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Accumulo, mail # user - Performance of table with large number of column families

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Re: Performance of table with large number of column families
William Slacum 2012-11-09, 17:02
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