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From Kanak Biscuitwala <kana...@hotmail.com>
Subject RE: Add performant IPC (Helix actors)
Date Thu, 21 Aug 2014 21:30:50 GMT
Yes, that would probably be best. I think what Greg has is a reasonable v1 for helix-ipc, and
(feel free to disagree with me) should be flexible enough as a base for most future things
we want to build, including multi-ZK support.
Kanak

Date: Thu, 21 Aug 2014 14:07:35 -0700
Subject: Re: Add performant IPC (Helix actors)
From: g.kishore@gmail.com
To: user@helix.apache.org
CC: dev@helix.apache.org

Should we move the ZK cross data center to a separate thread. This is an interesting problem
and probably needs more detailed discussions.

What do you guys think.



On Wed, Aug 20, 2014 at 7:44 PM, Kanak Biscuitwala <kanak.b@hotmail.com> wrote:




Hey Vlad,
In theory, we should be able to plug in a resolver that can resolve ZKs in other datacenters.
We already resolve different clusters within the same ZK. Here is the resolver interface:

https://github.com/brandtg/helix-actors/blob/master/helix-ipc/src/main/java/org/apache/helix/resolver/HelixResolver.java

Right now the ZK implementation of the resolver can return a different Helix manager for different
clusters, and perhaps it can be adapted to also accept a different ZK address from a different
DC. Then we can connect to ZK observers. However, the message scope probably needs an additional
resolver-specific metadata field or something that we can use to store the ZK observer addresses
(and therefore a corresponding field in a message).

Regarding ZK vs DNS, push updates via watchers is an advantage as you pointed out. Also since
Helix persists state on ZK, you have access to the entire cluster metadata in the context
of your requests. This can certainly be implemented in a DNS-like scheme, though. Perhaps
others can chime in on the tradeoffs here.

Kanak

From: brandt.greg@gmail.com
Date: Wed, 20 Aug 2014 18:16:55 -0700
Subject: Re: Add performant IPC (Helix actors)

To: user@helix.apache.org
CC: dev@helix.apache.org

Hey Vlad,

Correct, ZooKeeper would still be used for the address resolution component.
Cross-datacenter hasn't really been thought of yet, but you do make a good point in that we
should address this early because it usually seems to be an afterthought. However, we are
planning to allow cross-cluster messaging within the same ZooKeeper.



Something that might be interesting to do in the cross-datacenter use case is to replicate
each datacenter's ZooKeeper logs to each other datacenter in order to maintain a read-only
view of that ZooKeeper cluster. One could then resolve addresses with only connections to
local ZooKeeper(s), though the replication delay would have to be accounted for during state
transitions.



I've got a small project that does generic log change capture, and intend on doing ZooKeeper
log replication next, actually - have MySQL binary log and HDFS namenode edit logs now (https://github.com/brandtg/switchboard).
Just an idea.



-Greg

On Wed, Aug 20, 2014 at 6:00 PM, vlad.gm@gmail.com <vlad.gm@gmail.com> wrote:




Hi Greg,
Within Turn, a few of us were looking at Helix as a possible solution for service discovery.
It seems that the new system would keep the address resolution of the old messaging system
but replace ZooKeeper with a direct connection for high throughput. Incidentally, we have
a similar system, so we are more interested in the addressing part.



One thing that came up within our discussion was the possibility of accessing services in
other datacenters. Are there plans to offer inter-datacenter discovery capabilities? Would
that be based on ZK-observers or some other import mechanism (someone would need to connect
to the remote ZK, preferably not the client).



Also, especially in the across-datacenter case, there are clear parallels to using DNS for
the service discovery (I think Netflix published a blog post where they detailed this as an
option). What would we gain and lose by using ZK as the building block as opposed to DNS?
One thing that comes to mind is that ZK-based service discovery in Helix can be configured
as a push-from-ZK or a poll-by-client service, while DNS entries timeout and must always be
polled again.




Regards,Vlad

On Wed, Aug 20, 2014 at 5:46 PM, Greg Brandt <brandt.greg@gmail.com> wrote:




Hey Henry,
Initially, I thought the same thing. But after evaluating Akka Actors, I think they're a fundamentally
different approach to developing distributed systems as opposed to simply a messaging layer
implementation. Let me explain...






The primary difference between Akka Actors and Helix is that the former prefers loose, decentralized
control, whereas the latter prefers strong, centralized control. Akka applications are expected
to manage state by themselves, whereas in Helix, that responsibility is delegated to the controller.
And the actual user Akka Actor implementations are analogous to Helix Participant implementations.






So with that perspective, it would be a bit of a kludge to leverage Akka Actors for simple
cluster-scope-addressable message passing. Actually, Helix already provides this messaging
feature, but it is done via ZooKeeper which is dangerous and less-than-performant for a high
volume of messages.






The right thing to do seems to be to provide a set of better transport implemenations (e.g.
Netty, ActiveMQ, Kafka, etc.) for the cluster-scope-addressable messaging system, and better
preserve the fundamental concepts in Helix.






Let me know what you think.
-Greg



On Wed, Aug 20, 2014 at 9:55 AM, Henry Saputra <henry.saputra@gmail.com> wrote:


This seems fitting for Akka actor system [1]. Maybe we could just use

it as base?





- Henry



[1] http://akka.io



On Mon, Jul 21, 2014 at 9:47 AM, Greg Brandt <brandt.greg@gmail.com> wrote:

> We talked about this in a little bit greater detail, and it's seeming like

> there are three basic components that we want:

>

> 1. Transport - physically moving messages

> 2. Resolution - map cluster scope to set of machines

> 3. Management - message state, errors, retries, etc.

>

> The transport interface should be generic enough to allow many

> implementations (e.g. Netty, Kafka, etc.) It may be valuable to do multiple

> implementations if one underlying system supports desired message delivery

> guarantees better than another. For example, Kafka would be more amenable

> to at-least-once delivery, whereas something like Netty, with much less

> overhead than Kafka, would be better for at-most-once delivery.

>

> The goal here I think is to provide something that's most similar to Akka

> Actors, with the following guarantees:

>

> 1. at-most-once delivery

> 2. message ordering per sender-receiver pair

>

> A light-weight messaging primitive with those guarantees would allow

> implementation of many interesting things like Kishore mentions. Netty

> seems most suited to this task (it is the underlying transport for Akka as

> well). The reason to avoid Akka I think is that it imposes too much of its

> own philosophy on the user, and is really bloated. A Netty-based primitive

> could be provided out-of-the-box, and the interfaces it implements should

> be easy enough for users to implement on their own. It would be relatively

> trivial to add a Kafka-based implementation out-of-the-box as well.

>

> (Have a bit of a prototype here:

> https://github.com/brandtg/helix-actors/blob/master/helix-actors/src/main/java/org/apache/helix/actor/netty/NettyHelixActor.java







> )

>

> The transport mechanism should be agnostic to anything going on in the

> cluster: the resolution module is totally separate, and maps cluster scope

> to sets of nodes. For example, one could send a message to the entire

> cluster, specific partitions of a resource, or even from one cluster to

> another (via composing resolution modules or something).

>

> Then there would be a management component, composed with the other two

> components, which manages user callbacks associated with varying cluster

> scopes, tracks messages based on ID in order to perform request / response

> or feedback-loop kinds of things, manages errors / timeouts / retries, etc.

>

> -Greg

>

>

>

> On Sat, Jul 12, 2014 at 11:27 AM, kishore g <g.kishore@gmail.com> wrote:

>

>> Hi Vlad,

>>

>> Yes the idea is to have a pluggable architecture where Helix provides the

>> messaging channel without serializing/deserializing the data. In the end, I

>> envision having most of the building blocks needed to build a distributed

>> system. One should be able to build a datastore/search/olap/pu sub/stream

>> processing systems easily on top of Helix.

>>

>> I am curious to see what kind of tuning you guys did to handle 1.5 QPS. Our

>> goal is to have 1M QPS between the two servers. In order to achieve this we

>> might need pipelining/batching along with ordering guarantee's. This is non

>> trivial and error prone, I see a huge value in providing this feature. Most

>> systems have built some form replication schemes on their own. There are

>> two parts in the replication, one is the high through put message exchange

>> and the other is the scheme that is synchronous replication/async

>> replication/chained replication/consensus etc. The first part is the common

>> part that is needed across all the replication scheme.

>>

>> Of course getting this right is not easy and design is tricky but I feel

>> its worth a try.

>>

>> This is the high level flow I had discussed with Greg.

>>

>> Each server can host P partitions and is listening at one port. Based on

>> how many execution threads are needed, we can create C channels. Every

>> partition maps to a specific channel. On each channel we can guarantee

>> message ordering. We simply provide a callback to handle each message and

>> pass the received bytes without deserializing. Its up to the callback to

>> either process it synchronously or asynchronously.

>>

>> There are more details that its difficult to go over in the email. We

>> should probably write up the design and then deep dive on the details.

>>

>> thanks,

>> Kishore G

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>> On Sat, Jul 12, 2014 at 8:08 AM, vlad.gm@gmail.com <vlad.gm@gmail.com>

>> wrote:

>>

>> > I agree that having a messaging scheme that is not ZooKeeper-reliant

>> would

>> > help in building some synchronization protocols between clients and

>> > replicas. I am thinking of cases such as writing inside Kafka to

>> replicated

>> > partitions our our own application,a replicated Key/Value store.

>> >

>> > For me, service discovery bridges the gap between an application wanting

>> > to address a service (in Helix's case more particularly, a

>> service/resource

>> > name/partition tuple) and finding out a list of hostnames that can

>> receive

>> > that request. After that, whether the application wants to use Helix

>> itself

>> > or another messaging stack is an open problem, perhaps a clear separation

>> > of the discovery/messaging layers would allow for quickly swapping

>> > different pieces here.

>> >

>> > The interesting part (in my view) in providing fast messaging as part of

>> > Helix is the ability to use the service topology information that Helix

>> > hosts (number of replicas and their placement) together with the

>> messaging

>> > layer as sufficient components for realizing a consensus algorithm

>> between

>> > replicas, that is providing, on top of the regular service discovery

>> > function of writing to one instance of a service, the function of writing

>> > with consensus verification to all replicas of a service.

>> >

>> > In terms of capabilities, looking at Kafka and KV/Store as use cases,

>> this

>> > would mean running a whole protocol between the replicas of the service

>> to

>> > achieve a certain synchronization outcome (be it Paxos, 2 Phase Commit or

>> > Chain Replication - Paxos would probably not be needed since Helix

>> already

>> > provides a resilient master for the partition, so there is a clear

>> > hierarchy). Kafka suggests even more cases if we take the interaction

>> > between client and service into account, namely specifying the call to

>> > return after the master gets the data or after consensus between master

>> and

>> > replicas have been achieved, or sending data asynchronously (the

>> > combination of the producer.type and request.required.acks parameters of

>> > the producer).

>> >

>> > The only reason for which I would like to see a pluggable architecture is

>> > that in high volume applications the messaging stack requires a lot of

>> > tuning. As I said at the meet-up, in our company we deal with about 1.5M

>> > QPS, so having serialization/deserialization overheads per message, or

>> > event separate listening/executor threads can be resource intensive.

>> > Whenever we can, we are tempted to use a stage-event drive architecture,

>> > with few threads that handle large message pools. This also raises the

>> > question of how to implement the upper-layer callbacks (that would

>> perform

>> > the synchronization-related actions) without spawning new threads.

>> >

>> > Regards,

>> > Vlad

>> >

>> >

>> > On Fri, Jul 11, 2014 at 11:40 PM, kishore g <g.kishore@gmail.com> wrote:

>> >

>> >> Good point Vlad, I was thinking of defining the right abstraction and

>> >> possibly provide one implementation based. I think the synchronous and

>> >> asynchronous messaging should be covered as part of this.

>> >>

>> >> Also I think Finagle and likes of it cater more towards the client

>> server

>> >> communication but what we lack today is a good solution for peer to peer

>> >> transport. For example, if some one has to build a consensus layer they

>> >> have build everything from ground up. Providing a base layer that

>> exchange

>> >> messages between peers on a per partition basis can be a great building

>> >> block to build different replication schemes.

>> >>

>> >> Overall messaging can be used for two cases

>> >> -- data and control.

>> >>

>> >>

>> >> CONTROL

>> >>

>> >> This is needed for control messages that occur rarely, for these type of

>> >> messages latency/throughput is not important but its important for it

>> to be

>> >> reliable.

>> >>

>> >>

>> >> DATA

>> >>

>> >> This is mainly exchanging data between different roles,

>> >> controller-participant, participant-participant, spectator-participant.

>> >> These types of message exchanges occur quite frequently and having high

>> >> throughput and low latency is a requirement.

>> >>

>> >> For example having the following api and guarantee would allow one to

>> >> build synchronous replication, asynchronous, quorum etc.

>> >>

>> >> send(partition, message, ACK_MODE, callback) ACK_MODE can be like ACK

>> >> from ALL, QUORUM, 1, NONE etc. callback is fired when one gets the

>> response

>> >> back from the receiver.

>> >>

>> >> This simple api can allow both synchronous and asynchronous mode of

>> >> communication. We dont have to do the serialization/deserialization. The

>> >> hard part here would be to guarantee ordering between the messages. One

>> >> should be able to specify the message ordering requirement, FIFO on a

>> per

>> >> partition level or dont care about ordering. Having this makes it easy

>> for

>> >> one to implement replication schemes.

>> >>

>> >>  thanks,

>> >> Kishore G

>> >>

>> >>

>> >> On Fri, Jul 11, 2014 at 12:49 PM, Greg Brandt <brandt.greg@gmail.com>

>> >> wrote:

>> >>

>> >>> Vlad,

>> >>>

>> >>> I'm not sure that the goal here is to cover all possible use cases.

>> This

>> >>> is

>> >>> intended as basically a replacement for the current Helix cluster

>> >>> messaging

>> >>> service, which doesn't rely on ZooKeeper. I would argue that Helix is

>> >>> already that general framework for discovering the service endpoint,

>> and

>> >>> that this is just one implementation of an underlying messaging stack

>> >>> (for

>> >>> which there is currently only the ZooKeeper-based implementation).

>> >>>

>> >>> Moreover, keeping it too general (i.e. providing the APIs outlined in

>> the

>> >>> JIRA, but no implementation) puts much greater onus on the user. It

>> would

>> >>> be nice for someone just starting out with Helix to have a pretty good

>> >>> messaging service readily available, as well as the APIs to implement

>> >>> more

>> >>> specific solutions if he or she so chooses.

>> >>>

>> >>> -Greg

>> >>>

>> >>>

>> >>> On Fri, Jul 11, 2014 at 11:07 AM, vlad.gm@gmail.com <vlad.gm@gmail.com

>> >

>> >>> wrote:

>> >>>

>> >>> > This sounds like service discovery for a messaging solution. At
this

>> >>> point

>> >>> > there would be some overlap with message buses such as Finagle.

>> Perhaps

>> >>> > this should be a general framework for discovering the service

>> endpoint

>> >>> > that could leave the actual underlaying messaging stack open (be
it

>> >>> > Finagle, Netty-based or ZeroMQ, for example). My only fear is that
if

>> >>> the

>> >>> > messaging framework is encapsulated completely into Helix, it would

>> be

>> >>> hard

>> >>> > to compete with tuned messaging bus solutions and cover all possible

>> >>> use

>> >>> > cases (for example, in my company, we use a large number of sub
cases

>> >>> on

>> >>> > the synchronous call to asynchronous call spectrum).

>> >>> >

>> >>> > Regards,

>> >>> > Vlad

>> >>> >

>> >>> >

>> >>> > On Fri, Jul 11, 2014 at 10:56 AM, Greg Brandt <brandt.greg@gmail.com

>> >

>> >>> > wrote:

>> >>> >

>> >>> >> (copied from HELIX-470)

>> >>> >>

>> >>> >> Helix is missing a high-performance way to exchange messages
among

>> >>> >> resource partitions, with a user-friendly API.

>> >>> >>

>> >>> >> Currently, the Helix messaging service relies on creating many
nodes

>> >>> in

>> >>> >> ZooKeeper, which can lead to ZooKeeper outages if messages
are sent

>> >>> too

>> >>> >> frequently.

>> >>> >>

>> >>> >> In order to avoid this, high-performance NIO-based HelixActors

>> should

>> >>> be

>> >>> >> implemented (in rough accordance with the actor model). HelixActors

>> >>> exchange

>> >>> >> messages asynchronously without waiting for a response, and
are

>> >>> >> partition/state-addressable.

>> >>> >>

>> >>> >> The API would look something like this:

>> >>> >>

>> >>> >> public interface HelixActor<T> {

>> >>> >>     void send(Partition partition, String state, T message);

>> >>> >>     void register(String resource, HelixActorCallback<T>
callback);

>> >>> >> }

>> >>> >> public interface HelixActorCallback<T> {

>> >>> >>     void onMessage(Partition partition, State state, T message);

>> >>> >> }

>> >>> >>

>> >>> >> #send should likely support wildcards for partition number
and

>> state,

>> >>> or

>> >>> >> its method signature might need to be massaged a little bit
for more

>> >>> >> flexibility. But that's the basic idea.

>> >>> >>

>> >>> >> Nothing is inferred about the format of the messages - the
only

>> >>> metadata

>> >>> >> we need to be able to interpret is (1) partition name and (2)
state.

>> >>> The

>> >>> >> user provides a codec to encode / decode messages, so it's
nicer to

>> >>> >> implementHelixActor#send and HelixActorCallback#onMessage.

>> >>> >>

>> >>> >> public interface HelixActorMessageCodec<T> {

>> >>> >>     byte[] encode(T message);

>> >>> >>     T decode(byte[] message);

>> >>> >> }

>> >>> >>

>> >>> >> Actors should support somewhere around 100k to 1M messages
per

>> second.

>> >>> >> The Netty framework is a potential implementation candidate,
but

>> >>> should be

>> >>> >> thoroughly evaluated w.r.t. performance.

>> >>> >>

>> >>> >

>> >>> >

>> >>>

>> >>

>> >>

>> >

>>






 		 	   		  

 		 	   		  
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