Hi T.I.
Few things why Spout is responsible for replay rather then Various Bolts.
1. ack and fail messages carry only message ID, Usually your spouts
generate messaged Id and knows what tuple/message is linked to it(via
source i.e. jms etc). If ack or fail happens then Spout can do various
things like on ack delete from queue, on fail put in some dead letter
queue. intermediate Bolt Wont know what message it sent, unless you
implement something of your own. Technically you can put Delete message
from JMS in bolts but then your whole topology knows from where you are
getting data, what if tommorow you start processing data from JMS, Http
rest service, Database and file system etc.
2. BoltB fails, it tells BoltA, BoltA retry 3 times, it fails 3 times, now
what BoltA should do,? Send it to another bolt(say BoltPreA exists between
him and spout) or send it to Spout.?
If it sends to BoltPreA that means BoltPreA will retry 3 times(just
using 3 number consider as N), that means for each try to BoltPreA, BoltA
will retry again 3 times, so total 9 retries.(basically total retries will
be based on Total bolt from Spout to Failure Bolt TB and total Retries TR,
it will be like TR + Power(TR,2) ..... + Power(TR,TB)
If you send back from failure from BoltA to Spout then we can argue
why not send it to Spout from BoltB, as a framework i shouldnt be looking
into if BoltB is really costly or BoltA is really costly.
3. Also failure scenario are suppose to be really really low, and if your
database is down(means 100% tuple will fail), then performance wont be your
only concern. your concern will be to make sure database comes up and
reprocess all failed tuple.
4. Also you will have to take care of retry logic in every Bolt. Currently
its only at one place.
*There is one thing i am looking forward from Storm is to inform Spout
about what kind of failure it was*. i.e. if it was ConnectionTimeout or
ReadTimeout etc, that means if i retry it may pass. But say it was null
pointer exception(java world) , i know the data which is being expected is
not there and my code is not handling that scenario, so either i will have
to change code or ask data provider to send that field, but retry wont help
me.
Currently only way to do is use a outside datastore like Redis, whichever
Bolt you fail add a key with mesageId and Exception/error detail in redis
before calling fail. and then let Spout read that data from redis with
messageId received in onFail call and then spout can decide if i want to
retry or not. I would usually Create two wrappers Retry-able Exception and
*non* Retry-able Exception, so each bolt can inform whether retry can help
or not. Its upto you where you put this decision making logic.
Thanks
Ravi.
On Wed, Sep 14, 2016 at 6:43 AM, Tech Id <[email protected]> wrote:
> Thanks Ambud,
>
> I did read some very good things about acking mechanism in Storm but I am
> not sure it explains why point to point checking is expensive.
>
> Consider the example: Spout--> BoltA--->BoltB.
>
> If BoltB fails, it will report failure to the acker.
> If the acker can ask the Spout to replay, then why can't the acker ask the
> parent of BoltB to replay at this point?
> I don't think keeping parent of a bolt could be expensive.
>
>
> On a related note, I am a little confused about a statement "When a new
> tupletree is born, the spout sends the XORed edge-ids of each tuple
> recipient, which the acker records in its pending ledger" in
> Acking-framework-implementation.html
> <http://storm.apache.org/releases/current/Acking-framework-implementation.html>
> .
> How does the spout know before hand which bolts would receive the tuple?
> Bolts forward tuples to other bolts based on groupings and dynamically
> generated fields. How does spout know what fields will be generated and
> which bolts will receive the tuples? If it does not know that, then how
> does it send the XOR of each tuple recipient in a tuple's path because each
> tuple's path will be different (I think, not sure though).
>
>
> Thx,
> T.I.
>
>
> On Tue, Sep 13, 2016 at 6:37 PM, Ambud Sharma <[email protected]>
> wrote:
>
>> Here is a post on it https://bryantsai.com/fault-to
>> lerant-message-processing-in-storm/.
>>
>> Point to point tracking is expensive unless you are using transactions.
>> Flume does point to point transfers using transactions.
>>
>> On Sep 13, 2016 3:27 PM, "Tech Id" <[email protected]> wrote:
>>
>>> I agree with this statement about code/architecture but in case of some
>>> system outages, like one of the end-points (Solr, Couchbase, Elastic-Search
>>> etc.) being down temporarily, a very large number of other fully-functional
>>> and healthy systems will receive a large number of duplicate replays
>>> (especially in heavy throughput topologies).
>>>
>>> If you can elaborate a little more on the performance cost of tracking
>>> tuples or point to a document reflecting the same, that will be of great
>>> help.
>>>
>>> Best,
>>> T.I.
>>>
>>> On Tue, Sep 13, 2016 at 12:26 PM, Hart, James W. <[email protected]>
>>> wrote:
>>>
>>>> Failures should be very infrequent, if they are not then rethink the
>>>> code and architecture. The performance cost of tracking tuples in the way
>>>> that would be required to replay at the failure is large, basically that
>>>> method would slow everything way down for very infrequent failures.
>>>>
>>>>
>>>>
>>>> *From:* S G [mailto:[email protected]]
>>>> *Sent:* Tuesday, September 13, 2016 3:17 PM
>>>> *To:* [email protected]
>>>> *Subject:* Re: How will storm replay the tuple tree?
>>>>
>>>>
>>>>
>>>> Hi,
>>>>
>>>>
>>>>
>>>> I am a little curious to know why we begin at the spout level for case
>>>> 1.
>>>>
>>>> If we replay at the failing bolt's parent level (BoltA in this case),
>>>> then it should be more performant due to a decrease in duplicate processing
>>>> (as compared to whole tuple tree replays).
>>>>
>>>>
>>>>
>>>> If BoltA crashes due to some reason while replaying, only then the
>>>> Spout should receive this as a failure and whole tuple tree should be
>>>> replayed.
>>>>
>>>>
>>>>
>>>> This saving in duplicate processing will be more visible with several
>>>> layers of bolts.
>>>>
>>>>
>>>>
>>>> I am sure there is a good reason to replay the whole tuple-tree, and
>>>> want to know the same.
>>>>
>>>>
>>>>
>>>> Thanks
>>>>
>>>> SG
>>>>
>>>>
>>>>
>>>> On Tue, Sep 13, 2016 at 10:22 AM, P. Taylor Goetz <[email protected]>
>>>> wrote:
>>>>
>>>> Hi Cheney,
>>>>
>>>>
>>>>
>>>> Replays happen at the spout level. So if there is a failure at any
>>>> point in the tuple tree (the tuple tree being the anchored emits,
>>>> unanchored emits don’t count), the original spout tuple will be replayed.
>>>> So the replayed tuple will traverse the topology again, including
>>>> unanchored points.
>>>>
>>>>
>>>>
>>>> If an unanchored tuple fails downstream, it will not trigger a replay.
>>>>
>>>>
>>>>
>>>> Hope this helps.
>>>>
>>>>
>>>>
>>>> -Taylor
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Sep 13, 2016, at 4:42 AM, Cheney Chen <[email protected]> wrote:
>>>>
>>>>
>>>>
>>>> Hi there,
>>>>
>>>>
>>>>
>>>> We're using storm 1.0.1, and I'm checking through
>>>> http://storm.apache.org/releases/1.0.1/Guaranteeing-
>>>> message-processing.html
>>>>
>>>>
>>>>
>>>> Got questions for below two scenarios.
>>>>
>>>> Assume topology: S (spout) --> BoltA --> BoltB
>>>>
>>>> 1. S: anchored emit, BoltA: anchored emit
>>>>
>>>> Suppose BoltB processing failed w/ ack, what will the replay be, will
>>>> it execute both BoltA and BoltB or only failed BoltB processing?
>>>>
>>>>
>>>>
>>>> 2. S: anchored emit, BoltA: unanchored emit
>>>>
>>>> Suppose BoltB processing failed w/ ack, replay will not happen, correct?
>>>>
>>>>
>>>>
>>>> --
>>>>
>>>> Regards,
>>>> Qili Chen (Cheney)
>>>>
>>>> E-mail: [email protected]
>>>> MP: (+1) 4086217503
>>>>
>>>>
>>>>
>>>>
>>>>
>>>
>>>
>
