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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
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 <

> 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