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From Martin Kersten <martin.kersten...@gmail.com>
Subject Re: Best-practice guides on coordination of operations in distributed systems (and some C client specific questions)
Date Wed, 13 Jan 2016 11:21:56 GMT
Hello,

   I am not quite aware of the zookeeper specialities but from my point of
view you should think about distributing the task as well like having
multiple nodes being responsible for a task to be done and if one node
fails the other nodes take over and perform/complete the task instead. This
would involve having becon messages and a place you can put your code in.

Locks that time out should actually never happen, since it makes everything
go boom and become overly complex. Just bind a lock to the lifeliness of
the node. So if the node is considered dead free the lock. If the node is
kind of zombie (not reacting (stuck) but responsive in terms of sending
i-am-alife beacons (heart beat)) it is the task of the leader to kill the
node remotely or remove the node from the list of members and inform anyone
else about it. Once this happens this would also revoke the lock.

The goal is to simply let the leader kill any node that seams to be
malfunction in any possible way (like missing a deadline). A node that
wants to complete its operation needs to interact with the leader and at
this point in time the node should realize if it was considered dead and
should restart by crashing and rebooting instantly.

Another thing you might consider is to renew the lock in certain periodes.
If you have a workflow, your lock times out in 10 minutes just every time
you make real progress in your workflow renew the lock giving you another
10minutes to do the next steps.

This way (as long as you do not have a loop in the workflow) you are save
in assuming that a workflow is being completed in the future. If you need a
hard deadline the node processing the operation might as well check the
estimate of the workflow and drop the lock and abort the operation if it
estimates the operation is likely to timeout and might even perform a
compensation operation.


Cheers,

Martin (Kersten)



2016-01-13 11:08 GMT+01:00 singh.janmejay <singh.janmejay@gmail.com>:

> @Alexander: In that scenario, write of X will be attempted by A, but
> external system will not act upon write-X because that operation has
> already been acted upon in the past. This is guaranteed by idempotent
> operations invariant. But it does point out another problem, which I
> hadn't handled in my original algorithm. Problem: If X and Y have both
> not been issued yet, and if Y is issued before X towards external
> system, because neither operations have executed yet, it'll overwrite
> Y with X. I need another constraint, master should only issue 1
> operation on a certain external-system at a time and must issue
> operations in the order of operation-id (sequential-znode sequence
> number). So we need the following invariants:
> - order of issuing operation being fixed (matching order of creation
> of operations)
> - concurrency of operation fixed to 1
> - idempotent execution on external-system side
>
> @Powell: Im kind of doing the same thing. Except the loop doesn't run
> on consumer, instead it runs on master, which is assigning work to
> consumers. So triggerWork function is basically changed to issueWork,
> which is RPC + triggerWork. The replay if history is basically just
> replay of 1 operation per operand-node (in this thread we are calling
> it external-system), so its as if triggerWork failed, in which case we
> need to re-execute triggerWork. Idempotency also follows from that
> requirement. If triggerWork fails in the last step, and all the
> desired effect that was necessary has happened, we will still need to
> run triggerWork again, but we need awareness that actual work has been
> done, which is why idempotency is necessary.
>
> Btw, thanks for continuing to spare time for this, I really appreciate
> this feedback/validation.
>
> Thoughts?
>
> On Wed, Jan 13, 2016 at 3:47 AM, powell molleti
> <powellm79@yahoo.com.invalid> wrote:
> > Wouldn't a distributed queue recipe for consumer work?. Where one needs
> to add extra logic something like this:
> >
> > with lock() {
> >     p = queue.peek()
> >     if triggerWork(p) is Done:
> >         queue.pop()
> > }
> >
> > With this a consumer that worked on it but crashed before popping the
> queue would result in another consumer processing the same work.
> >
> > I am not sure with the details of where you are getting the work from
> and the scale of it is but producers(leader) could write to this queue.
> Since there is guarantee of read after write , producer could delete from
> its local queue the work that was successfully queued. Hence again new
> producer could re-send the last entry of work so one has to handle that.
> Without more details on the origin of work etc its hard to design end to
> end.
> >
> > I do not see a need to do a total replay of past history etc when using
> ZK like system because ZK is built on idea of serialized and replicated
> log, hence if you are using ZK then your design should be much simpler i.e
> fail and re-start from last know transaction.
> >
> > Powell.
> >
> >
> >
> > On Tuesday, January 12, 2016 11:51 AM, Alexander Shraer <
> shralex@gmail.com> wrote:
> > Hi,
> >
> > With your suggestion, the following scenario seems possible: master A is
> > about to write value X to an external system so it logs it to ZK, then
> > freezes for some time, ZK suspects it as failed, another master B is
> > elected, writes X (completing what A wanted to do)
> > then starts doing something else and writes Y. Then leader A "wakes up"
> and
> > re-executes the old operation writing X which is now stale.
> >
> > perhaps if your external system supports conditional updates this can be
> > avoided - a write of X only works if the current state is as expected.
> >
> > Alex
> >
> >
> > On Tue, Jan 5, 2016 at 1:00 AM, singh.janmejay <singh.janmejay@gmail.com
> >
> > wrote:
> >
> >> Thanks for the replies everyone, most of it was very useful.
> >>
> >> @Alexander: The section of chubby paper you pointed me to tries to
> >> address exactly what I was looking for. That clearly is one good way
> >> of doing it. Im also thinking of an alternative way and can use a
> >> review or some feedback on that.
> >>
> >> @Powel: About x509 auth on intra-cluster communication, I don't have a
> >> blocking need for it, as it can be achieved by setting up firewall
> >> rules to accept only from desired hosts. It may be a good-to-have
> >> thing though, because in cloud-based scenarios where IP addresses are
> >> re-used, a recycled IP can still talk to a secure zk-cluster unless
> >> config is changed to remove the old peer IP and replace it with the
> >> new one. Its clearly a corner-case though.
> >>
> >> Here is the approach Im thinking of:
> >> - Implement all operations(atleast master-triggered operations) on
> >> operand machines idempotently
> >> - Have master journal these operations to ZK before issuing RPC
> >> - In case master fails with some of these operations in flight, the
> >> newly elected master will need to read all issued (but not retired
> >> yet) operations and issue them again.
> >> - Existing master(before failure or after failure) can retry and
> >> retire operations according to whatever the retry policy and
> >> success-criterion is.
> >>
> >> Why am I thinking of this as opposed to going with chubby sequencer
> >> passing:
> >> - I need to implement idempotency regardless, because recovery-path
> >> involving master-death after successful execution of operation but
> >> before writing ack to coordination service requires it. So idempotent
> >> implementation complexity is here to stay.
> >> - I need to increase surface-area of the architecture which is exposed
> >> to coordination-service for sequencer validation. Which may bring
> >> verification RPC in data-plane in some cases.
> >> - The sequencer may expire after verification but before ack, in which
> >> case new master may not recognize the operation as consistent with its
> >> decisions (or previous decision path).
> >>
> >> Thoughts? Suggestions?
> >>
> >>
> >>
> >> On Sun, Jan 3, 2016 at 2:18 PM, Alexander Shraer <shralex@gmail.com>
> >> wrote:
> >> > regarding atomic multi-znode updates -- check out "multi" updates
> >> > <
> >>
> http://tdunning.blogspot.com/2011/06/tour-of-multi-update-for-zookeeper.html
> >> >
> >> > .
> >> >
> >> > On Sat, Jan 2, 2016 at 10:45 PM, Alexander Shraer <shralex@gmail.com>
> >> wrote:
> >> >
> >> >> for 1, see the chubby paper
> >> >> <
> >>
> http://static.googleusercontent.com/media/research.google.com/en//archive/chubby-osdi06.pdf
> >> >,
> >> >> section 2.4.
> >> >> for 2, I'm not sure I fully understand the question, but
> essentially, ZK
> >> >> guarantees that even during failures
> >> >> consistency of updates is preserved. The user doesn't need to do
> >> anything
> >> >> in particular to guarantee this, even
> >> >> during leader failures. In such case, some suffix of operations
> executed
> >> >> by the leader may be lost if they weren't
> >> >> previously acked by a majority.However, none of these operations
> could
> >> >> have been visible
> >> >> to reads.
> >> >>
> >> >> On Fri, Jan 1, 2016 at 12:29 AM, powell molleti <
> >> >> powellm79@yahoo.com.invalid> wrote:
> >> >>
> >> >>> Hi Janmejay,
> >> >>> Regarding question 1, if a node takes a lock and the lock has
> timed-out
> >> >>> from system perspective then it can mean that other nodes are free
> to
> >> take
> >> >>> the lock and work on the resource. Hence the history could be well
> >> into the
> >> >>> future when the previous node discovers the time-out. The question
> of
> >> >>> rollback in the specific context depends on the implementation
> >> details, is
> >> >>> the lock holder updating some common area?, then there could be
> >> corruption
> >> >>> since other nodes are free to write in parallel to the first one?.
> In
> >> the
> >> >>> usual sense a time-out of lock held means the node which held the
> lock
> >> is
> >> >>> dead. It is upto the implementation to ensure this case and, using
> this
> >> >>> primitive, if there is a timeout which means other nodes are sure
> that
> >> no
> >> >>> one else is working on the resource and hence can move forward.
> >> >>> Question 2 seems to imply the assumption that leader has significant
> >> work
> >> >>> todo and leader change is quite common, which seems contrary to
> common
> >> >>> implementation pattern. If the work can be broken down into smaller
> >> chunks
> >> >>> which need serialization separately then each chunk/work type can
> have
> >> a
> >> >>> different leader.
> >> >>> For question 3, ZK does support auth and encryption for client
> >> >>> connections but not for inter ZK node channels. Do you have
> >> requirement to
> >> >>> secure inter ZK nodes, can you let us know what your requirements
> are
> >> so we
> >> >>> can implement a solution to fit all needs?.
> >> >>> For question 4 the official implementation is C, people tend to
wrap
> >> that
> >> >>> with C++ and there should projects that use ZK doing that you can
> look
> >> them
> >> >>> up and see if you can separate it out and use them.
> >> >>> Hope this helps.Powell.
> >> >>>
> >> >>>
> >> >>>
> >> >>>     On Thursday, December 31, 2015 8:07 AM, Edward Capriolo <
> >> >>> edward.capriolo@huffingtonpost.com> wrote:
> >> >>>
> >> >>>
> >> >>>  Q:What is the best way of handling distributed-lock expiry? The
> owner
> >> >>> of the lock managed to acquire it and may be in middle of some
> >> >>> computation when the session expires or lock expire
> >> >>>
> >> >>> If you are using Java a way I can see doing this is by using the
> >> >>> ExecutorCompletionService
> >> >>>
> >> >>>
> >>
> https://docs.oracle.com/javase/7/docs/api/java/util/concurrent/ExecutorCompletionService.html
> >> >>> .
> >> >>> It allows you to keep your workers in a group, You can poll the
> group
> >> and
> >> >>> provide cancel semantics as needed.
> >> >>> An example of that service is here:
> >> >>>
> >> >>>
> >>
> https://github.com/edwardcapriolo/nibiru/blob/master/src/main/java/io/teknek/nibiru/coordinator/EventualCoordinator.java
> >> >>> where I am issuing multiple reads and I want to abandon the process
> if
> >> >>> they
> >> >>> do not timeout in a while. Many async/promices frameworks do this
by
> >> >>> launching two task ComputationTask and a TimeoutTask that returns
> in 10
> >> >>> seconds. Then they ask the completions service to poll. If the
> service
> >> is
> >> >>> given the TimoutTask after the timeout that means the Computation
> did
> >> not
> >> >>> finish in time.
> >> >>>
> >> >>> Do people generally take action in middle of the computation (abort
> it
> >> and
> >> >>> do itin a clever way such that effect appears atomic, so abort
is
> >> >>> notreally
> >> >>> visible, if so what are some of those clever ways)?
> >> >>>
> >> >>> The base issue is java's synchronized/ AtomicReference do not have
a
> >> >>> rollback.
> >> >>>
> >> >>> There are a few ways I know to work around this. Clojure has STM
> >> (software
> >> >>> Transactional Memory) such that if an exception is through inside
a
> >> doSync
> >> >>> all of the stems inside the critical block never happened. This
> assumes
> >> >>> your using all clojure structures which you are probably not.
> >> >>> A way co workers have done this is as follows. Move your entire
> >> >>> transnational state into a SINGLE big object that you can
> >> >>> copy/mutate/compare and swap. You never need to rollback each piece
> >> >>> because
> >> >>> your changing the clone up until the point you commit it.
> >> >>> Writing reversal code is possible depending on the problem. There
> are
> >> >>> questions to ask like "what if the reversal somehow fails?"
> >> >>>
> >> >>>
> >> >>>
> >> >>>
> >> >>> On Thu, Dec 31, 2015 at 3:10 AM, singh.janmejay <
> >> singh.janmejay@gmail.com
> >> >>> >
> >> >>> wrote:
> >> >>>
> >> >>> > Hi,
> >> >>> >
> >> >>> > Was wondering if there are any reference designs, patterns
on
> >> handling
> >> >>> > common operations involving distributed coordination.
> >> >>> >
> >> >>> > I have a few questions and I guess they must have been asked
> before,
> >> I
> >> >>> > am unsure what to search for to surface the right answers.
It'll
> be
> >> >>> > really valuable if someone can provide links to relevant
> >> >>> > "best-practices guide" or "suggestions" per question or share
some
> >> >>> > wisdom or ideas on patterns to do this in the best way.
> >> >>> >
> >> >>> > 1. What is the best way of handling distributed-lock expiry?
The
> >> owner
> >> >>> > of the lock managed to acquire it and may be in middle of
some
> >> >>> > computation when the session expires or lock expires. When
it
> >> finishes
> >> >>> > that computation, it can tell that the lock expired, but do
people
> >> >>> > generally take action in middle of the computation (abort
it and
> do
> >> it
> >> >>> > in a clever way such that effect appears atomic, so abort
is not
> >> >>> > really visible, if so what are some of those clever ways)?
Or is
> the
> >> >>> > right thing to do, is to write reversal-code, such that operations
> >> can
> >> >>> > be cleanly undone in case the verification at the end of
> computation
> >> >>> > shows that lock expired? The later obviously is a lot harder
to
> >> >>> > achieve.
> >> >>> >
> >> >>> > 2. Same as above for leader-election scenarios. Leader generally
> >> >>> > administers operations on data-systems that take significant
time
> to
> >> >>> > complete and have significant resource overhead and RPC to
> administer
> >> >>> > such operations synchronously from leader to data-node can't
be
> >> atomic
> >> >>> > and can't be made latency-resilient to such a degree that
issuing
> >> >>> > operation across a large set of nodes on a cluster can be
> guaranteed
> >> >>> > to finish without leader-change. What do people generally
do in
> such
> >> >>> > situations? How are timeouts for operations issued when operations
> >> are
> >> >>> > issued using sequential-znode as a per-datanode dedicated
queue?
> How
> >> >>> > well does it scale, and what are some things to watch-out
for
> >> >>> > (operation-size, encoding, clustering into one znode for atomicity
> >> >>> > etc)? Or how are atomic operations that need to be issued
across
> >> >>> > multiple data-nodes managed (do they have to be clobbered
into one
> >> >>> > znode)?
> >> >>> >
> >> >>> > 3. How do people secure zookeeper based services? Is
> >> >>> > client-certificate-verification the recommended way? How well
does
> >> >>> > this work with C client? Is inter-zk-node communication done
with
> >> >>> > X509-auth too?
> >> >>> >
> >> >>> > 4. What other projects, reference-implementations or libraries
> should
> >> >>> > I look at for working with C client?
> >> >>> >
> >> >>> > Most of what I have asked revolves around leader or lock-owner
> having
> >> >>> > a false-failure (where it doesn't know that coordinator thinks
it
> has
> >> >>> > failed).
> >> >>> >
> >> >>> > --
> >> >>> > Regards,
> >> >>> > Janmejay
> >> >>> > http://codehunk.wordpress.com
> >> >>> >
> >> >>>
> >> >>>
> >> >>>
> >> >>>
> >> >>
> >> >>
> >>
> >>
> >>
> >> --
> >> Regards,
> >> Janmejay
> >> http://codehunk.wordpress.com
> >>
>
>
>
> --
> Regards,
> Janmejay
> http://codehunk.wordpress.com
>

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