openstack/deb-python-taskflow
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Merge "Add docs for jobs and jobboards"

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doc/source/index.rst
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arguments_and_results
patterns
engines
jobs
inputs_and_outputs
notifications
storage

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----
Jobs
----
Overview
========
Jobs and jobboards are a **novel** concept that taskflow provides to allow for
automatic ownership transfer of workflows between capable
owners (those owners usually then use :doc:`engines <engines>` to complete the
workflow). They provide the necessary semantics to be able to atomically
transfer a job from a producer to a consumer in a reliable and fault tolerant
manner. They are modeled off the concept used to post and acquire work in the
physical world (typically a job listing in a newspaper or online website
serves a similar role).
**TLDR:** It's similar to a queue, but consumers lock items on the queue when
claiming them, and only remove them from the queue when they're done with the
work. If the consumer fails, the lock is *automatically* released and the item
is back on the queue for further consumption.
Features
--------
- High availability
- Guarantees workflow forward progress by transfering partially completed work
or work that has not been started to entities which can either resume the
previously partially completed work or begin initial work to ensure that
the workflow as a whole progresses (where progressing implies transitioning
through the workflow :doc:`patterns <patterns>` and :doc:`atoms <atoms>`
and completing their associated state transitions).
- Atomic transfer and single ownership
- Ensures that only one workflow is managed (aka owned) by a single owner at
a time in an atomic manner (including when the workflow is transferred to
a owner that is resuming some other failed owners work). This avoids
contention and ensures a workflow is managed by one and only one entity at
a time.
- *Note:* this does not mean that the owner needs to run the
workflow itself but instead said owner could use an engine that runs the
work in a distributed manner to ensure that the workflow progresses.
- Separation of workflow construction and execution
- Jobs can be created with logbooks that contain a specification of the work
to be done by a entity (such as an API server). The job then can be
completed by a entity that is watching that jobboard (not neccasarily the
API server itself). This creates a disconnection between work
formation and work completion that is useful for scaling out horizontally.
- Asynchronous completion
- When for example a API server posts a job for completion to a
jobboard that API server can return a *tracking* identifier to the user
calling the API service. This *tracking* identifier can be used by the
user to poll for status (similar in concept to a shipping *tracking*
identifier created by fedex or UPS).
For more information, please see `wiki page`_ for more details.
Jobs
----
A job consists of a unique identifier, name, and a reference to a logbook
which contains the details of the work that has been or should be/will be
completed to finish the work that has been created for that job.
Jobboards
---------
A jobboard is responsible for managing the posting, ownership, and delivery
of jobs. It acts as the location where jobs can be posted, claimed and searched
for; typically by iteration or notification. Jobboards may be backed by
different *capable* implementations (each with potentially differing
configuration) but all jobboards implement the same interface and semantics so
that the backend usage is as transparent as possible. This allows deployers or
developers of a service that uses TaskFlow to select a jobboard implementation
that fits their setup (and there intended usage) best.
Using Jobboards
===============
All engines are mere classes that implement same interface, and of course it is
possible to import them and create their instances just like with any classes
in Python. But the easier (and recommended) way for creating jobboards is by
using the `fetch()` functionality. Using this function the typical creation of
a jobboard (and an example posting of a job) might look like:
.. code-block:: python
from taskflow.persistence import backends as persistence_backends
from taskflow.jobs import backends as job_backends
...
persistence = persistence_backends.fetch({
"connection': "mysql",
"user": ...,
"password": ...,
})
book = make_and_save_logbook(persistence)
board = job_backends.fetch('my-board', {
"board": "zookeeper",
}, persistence=persistence)
job = board.post("my-first-job", book)
...
Consumption of jobs is similarly achieved by creating a jobboard and using
the iteration functionality to find and claim jobs (and eventually consume
them). The typical usage of a joboard for consumption (and work completion)
might look like:
.. code-block:: python
import time
from taskflow import exceptions as exc
from taskflow.persistence import backends as persistence_backends
from taskflow.jobs import backends as job_backends
...
my_name = 'worker-1'
coffee_break_time = 60
persistence = persistence_backends.fetch({
"connection': "mysql",
"user": ...,
"password": ...,
})
board = job_backends.fetch('my-board', {
"board": "zookeeper",
}, persistence=persistence)
while True:
my_job = None
for job in board.iterjobs(only_unclaimed=True):
try:
board.claim(job, my_name)
except exc.UnclaimableJob:
pass
else:
my_job = job
break
if my_job is not None:
try:
perform_job(my_job)
except Exception:
LOG.exception("I failed performing job: %s", my_job)
else:
# I finished it, now cleanup.
board.consume(my_job)
persistence.destroy_logbook(my_job.book.uuid)
time.sleep(coffee_break_time)
...
.. automodule:: taskflow.jobs.backends
.. automodule:: taskflow.persistence
.. automodule:: taskflow.persistence.backends
Jobboard Configuration
======================
Known engine types are listed below.
Zookeeper
---------
**Board type**: ``'zookeeper'``
Uses `zookeeper`_ to provide the jobboard capabilities and semantics by using
a zookeeper directory, ephemeral, non-ephemeral nodes and watches.
Additional *kwarg* parameters:
* ``client``: a class that provides ``kazoo.client.KazooClient``-like
interface; it will be used for zookeeper interactions, sharing clients
between jobboard instances will likely provide better scalability and can
help avoid creating to many open connections to a set of zookeeper servers.
* ``persistence``: a class that provides a :doc:`persistence <persistence>`
backend interface; it will be used for loading jobs logbooks for usage at
runtime or for usage before a job is claimed for introspection.
Additional *configuration* parameters:
* ``path``: the root zookeeper path to store job information (*defaults* to
``/taskflow/jobs``)
* ``hosts``: the list of zookeeper hosts to connect to (*defaults* to
``localhost:2181``); only used if a client is not provided.
* ``timeout``: the timeout used when performing operations with zookeeper;
only used if a client is not provided.
* ``handler``: a class that provides ``kazoo.handlers``-like interface; it will
be used internally by `kazoo`_ to perform asynchronous operations, useful when
your program uses eventlet and you want to instruct kazoo to use an eventlet
compatible handler (such as the `eventlet handler`_).
Job Interface
=============
.. automodule:: taskflow.jobs.job
Jobboard Interface
==================
.. automodule:: taskflow.jobs.jobboard
.. _wiki page: https://wiki.openstack.org/wiki/TaskFlow/Paradigm_shifts#Workflow_ownership_transfer
.. _zookeeper: http://zookeeper.apache.org/
.. _kazoo: http://kazoo.readthedocs.org/
.. _eventlet handler: https://pypi.python.org/pypi/kazoo-eventlet-handler/