If the hash is dynamically computed and is stateless, then that brings up one more question.
Let's say there are two spout classes S1 and S2. I create 10 tasks of S1 and 10 tasks of S2. There are 10 tasks of a bolt B. S1 and S2 are fieldsGrouped with B. I receive data x in S1 and another data x in S2. If S1's emit of x goes to task1 of B, then will S2's emit of x also go to task1 of B? *Basically the question is: *Is the hash value decided by the Spout or by Storm? Because if it is decided by the spout, then S1's emit of x can go to task 1 but S2's emit of x might go to some other task of the bolt, and that won't serve the purpose of someone who wants all x'es to go to one bolt. On Wed, Aug 10, 2016 at 8:58 PM, Navin Ipe <navin....@searchlighthealth.com> wrote: > Oh that's good to know. I assume it works like this: > https://en.wikipedia.org/wiki/Hash_function#Hashing_ > uniformly_distributed_data > > On Wed, Aug 10, 2016 at 6:23 PM, Nathan Leung <ncle...@gmail.com> wrote: > >> It's based on a modulo of a hash of the field. The fields grouping is >> stateless. >> >> On Aug 10, 2016 8:18 AM, "Navin Ipe" <navin....@searchlighthealth.com> >> wrote: >> >>> Hi, >>> >>> For spouts to be able to continuously send a fields grouped tuple to the >>> same bolt, it would have to store a key value map something like this, >>> right? >>> >>> field1023 ---> Bolt1 >>> field1343 ---> Bolt3 >>> field1629 ---> Bolt5 >>> field1726 ---> Bolt1 >>> field1481 ---> Bolt3 >>> >>> So if my topology runs for a very long time and the spout generates many >>> unique field values, won't this key value map run out of memory eventually? >>> >>> OR is there a failsafe or a map limit that Storm has to handle this >>> without crashing? >>> >>> If memory problems could happen, what would be an alternative way to >>> solve this problem where many unique fields could get generated over time? >>> >>> -- >>> Regards, >>> Navin >>> >> > > > -- > Regards, > Navin > -- Regards, Navin
