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 >>>>>>>>> >>>>>>>>> >>>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> >
