[jira] [Created] (DATAFU-63) SimpleRandomSample by a fixed number

["jian wang (JIRA)" <ji...@apache.org>]

jian wang created DATAFU-63:
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             Summary: SimpleRandomSample by a fixed number
                 Key: DATAFU-63
                 URL: https://issues.apache.org/jira/browse/DATAFU-63
             Project: DataFu
          Issue Type: New Feature
            Reporter: jian wang


SimpleRandomSample currently supports random sampling by probability, it does not support random sample a fixed number of items. ReserviorSample may do the work but since it relies on an in-memory priority queue, memory issue may happen if we are going to sample a huge number of items, eg: sample 100M from 100G data. 

Suggested approach is to create a new class "SimpleRandomSampleByCount" that uses Manuver's rejection threshold to reject items whose weight exceeds the threshold as we go from mapper to combiner to reducer. The majority part of the algorithm will be very similar to SimpleRandomSample, except that we do not use Berstein's theory to accept items and replace probability p = k / n,  k is the number of items to sample, n is the total number of items local in mapper, combiner and reducer.

Quote this requirement from others:

"Hi folks,

Question: does anybody know if there is a quicker way to randomly sample a specified number of rows from grouped data? I’m currently doing this, since it appears that the SAMPLE operator doesn’t work inside FOREACH statements:

photosGrouped = GROUP photos BY farm;

agg = FOREACH photosGrouped {
  rnds = FOREACH photos GENERATE *, RANDOM() as rnd;
  ordered_rnds = ORDER rnds BY rnd;
  limitSet = LIMIT ordered_rnds 5000;
  GENERATE group AS farm,
           FLATTEN(limitSet.(photo_id, server, secret)) AS (photo_id, server, secret);
};

This approach seems clumsy, and appears to run quite slowly (I’m assuming the ORDER/LIMIT isn’t great for performance). Is there a less awkward way to do this?

Thanks,
"



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