log.debug(f"Intentionally failing job with message ({failure_message})") return JOB_ERROR, job_destination # job is ready to run, check limits # TODO: these checks should be refactored to minimize duplication and made more modular/pluggable state = self.__check_destination_jobs(job, job_wrapper) if state == JOB_READY: state = self.__check_user_jobs(job, job_wrapper) if state == JOB_READY and, job, job_destination): return JOB_USER_OVER_QUOTA, job_destination # Check total walltime limits if state == JOB_READY and "delta" in jobs_to_check = self.sa_session.query(model.Job).filter( model.Job.update_time >= - datetime.timedelta(["window"]), model.Job.state == "ok", ) if job.user_id: jobs_to_check = jobs_to_check.filter(model.Job.user_id == job.user_id) else: jobs_to_check = jobs_to_check.filter(model.Job.session_id == job.session_id) time_spent = datetime.timedelta(0) for job in jobs_to_check: # History is job.state_history started = None finished = None for history in sorted(job.state_history, key=lambda h: h.create_time): if history.state == "running": started = history.create_time elif history.state == "ok": finished = history.create_time if started is not None and finished is not None: time_spent += finished - started else: log.warning( "Unable to calculate time spent for job %s; started: %s, finished: %s",, started, finished, ) if time_spent >["delta"]: return JOB_USER_OVER_TOTAL_WALLTIME, job_destination return state, job_destination def __verify_in_memory_job_inputs(self, job): """Perform the same checks that happen via SQL for in-memory managed jobs. """ if job.state == model.Job.states.DELETED: return JOB_DELETED elif job.state == model.Job.states.ERROR: return JOB_ADMIN_DELETED for dataset_assoc in job.input_datasets + job.input_library_datasets: idata = dataset_assoc.dataset if not idata: continue # don't run jobs for which the input dataset was deleted if idata.deleted: self.job_wrappers.pop(, self.job_wrapper(job)).fail( f"input data {idata.hid} (file: {idata.get_file_name()}) was deleted before the job started" ) return JOB_INPUT_DELETED # an error in the input data causes us to bail immediately elif idata.state == idata.states.ERROR: self.job_wrappers.pop(, self.job_wrapper(job)).fail(f"input data {idata.hid} is in error state") return JOB_INPUT_ERROR elif idata.state == idata.states.FAILED_METADATA: self.job_wrappers.pop(, self.job_wrapper(job)).fail( f"input data {idata.hid} failed to properly set metadata" ) return JOB_INPUT_ERROR elif idata.state != idata.states.OK and not ( idata.state == idata.states.SETTING_METADATA and job.tool_id is not None and job.tool_id == ): # need to requeue return JOB_WAIT # All inputs ready to go. return None def __clear_job_count(self): self.user_job_count = None self.user_job_count_per_destination = None self.total_job_count_per_destination = None
[docs] def get_user_job_count(self, user_id): self.__cache_user_job_count() # This could have been incremented by a previous job dispatched on this iteration, even if we're not caching rval = self.user_job_count.get(user_id, 0) if not result = self.sa_session.execute( select(func.count( and_( model.Job.table.c.state.in_( (model.Job.states.QUEUED, model.Job.states.RUNNING, model.Job.states.RESUBMITTED) ), (model.Job.table.c.user_id == user_id), ) ) ) for row in result: # there should only be one row rval += row[0] return rval
def __cache_user_job_count(self): # Cache the job count if necessary if self.user_job_count is None and self.user_job_count = {} query = self.sa_session.execute( select(model.Job.table.c.user_id, func.count(model.Job.table.c.user_id)) .where( and_( model.Job.table.c.state.in_( (model.Job.states.QUEUED, model.Job.states.RUNNING, model.Job.states.RESUBMITTED) ), (model.Job.table.c.user_id != null()), ) ) .group_by(model.Job.table.c.user_id) ) for row in query: self.user_job_count[row[0]] = row[1] elif self.user_job_count is None: self.user_job_count = {}
[docs] def get_user_job_count_per_destination(self, user_id): self.__cache_user_job_count_per_destination() cached = self.user_job_count_per_destination.get(user_id, {}) if rval = cached else: # The cached count is still used even when we're not caching, it is # incremented when a job is run by this handler to ensure that # multiple jobs can't get past the limits in one iteration of the # queue. rval = {} rval.update(cached) result = self.sa_session.execute( select( model.Job.table.c.destination_id, func.count(model.Job.table.c.destination_id).label("job_count") ) .where( and_( model.Job.table.c.state.in_((model.Job.states.QUEUED, model.Job.states.RUNNING)), (model.Job.table.c.user_id == user_id), ) ) .group_by(model.Job.table.c.destination_id) ) for row in result.mappings(): # Add the count from the database to the cached count rval[row["destination_id"]] = rval.get(row["destination_id"], 0) + row["job_count"] return rval
def __cache_user_job_count_per_destination(self): # Cache the job count if necessary if self.user_job_count_per_destination is None and self.user_job_count_per_destination = {} result = self.sa_session.execute( select( model.Job.table.c.user_id, model.Job.table.c.destination_id, func.count(model.Job.table.c.user_id).label("job_count"), ) .where(and_(model.Job.table.c.state.in_((model.Job.states.QUEUED, model.Job.states.RUNNING)))) .group_by(model.Job.table.c.user_id, model.Job.table.c.destination_id) ) for row in result.mappings(): if row["user_id"] not in self.user_job_count_per_destination: self.user_job_count_per_destination[row["user_id"]] = {} self.user_job_count_per_destination[row["user_id"]][row["destination_id"]] = row["job_count"] elif self.user_job_count_per_destination is None: self.user_job_count_per_destination = {}
[docs] def increase_running_job_count(self, user_id, destination_id): if ( or or ): if self.user_job_count is None: self.user_job_count = {} if self.user_job_count_per_destination is None: self.user_job_count_per_destination = {} self.user_job_count[user_id] = self.user_job_count.get(user_id, 0) + 1 if user_id not in self.user_job_count_per_destination: self.user_job_count_per_destination[user_id] = {} self.user_job_count_per_destination[user_id][destination_id] = ( self.user_job_count_per_destination[user_id].get(destination_id, 0) + 1 ) if if self.total_job_count_per_destination is None: self.total_job_count_per_destination = {} self.total_job_count_per_destination[destination_id] = ( self.total_job_count_per_destination.get(destination_id, 0) + 1 )
def __check_user_jobs(self, job, job_wrapper): # TODO: Update output datasets' _state = LIMITED or some such new # state, so the UI can reflect what jobs are waiting due to concurrency # limits if job.user: # Check the hard limit first if count = self.get_user_job_count(job.user_id) # Check the user's number of dispatched jobs against the overall limit if count >= return JOB_WAIT # If we pass the hard limit, also check the per-destination count id = count_per_id = self.get_user_job_count_per_destination(job.user_id) if id in count = count_per_id.get(id, 0) # Check the user's number of dispatched jobs in the assigned destination id against the limit for that id if count >=[id]: return JOB_WAIT # If we pass the destination limit (if there is one), also check limits on any tags (if any) if job_wrapper.job_destination.tags: for tag in job_wrapper.job_destination.tags: # Check each tag for this job's destination if tag in # Only if there's a limit defined for this tag count = 0 for id in [ for d in]: # Add up the aggregate job total for this tag count += count_per_id.get(id, 0) if count >=[tag]: return JOB_WAIT elif job.galaxy_session: # Anonymous users only get the hard limit if count = ( self.sa_session.query(model.Job) .enable_eagerloads(False) .filter( and_( model.Job.session_id ==, or_( model.Job.state == model.Job.states.RUNNING, model.Job.state == model.Job.states.QUEUED ), ) ) .count() ) if count >= return JOB_WAIT else: log.warning( f"Job {} is not associated with a user or session so job concurrency limit cannot be checked." ) return JOB_READY def __cache_total_job_count_per_destination(self): # Cache the job count if necessary if self.total_job_count_per_destination is None: self.total_job_count_per_destination = {} result = self.sa_session.execute( select( model.Job.table.c.destination_id, func.count(model.Job.table.c.destination_id).label("job_count") ) .where(and_(model.Job.table.c.state.in_((model.Job.states.QUEUED, model.Job.states.RUNNING)))) .group_by(model.Job.table.c.destination_id) ) for row in result.mappings(): self.total_job_count_per_destination[row["destination_id"]] = row["job_count"]
[docs] def get_total_job_count_per_destination(self): self.__cache_total_job_count_per_destination() # Always use caching (at worst a job will have to wait one iteration, # and this would be more fair anyway as it ensures FIFO scheduling, # insofar as FIFO would be fair...) return self.total_job_count_per_destination
def __check_destination_jobs(self, job, job_wrapper): if id = count_per_id = self.get_total_job_count_per_destination() if id in count = count_per_id.get(id, 0) # Check the number of dispatched jobs in the assigned destination id against the limit for that id if count >=[id]: return JOB_WAIT # If we pass the destination limit (if there is one), also check limits on any tags (if any) if job_wrapper.job_destination.tags: for tag in job_wrapper.job_destination.tags: # Check each tag for this job's destination if tag in # Only if there's a limit defined for this tag count = 0 for id in [ for d in]: # Add up the aggregate job total for this tag count += count_per_id.get(id, 0) if count >=[tag]: return JOB_WAIT return JOB_READY
[docs] def put(self, job_id, tool_id): """Add a job to the queue (by job identifier)""" if not self.track_jobs_in_database: self.queue.put((job_id, tool_id)) self.sleeper.wake()
[docs] def shutdown(self): """Attempts to gracefully shut down the worker thread""" if self.parent_pid != os.getpid(): # We're not the real job queue, do nothing return else:"sending stop signal to worker thread") self.stop_monitoring() if not self.track_jobs_in_database: self.queue.put(self.STOP_SIGNAL) # A message could still be received while shutting down, should be ok since they will be picked up on next startup. self.sleeper.wake() self.shutdown_monitor()"job handler queue stopped") self.dispatcher.shutdown()
[docs]class JobHandlerStopQueue(BaseJobHandlerQueue): """ A queue for jobs which need to be terminated prematurely. """
[docs] def __init__(self, app: MinimalManagerApp, dispatcher): super().__init__(app, dispatcher) # self.queue contains tuples: (job_id, error message) name = "JobHandlerStopQueue.monitor_thread" self._init_monitor_thread(name, target=self.__monitor, config=app.config)
[docs] def start(self): # Start the queue self.monitor_thread.start()"job handler stop queue started")
def __monitor(self): """ Continually iterate and stop appropriate jobs. """ # HACK: Delay until after forking, we need a way to do post fork notification!!! time.sleep(10) while self.monitor_running: try: self.__monitor_step() except Exception: log.exception("Exception in monitor_step") # Sleep self._monitor_sleep(1) def __delete(self, job, error_msg, session): final_state = job.states.DELETED if error_msg is not None: final_state = job.states.ERROR = error_msg job.set_final_state(final_state, session.add(job) session.flush() def __stop(self, job, session): job.set_state(job.states.STOPPED) session.add(job) session.flush() def __monitor_step(self): """ Called repeatedly by `monitor` to stop jobs. """ # Pull all new jobs from the queue at once jobs_to_check = [] with self.sa_session() as session, session.begin(): self._add_newly_deleted_jobs(session, jobs_to_check) try: self._pull_from_queue(session, jobs_to_check) except StopSignalException: return self._check_jobs(session, jobs_to_check)
[docs] def put(self, job_id, error_msg=None): if not self.track_jobs_in_database: self.queue.put((job_id, error_msg))
[docs] def shutdown(self): """Attempts to gracefully shut down the worker thread""" if self.parent_pid != os.getpid(): # We're not the real job queue, do nothing return else:"sending stop signal to worker thread") self.stop_monitoring() if not self.track_jobs_in_database: self.queue.put(self.STOP_SIGNAL) self.shutdown_monitor()"job handler stop queue stopped")
def _add_newly_deleted_jobs(self, session, jobs_to_check): if self.track_jobs_in_database: newly_deleted_jobs = self._get_new_jobs(session) for job in newly_deleted_jobs: # job.stderr is always a string (job.job_stderr + job.tool_stderr, possibly `''`), # while any `not None` message returned in self.queue.get_nowait() is interpreted # as an error, so here we use None if job.stderr is false-y jobs_to_check.append((job, job.stderr or None)) def _get_new_jobs(self, session): states = (model.Job.states.DELETING, model.Job.states.STOPPING) stmt = select(model.Job).filter( model.Job.state.in_(states) & (model.Job.handler == ) return session.scalars(stmt).all() def _pull_from_queue(self, session, jobs_to_check): # Pull jobs from the queue (in the case of Administrative stopped jobs) try: while 1: message = self.queue.get_nowait() if message is self.STOP_SIGNAL: raise StopSignalException() job_id, error_msg = message job = session.get(model.Job, job_id) jobs_to_check.append((job, error_msg)) except Empty: pass def _check_jobs(self, session, jobs_to_check): for job, error_msg in jobs_to_check: if ( job.state not in ( job.states.DELETING, job.states.DELETED, job.states.STOPPING, job.states.STOPPED, ) and job.finished ): # terminated before it got here log.debug("Job %s already finished, not deleting or stopping", continue if job.state == job.states.DELETING: self.__delete(job, error_msg, session) elif job.state == job.states.STOPPING: self.__stop(job, session) if job.job_runner_name is not None: # tell the dispatcher to stop the job job_wrapper = JobWrapper(job, self, use_persisted_destination=True) self.dispatcher.stop(job, job_wrapper)
[docs]class DefaultJobDispatcher:
[docs] def __init__(self, app: MinimalManagerApp): = app self.job_runners = # Once plugins are loaded, all job destinations that were created from # URLs can have their URL params converted to the destination's param # dict by the plugin. log.debug(f"Loaded job runners plugins: {':'.join(self.job_runners.keys())}")
[docs] def start(self): for runner in self.job_runners.values(): runner.start()
[docs] def url_to_destination(self, url): """This is used by the runner mapper (a.k.a. dynamic runner) and recovery methods to have runners convert URLs to destinations. New-style runner plugin IDs must match the URL's scheme for this to work. """ runner_name = url.split(":", 1)[0] try: return self.job_runners[runner_name].url_to_destination(url) except Exception: log.exception( "Unable to convert legacy job runner URL '%s' to job destination, destination will be the '%s' runner with no params", url, runner_name, ) return JobDestination(runner=runner_name)
[docs] def get_job_runner(self, job_wrapper, get_task_runner=False): runner_name = job_wrapper.job_destination.runner try: runner = self.job_runners[runner_name] except KeyError: log.error(f"({job_wrapper.job_id}) Invalid job runner: {runner_name}") return None if get_task_runner and job_wrapper.can_split() and runner.runner_name != "PulsarJobRunner": return self.job_runners["tasks"] return runner
[docs] def put(self, job_wrapper): runner = self.get_job_runner(job_wrapper, get_task_runner=True) if runner is None: # Something went wrong, we've already failed the job wrapper return if isinstance(job_wrapper, TaskWrapper): # DBTODO Refactor log.debug(f"({job_wrapper.job_id}) Dispatching task {job_wrapper.task_id} to task runner") else: log.debug(f"({job_wrapper.job_id}) Dispatching to {job_wrapper.job_destination.runner} runner") runner.put(job_wrapper)
[docs] def stop(self, job, job_wrapper): """ Stop the given job. The input variable job may be either a Job or a Task. """ # The Job and Task classes have been modified so that their accessors # will return the appropriate value. # Note that Jobs and Tasks have runner_names, which are distinct from # the job_runner_name and task_runner_name. # The runner name is not set until the job has started. # If we're stopping a task, then the runner_name may be # None, in which case it hasn't been scheduled. if and job.tool_id == "__DATA_FETCH__": from galaxy.celery import celery_app celery_app.control.revoke(job.job_runner_external_id) if (job_runner_name := job.get_job_runner_name()) is not None: runner_name = job_runner_name.split(":", 1)[0] log.debug(f"Stopping job {job_wrapper.get_id_tag()} in {runner_name} runner") try: self.job_runners[runner_name].stop_job(job_wrapper) except KeyError: log.error(f"stop(): ({job_wrapper.get_id_tag()}) Invalid job runner: {runner_name}")
# Job and output dataset states have already been updated, so nothing is done here.
[docs] def recover(self, job, job_wrapper): runner_name = (job.job_runner_name.split(":", 1))[0] log.debug("recovering job %d in %s runner" % (, runner_name)) runner = self.get_job_runner(job_wrapper) try: runner.recover(job, job_wrapper) except ObjectNotFound: msg = "Could not recover job working directory after Galaxy restart" log.exception(f"recover(): ({job_wrapper.job_id}) {msg}")
[docs] def shutdown(self): failures = [] for name, runner in self.job_runners.items(): try: runner.shutdown() except Exception: failures.append(name) log.exception("Failed to shutdown runner %s", name) if failures: raise Exception(f"Failed to shutdown runners: {', '.join(failures)}")