I agree with Matthieu, that's a really nice integration!
I particularly like having different partition schemes per stream. I
guess it would be easy (or at least possible) to implement some kind of
isolation where only a subset of nodes handles a specific stream, for
example (related to S4-91).
It looks really nice, I'm looking forward to trying it. I'll give more
feedback if I run into any issues. I guess the right JIRA for that
would be S4-110, right? (It's missing a description!)
Good job!
Daniel
On Fri Nov 30 16:37:11 2012, Matthieu Morel wrote:
Thanks Kishore, that's a very interesting contribution!
It's also very appropriate considering that S4 is completely decentralized and
that there is no driving/scheduling entity: the logic is within the nodes. So
it's nice to have a way to easily describe and define coordinated behaviors,
and to easily automate them.
About the partitioning, the key here as I understand it, is to have a number of
partitions higher than the number of nodes by default, possibly several times
higher. So a given node is assigned multiple partitions. (In contrast, until now
in S4, nb partitions <= nb nodes, including standby nodes).
In the canonical example that you provide, how do we proceed if we want to add
another s4 node? That's not clear to me, and it would help understand how
partitions are reassigned.
Thanks!
Matthieu
In S4 the number of partition is fixed for all streams and is dependent on
the number of nodes in the cluster. Adding new nodes to S4 cluster causes
the number of partitions to change. This results in lot of data movement.
For example if there are 4 nodes and you add another node then nearly all
keys will be remapped which result is huge data movement where as ideally
only 20% of the data should move.
By using Helix, every stream can be partitioned differently and
independent of the number of nodes. Helix distributes the partitions evenly
among the nodes. When new nodes are added, partitions can be migrated to
new nodes without changing the number of partitions and minimizes the data
movement.
In S4 handles failures by having stand by nodes that are idle most of the
time and become active when a node fails. Even though this works, its not
ideal in terms of efficient hardware usage since the stand by nodes are
idle most of the time. This also increases the fail over time since the PE
state has to be transfered to only one node.
Helix allows S4 to have Active and Standby nodes at a partition level so
that all nodes can be active but some partitions will be Active and some in
stand by mode. When a node fails, the partitions that were Active on that
node will be evenly distributed among the remaining nodes. This provides
automatic load balancing and also improves fail over time, since PE state
can be transfered to multiple nodes in parallel.
I have a prototype implementation here
https://github.com/kishoreg/incubator-s4
Instructions to build it and try it out are in the Readme.
More info on Helix can be found here, http://helix.incubator.apache.org/
Helix can provide lot of other functionalities like
1. Configure the topology according to use case. For example, co-locate
the partitions of different streams to allow efficient joins. Configure the
number of standby for each partition based on the head room available.
2. When new nodes are added, it can throttle the data movement
3. Comes with large set of admin tools like enable/disable node,
dynamically change the topology etc. Provides a rest interface to manage
the cluster.
4. Allows one to schedule custom tasks like snapshot the PE's in a
partition and restore from the snapshot.
Would like to get your feedback.
Thanks,
Kishore G
