So that means you have roughly 312.5k rows per tablet, which means about 725k column families in any given tablet. The intersecting iterator will work at a row per time, so I think at any given moment, it will be working through 32 at a time and doing a linear scan through the RFile blocks. With RFile indices, that check is usually pretty fast, but you're having go through 4 orders of magnitude more data sequentially than you can work on. If you can experiment and re-ingest with a smaller number of tablets, anywhere between 15 and 45, I think you will see better performance.
On Fri, Nov 9, 2012 at 11:53 AM, Anthony Fox <[email protected]> wrote: > Failed to answer the original question - 15 tablet servers, 32 > tablets/splits. > > > On Fri, Nov 9, 2012 at 11:52 AM, Anthony Fox <[email protected]> wrote: > >> I've tried a number of different settings of table.split.threshold. I >> started at 1G and bumped it down to 128M and the cf scan is still ~30 >> seconds for both. I've also used less rows - 00000 to 99999 and still see >> similar performance numbers. I thought the column family bloom filter >> would help deal with large row space but sparsely populated column space. >> Is that correct? >> >> >> On Fri, Nov 9, 2012 at 11:49 AM, William Slacum < >> [email protected]> wrote: >> >>> I'm more inclined to believe it's because you have to search across 10M >>> different rows to find any given column family, since they're randomly, and >>> possibly uniformly, distributed. How many tablets are you searching across? >>> >>> >>> On Fri, Nov 9, 2012 at 11:45 AM, Anthony Fox <[email protected]>wrote: >>> >>>> Yes, there are 10M possible partitions. I do not have a hash from >>>> value to partition, the data is essentially randomly balanced across all >>>> the tablets. Unlike the bloom filter and intersecting iterator examples, I >>>> do not have locality groups turned on and I have data in the cq and the >>>> value for both index entries and record entries. Could this be the issue? >>>> Each record entry has approximately 30 column qualifiers with data in the >>>> value for each. >>>> >>>> >>>> On Fri, Nov 9, 2012 at 11:41 AM, William Slacum < >>>> [email protected]> wrote: >>>> >>>>> I guess assuming you have 10M possible partitions, if you're using a >>>>> relatively uniform hash to generate your IDs, you'll average about 2 per >>>>> partition. Do you have any index for term/value to partition? This will >>>>> help you narrow down your search space to a subset of your partitions. >>>>> >>>>> >>>>> On Fri, Nov 9, 2012 at 11:39 AM, William Slacum < >>>>> [email protected]> wrote: >>>>> >>>>>> That shouldn't be a huge issue. How many rows/partitions do you have? >>>>>> How many do you have to scan to find the specific column family/doc id >>>>>> you >>>>>> want? >>>>>> >>>>>> >>>>>> On Fri, Nov 9, 2012 at 11:26 AM, Anthony Fox <[email protected]>wrote: >>>>>> >>>>>>> I have a table set up to use the intersecting iterator pattern. The >>>>>>> table has about 20M records which leads to 20M column families for the >>>>>>> data section - 1 unique column family per record. The index section of >>>>>>> the table is not quite as large as the data section. The rowkey is a >>>>>>> random padded integer partition between 0000000 and 9999999. I turned >>>>>>> bloom filters on and used the ColumnFamilyFunctor to get performant >>>>>>> column family scans without specifying a range like in the bloom filter >>>>>>> examples in the README. However, my column family scans (without any >>>>>>> custom iterator) are still fairly slow - ~30 seconds for a column family >>>>>>> batch scan of one record. I've also tried RowFunctor but I see similar >>>>>>> performance. Can anyone shed any light on the performance metrics I'm >>>>>>> seeing? >>>>>>> >>>>>>> Thanks, >>>>>>> Anthony >>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> >
