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Stavros Kontopoulos edited comment on FLINK-2147 at 4/4/17 2:04 PM: -------------------------------------------------------------------- You just pick one of the sketches merge it with another one kill the task (3 down to 2 case). For 1 to N. Just split the stream and create N-1 count-min sketches, keep the first as is. Wouldn't that work? was (Author: skonto): You just pick one of the sketches merge it with another one kill the task (3 down to 2 case). For 1 to N. Just split the stream and create N count-min sketches. Wouldn't that work? > Approximate calculation of frequencies in data streams > ------------------------------------------------------ > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: DataStream API > Reporter: Gabor Gevay > Labels: approximate, statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian JIRA (v6.3.15#6346)