You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Trill supports using multiple threads to process an input stream by setting Config.StreamScheduler = StreamScheduler.OwnedThreads(n), where n is the number of threads.
Let's consider the number of thread to be 2, and the data item is of shape "(key, val)" (keyset = {1,2,3,...,10}).
According to my observation, when I use MapReduce-pattern to compute the sum of data value over key-based partitions, Trill assigns data items with the same key to the same thread with a certain order, e.g., always assigns key = 1, 3, 5, ... to thread 1 and key = 2, 4, ... to thread 2.
Does Trill provide a random splitter that allows us to do things like: key = 1, 2, 5, 7... to thread 1 and key 3, 4,... to thread 2 (i.e., random key-thread correspondence)? Also, can we implement a customized splitter to split the stream?
The text was updated successfully, but these errors were encountered:
Trill supports using multiple threads to process an input stream by setting
Config.StreamScheduler = StreamScheduler.OwnedThreads(n)
, wheren
is the number of threads.Let's consider the number of thread to be 2, and the data item is of shape "(key, val)" (keyset = {1,2,3,...,10}).
According to my observation, when I use MapReduce-pattern to compute the sum of data value over key-based partitions, Trill assigns data items with the same key to the same thread with a certain order, e.g., always assigns key = 1, 3, 5, ... to thread 1 and key = 2, 4, ... to thread 2.
Does Trill provide a random splitter that allows us to do things like: key = 1, 2, 5, 7... to thread 1 and key 3, 4,... to thread 2 (i.e., random key-thread correspondence)? Also, can we implement a customized splitter to split the stream?
The text was updated successfully, but these errors were encountered: