I see. Thanks Alan for your reply. Also one more question that I posted earlier was
I used RandomSampleLoader and specified a sample size of 100. The number of map tasks that are executed is 110. So I am expecting total samples that are received on the reducer to be 110*100 = 11000 but its always more than the expected value. The actual received tuples is between 14000 to 15000. I am not sure if its a bug or if I am missing something. Is it an expected behavior? Thanks -- Prasanth On Aug 23, 2012, at 6:20 PM, Alan Gates <ga...@hortonworks.com> wrote: > Sorry for the very slow response, but here it is, hopefully better late than > never. > > On Jul 25, 2012, at 4:28 PM, Prasanth J wrote: > >> Thanks Alan. >> The requirement for me is that I want to load N number of samples based on >> the input file size and perform naive cube computation to determine the >> large groups that will not fit in reducer's memory. I need to know the exact >> number of samples for calculating the partition factor for large groups. >> Currently I am using RandomSampleLoader to load 1000 tuples from each >> mapper. Without knowing the number of mappers I will not be able to find the >> exact number of samples loaded. Also RandomSampleLoader doesn't attach any >> special marker (as in PoissonSampleLoader) tuples which tells the number of >> samples loaded. >> Is there any other way to know the exact number of samples loaded? > Not that I know of. > >> >> By analyzing the MR plans of order-by and skewed-join, it seems like the >> entire dataset is copied to a temp file and then SampleLoaders use the temp >> file to load samples. Is there any specific reason for this redundant copy? >> Is it because SampleLoaders can only use pig's internal i/o format? > Partly, but also because it allows any operators that need to run before the > sample (like project or filter) to be placed in the pipeline. > > Alan. >
