I'm trying to solve a Word-Count like problem, the difference lies in that, I
need the count of a specific word among a specific timespan in a social message
stream.
My data is in the format of (time, message), and I transformed (flatMap etc.)
it into a series of (time, word_id), the time is represented with Python
datetime.datetime class. And I continued to transform it to ((time, word_id),
1) then use reduceByKey for result.
But the dataset returned is a little weird, just like the following:
format:((timespan with datetime.datetime, wordid), freq)
((datetime.datetime(2009, 10, 6, 2, 0), 0), 8)((datetime.datetime(2009, 10, 6,
3, 0), 0), 3)((datetime.datetime(2009, 10, 6, 3, 0), 0), 14)
As you can see, there are DUPLICATED keys, but as a result of reducedByKey, all
keys SHOULD BE UNIQUE.
I tried to convert the key to a string (like '2006-12-02 21:00:00-000') and
reducedByKey again, the problem stays. It seems the only way left for me is
convert the date to a timestamp, but this time it works.
Is this expected behavior of reduceByKey(and all other transformations that
work with keys)?
Currently I'm still working on it.
