The bloom filter checks only occur on a seek, and the way the column family filter works it's it seeks and then does a few scans to see if the appropriate families pop up in the short term. Bloom filter on the column family would be better if you had larger rows to encourage more seeks/minimize the number of rows to do bloom checks.
The issue is that you are ultimately checking every single row for a column, which is sparse. It's not that different than doing a full table regex. If you had locality groups set up it would be more performant, until you create locality groups for everything. The intersecting iterators get their performance by being able to operate on large rows to avoid the penalty of checking each row. Minimize the number of partitions you have and it should clear up your issues. John Sent from my phone, pardon the typos and brevity. On Nov 9, 2012 12:24 PM, "William Slacum" <[email protected]> wrote: > I'll ask for someone to verify this comment for me (look @ u John W > Vines), but the bloom filter helps when you have a discrete number of > column families that will appear across many rows. > > On Fri, Nov 9, 2012 at 12:18 PM, Anthony Fox <[email protected]> wrote: > >> Ah, ok, I was under the impression that this would be really fast since I >> have a column family bloom filter turned on. Is this not correct? >> >> >> On Fri, Nov 9, 2012 at 12:15 PM, William Slacum < >> [email protected]> wrote: >> >>> When I said smaller of tablets, I really mean smaller number of rows :) >>> My apologies. >>> >>> So if you're searching for a random column family in a table, like with >>> a `scan -c <cf>` in the shell, it will start at row 0 and work sequentially >>> up to row 10000000 until it finds the cf. >>> >>> >>> On Fri, Nov 9, 2012 at 12:11 PM, Anthony Fox <[email protected]>wrote: >>> >>>> This scan is without the intersecting iterator. I'm just trying to >>>> pull back a single data record at the moment which corresponds to scanning >>>> for one column family. I'll try with a smaller number of tablets, but is >>>> the computation effort the same for the scan I am doing? >>>> >>>> >>>> On Fri, Nov 9, 2012 at 12:02 PM, William Slacum < >>>> [email protected]> wrote: >>>> >>>>> 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 >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> >
