1. A Python Petting Zoo
Python and ZooKeeper
Devon Jones
Senior Software Engineer
knewt.ly/pettingzoo-slides
2. Knewton is an education technology company with a goal of
bringing adaptive education to the masses. Knewton makes it
possible to break courses into tiny parts that are delivered to
each student as personalized, real-time recommendations.
Knewton recommends the best work for an individual learner by
calculating data on what we know about a student, similar
students, the learning objective, and the content itself at a given
point in time.
The Knewton platform today has tens of thousands of students,
will have over 600k students starting Sept. 2012, and will soon
have millions of students.
3. What is this about?
● What is ZooKeeper, how is it useful
● State of ZooKeeper on python
● The release of PettingZoo, Knewton's
ZooKeeper recipes for managing a
distributed machine learning cluster
4. What is ZooKeeper?
According to ZooKeeper's Apache Site:
ZooKeeper is a centralized service for maintaining configuration information,
naming, providing distributed synchronization, and providing group services. All
of these kinds of services are used in some form or another by distributed
applications. Each time they are implemented there is a lot of work that goes
into fixing the bugs and race conditions that are inevitable. Because of the
difficulty of implementing these kinds of services, applications initially usually
skimp on them, which make them brittle in the presence of change and difficult
to manage. Even when done correctly, different implementations of these
services lead to management complexity when the applications are deployed.
Right, but what is it?
5. What is ZooKeeper?
ZooKeeper is a distributed filesystem based on
the PAXOS algorithim with a few valuable
features.
● No single point of failure
● Strictly ordered, observable state
● Events
● Sequential and ephemeral primitives
● ACLs
7. What is ZooKeeper for?
ZooKeeper is a platform for creating protocols
for synchronization of distributed systems.
Uses include:
● Distributed configuration
● Queues
● Implementation of distributed concurrency
primitives such as locks, barriers, latches,
counters, etc.
In short, it's a system for managing shared
state between distributed systems.
9. Watches
● Can be set by any read operation
● Will fire an event to the client who set them
once and only once
● Can be set on nodes or on their data.
● Will always be sent to you in a fixed order
10. Sequential Nodes
● Appends a monotonically increasing number
to the end of the znode (file)
● Can be used directly for leader election
● Provides communication of server's view of
ordering
11. Ephemeral Nodes
● Only exist for the life of a connection
● If your connection does not respond to a
keepalive request, will disappear
● Used to ensure reliability against service
disruption for most recipes
● Used to trigger events, such as
reconfiguration if a service goes down that
published discovery configs
13. Recipes
As a community, we need well tested versions
of these recipes as well as other valuable
protocols built on ZooKeeper
14. State of ZooKeeper
● Very low level
● Coding for it is very complex
● Lots of edge cases
● ZooKeeper needs high level, well tested
libraries
● Very few complete, high level solutions exist
15. ZooKeeper Libraries
The first high level library with significant recipe
implementations has emerged from Netflix. It's
name is Curator.
Unfortunately for us, it's in Java, not Python.
16. Curator
https://github.com/Netfix/curator
● State
○ High level api
○ Non-Resilient Client
○ Documentation
○ Tests, Embeddable ZooKeeper for testing
● Recipes
○ Leader Latch, Leader Election
○ Multiple Locks and Semaphores
○ Multiple Queues
○ Barrier, Double Barrier
○ Shared Counter/Distributed Atomic Long
17. State of ZooKeeper on Python
● Current state is in a lot of flux
● Went from only low level bindings to a
number of incomplete bindings in first half of
2012
● So far nothing like Curator has emerged (but
it appears to be brewing)
18. One of the top ranked results for 'Python ZooKeeper'
19. Summary of Python ZooKeeper
bindings
● There are about 10 presently
● Many suffer from not handling known edge
cases in ZooKeeper
● Some suffer problems with resilient
connections
● The following is derived from the python
ZooKeeper binding census of Ben Bangert
20. Official Bindings
● State
○ Complete access to the ZooKeeper C bindings
○ Full of sharp edges
○ Not a resilient client
○ No recipes
○ Threads communication with ZooKeeper in a C
thread
○ Foundation for most other libraries
○ Very low level
24. State of ZooKeeper on Python:
Kind of a Mess
A project exists to merge some of the high level
bindings in an attempt to create a python
equivalent of Curator: https://github.
com/python-zk
Started by Ben Bangert to merge Kazoo & zc.
zk with an attempt to implement all Curator
recipes.
25. PettingZoo
https://github.com/Knewton/pettingzoo-python
● State
○ Relies on zc.zk
○ Documented, doc strings
○ Tests (mock ZooKeeper)
○ All recipes implemented in a Java version as well
● Recipes
○ Distributed Config
○ Distributed Bag
○ Leader Queue
○ Role Match
26. PettingZoo
● In heavy development
● Distributed Discovery, Distributed Bag are
well tested and used in production
● Leader Queue and Role Match are tested,
but undeployed
● PettingZoo will be ported to or merged with
the kazoo effort when it is ready
27. Our Problem
Need to be able to do stream processing of
observations of student interactions with course
material. This involves multiple models that
have interdependent parameters. This requires:
● Sharding along different axes dependent
upon the models
● Subscriptions between models for
parameters
● Dynamic reconfiguration of the environment
to deal with current load
28. Distributed Discovery
Allows services in a dynamic, distributed
environment to be able to be quickly alerted of
service address changes.
● Most service discovery recipes only contain
host:port, Distributed Discovery can share
arbitrary data as well (using yaml)
● Can handle load balancing through random
selection of config
● Handles rebalancing on pool change
29. How does this help us scale?
● Makes discovery of dependencies simple
● Adds to reliability of system by quickly
removing dead resources
● Makes dynamic reconfiguration simple as
additional resources become available
32. Distributed Bag
Recipe for a distributed bag (dbag) that allows
processes to share a collection. Any
participant can post or remove data, alerting all
others.
● Used as a part of Role Match
● Useful for any case where
processes need to share
configuration determined at
runtime
33. How does this help us scale?
● Can quickly alert processes as to who is
subscribing to them
● Reduces load by quickly yanking dead
subscriptions
● Provides event based subscriptions, making
implementation simpler
34. Distributed Bag
● Sequential items
Item
contain the actual data
Items
1Item
2Item ● Can be ephemeral
3 ● Clients set delete watch
on discrete items
<bag> ● Token is set to id of
highest item
● Clients set a child
Tokens
Token watch on the "Tokens"
3
node
● Can determine exact
adds and deletes with a
constant number of
messages per delta
36. Leader Queue
Recipe is similar to Leader Election, but makes
it easy to monitor your spare capacity.
● Used in Role Match
● As services are ready to do work, they
create an ephemeral, sequential node in the
queue.
● Any member always knows if either they are
in the queue or at the front
● Watch lets leader know when it is elected
37. How does this help us scale?
● Gives a convenient method of assigning
work
● Makes monitoring current excess capacity
easy
38. Leader Queue
● Candidates register with
sequential, ephemeral nodes
C_1
● Candidate sets delete watch
on predecessor
● Candidate is elected when it
is the smallest node
<queue> C_3 ● When elected, candidate
takes over its new role
● When ready, candidate
removes itself from the
queue
C_4
● Only one candidate needs to
call get_children upon any
node exiting
39. Leader Queue Usage Example
from pettingzoo.leader_queue import LeaderQueue, Candidate
from pettingzoo.utils import connect_to_zk
class SomeCandidate (Candidate):
def on_elected (self):
<do something sexy>
conn = connect_to_zk( 'localhost:2181' )
leaderq = LeaderQueue(conn)
leaderq.add_candidate(SomeCandidate())
40. Role Match
Allows systems to expose needed, long lived
jobs, and for services to take over those jobs
until all are filled.
● Dbag used to expose jobs
● Leader queue used to hold applicants
● Records which jobs are presently held with
ephemeral node
● Lets a new process take over if a worker
dies
● We use it for sharding/segmentation to
dynamically adjust the shards as needed
41. How does this help us scale?
● Core of our ability to dynamically adjust
shards
● Lets the controlling process adjust problem
spaces and have those tasks become
automatically filled
● Monitoring is easy to identify who is working
on what, when
42. Role Match
job
Distributed ● Leader monitors for
Bag
open jobs
● Job holder creates
an ephemeral
assignment
<match> applicant Leader Queue
● Assignment id
matches job id,
indicating that it is
Assgn
claimed
assignment
1
A_2
43. Future: Distributed Config
Next project is Distributed Config.
● Allows service config to be recorded and
changed with a yaml config
● Every process that connects creates a child
node of the appropriate service
● Any change in a child node's config
overrides the overall service config for that
process
● Any change of the parent or child fires a
watch to let the process know that it's config
has changed
45. Appendix: Official Bindings
● State
○ Complete access to the ZooKeeper C bindings
○ Full of sharp edges
○ Not a resilient client
○ No recipes
○ Threads communication with ZooKeeper in a C
thread
○ Foundation for most other libraries
○ Very low level
