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From Christian Schäfer <syrious3...@yahoo.de>
Subject Re: How to query by rowKey-infix
Date Thu, 09 Aug 2012 20:55:23 GMT
Nice. Thanks Alex for sharing your experiences with that custom filter implementation.


Currently I'm still using key filter with substring comparator.
As soon as I got a good amount of test data I will measure performance of that naiive substring
filter in comparison to your fuzzy row filter.

regards,
Christian



________________________________
Von: Alex Baranau <alex.baranov.v@gmail.com>
An: user@hbase.apache.org; Christian Schäfer <syrious3000@yahoo.de> 
Gesendet: 22:18 Donnerstag, 9.August 2012
Betreff: Re: How to query by rowKey-infix


jfyi: documented FuzzyRowFilter usage here: http://bit.ly/OXVdbg. Will add documentation to
HBase book very soon [1]

Alex Baranau
------
Sematext :: http://sematext.com/ :: Hadoop - HBase - ElasticSearch - Solr

[1] https://issues.apache.org/jira/browse/HBASE-6526

On Fri, Aug 3, 2012 at 6:14 PM, Alex Baranau <alex.baranov.v@gmail.com> wrote:

Good!
>
>
>Submitted initial patch of fuzzy row key filter at https://issues.apache.org/jira/browse/HBASE-6509.
You can just copy the filter class and include it in your code and use it in your setup as
any other custom filter (no need to patch HBase).
>
>
>Please let me know if you try it out (or post your comments at HBASE-6509).
>
>
>Alex Baranau
>------
>Sematext :: http://sematext.com/ :: Hadoop - HBase - ElasticSearch - Solr
>
>
>On Fri, Aug 3, 2012 at 5:23 AM, Christian Schäfer <syrious3000@yahoo.de> wrote:
>
>Hi Alex,
>>
>>thanks a lot for the hint about setting the timestamp of the put.
>>I didn't know that this would be possible but that's solving the problem (first test
was successful).
>>So I'm really glad that I don't need to apply a filter to extract the time and so
on for every row.
>>
>>Nevertheless I would like to see your custom filter implementation.
>>Would be nice if you could provide it helping me to get a bit into it.
>>
>>And yes that helped :)
>>
>>regards
>>Chris
>>
>>
>>
>>________________________________
>>Von: Alex Baranau <alex.baranov.v@gmail.com>
>>An: user@hbase.apache.org; Christian Schäfer <syrious3000@yahoo.de>
>>Gesendet: 0:57 Freitag, 3.August 2012
>>
>>Betreff: Re: How to query by rowKey-infix
>>
>>
>>Hi Christian!
>>If to put off secondary indexes and assume you are going with "heavy scans", you can
try two following things to make it much faster. If this is appropriate to your situation,
of course.
>>
>>1.
>>
>>> Is there a more elegant way to collect rows within time range X?
>>> (Unfortunately, the date attribute is not equal to the timestamp that is stored
by hbase automatically.)
>>
>>Can you set timestamp of the Puts to the one you have in row key? Instead of relying
on the one that HBase puts automatically (current ts). If you can, this will improve reading
speed a lot by setting time range on scanner. Depending on how you are writing your data of
course, but I assume that you mostly write data in "time-increasing" manner.
>>
>>
>>2.
>>
>>If your userId has fixed length, or you can change it so that it has fixed length,
then you can actually use smth like "wildcard"  in row key. There's a way in Filter implementation
to fast-forward to the record with specific row key and by doing this skip many records. This
might be used as follows:
>>* suppose your userId is 5 characters in length
>>* suppose you are scanning for records with time between 2012-08-01 and 2012-08-08
>>* when you scanning records and you face e.g. key "aaaaa_2012-08-09_3jh345j345kjh",
where "aaaaa" is user id, you can tell the scanner from your filter to fast-forward to key
"aaaab_ 2012-08-01". Because you know that all remained records of user "aaaaa" don't fall
into the interval you need (as the time for its records will be >= 2012-08-09).
>>
>>As of now, I believe you will have to implement your custom filter to do that. Pointer: org.apache.hadoop.hbase.filter.Filter.ReturnCode.SEEK_NEXT_USING_HINT
>>I believe I implemented similar thing some time ago. If this idea works for you I
could look for the implementation and share it if it helps. Or may be even simply add it to
HBase codebase.
>>
>>Hope this helps,
>>
>>
>>Alex Baranau
>>------
>>Sematext :: http://blog.sematext.com/ :: Hadoop - HBase - ElasticSearch - Solr
>>
>>
>>
>>On Thu, Aug 2, 2012 at 8:40 AM, Christian Schäfer <syrious3000@yahoo.de> wrote:
>>
>>
>>>
>>>Excuse my double posting.
>>>Here is the complete mail:
>>>
>>>
>>>
>>>OK,
>>>
>>>at first I will try the scans.
>>>
>>>If that's too slow I will have to upgrade hbase (currently 0.90.4-cdh3u2) to be
able to use coprocessors.
>>>
>>>
>>>Currently I'm stuck at the scans because it requires two steps (therefore maybe
some kind of filter chaining is required)
>>>
>>>
>>>The key:  userId-dateInMillis-sessionId
>>>
>>>
>>>At first I need to extract dateInMllis with regex or substring (using special
delimiters for date)
>>>
>>>Second, the extracted value must be parsed to Long and set to a RowFilter Comparator
like this:
>>>
>>>scan.setFilter(new RowFilter(CompareOp.GREATER_OR_EQUAL, new BinaryComparator(Bytes.toBytes((Long)dateInMillis))));
>>>
>>>How to chain that?
>>>Do I have to write a custom filter?
>>>(Would like to avoid that due to deployment)
>>>
>>>regards
>>>Chris
>>>
>>>
>>>----- Ursprüngliche Message -----
>>>Von: Michael Segel <michael_segel@hotmail.com>
>>>An: user@hbase.apache.org
>>>CC:
>>>Gesendet: 13:52 Mittwoch, 1.August 2012
>>>Betreff: Re: How to query by rowKey-infix
>>>
>>>Actually w coprocessors you can create a secondary index in short order.
>>>Then your cost is going to be 2 fetches. Trying to do a partial table scan will
be more expensive.
>>>
>>>On Jul 31, 2012, at 12:41 PM, Matt Corgan <mcorgan@hotpads.com> wrote:
>>>
>>>> When deciding between a table scan vs secondary index, you should try to
>>>> estimate what percent of the underlying data blocks will be used in the
>>>> query.  By default, each block is 64KB.
>>>>
>>>> If each user's data is small and you are fitting multiple users per block,
>>>> then you're going to need all the blocks, so a tablescan is better because
>>>> it's simpler.  If each user has 1MB+ data then you will want to pick out
>>>> the individual blocks relevant to each date.  The secondary index will help
>>>> you go directly to those sparse blocks, but with a cost in complexity,
>>>> consistency, and extra denormalized data that knocks primary data out of
>>>> your block cache.
>>>>
>>>> If latency is not a concern, I would start with the table scan.  If that's
>>>> too slow you add the secondary index, and if you still need it faster you
>>>> do the primary key lookups in parallel as Jerry mentions.
>>>>
>>>> Matt
>>>>
>>>> On Tue, Jul 31, 2012 at 10:10 AM, Jerry Lam <chilinglam@gmail.com>
wrote:
>>>>
>>>>> Hi Chris:
>>>>>
>>>>> I'm thinking about building a secondary index for primary key lookup,
then
>>>>> query using the primary keys in parallel.
>>>>>
>>>>> I'm interested to see if there is other option too.
>>>>>
>>>>> Best Regards,
>>>>>
>>>>> Jerry
>>>>>
>>>>> On Tue, Jul 31, 2012 at 11:27 AM, Christian Schäfer <syrious3000@yahoo.de
>>>>>> wrote:
>>>>>
>>>>>> Hello there,
>>>>>>
>>>>>> I designed a row key for queries that need best performance (~100
ms)
>>>>>> which looks like this:
>>>>>>
>>>>>> userId-date-sessionId
>>>>>>
>>>>>> These queries(scans) are always based on a userId and sometimes
>>>>>> additionally on a date, too.
>>>>>> That's no problem with the key above.
>>>>>>
>>>>>> However, another kind of queries shall be based on a given time range
>>>>>> whereas the outermost left userId is not given or known.
>>>>>> In this case I need to get all rows covering the given time range
with
>>>>>> their date to create a daily reporting.
>>>>>>
>>>>>> As I can't set wildcards at the beginning of a left-based index for
the
>>>>>> scan,
>>>>>> I only see the possibility to scan the index of the whole table to
>>>>> collect
>>>>>> the
>>>>>> rowKeys that are inside the timerange I'm interested in.
>>>>>>
>>>>>> Is there a more elegant way to collect rows within time range X?
>>>>>> (Unfortunately, the date attribute is not equal to the timestamp
that is
>>>>>> stored by hbase automatically.)
>>>>>>
>>>>>> Could/should one maybe leverage some kind of row key caching to
>>>>> accelerate
>>>>>> the collection process?
>>>>>> Is that covered by the block cache?
>>>>>>
>>>>>> Thanks in advance for any advice.
>>>>>>
>>>>>> regards
>>>>>> Chris
>>>>>>
>>>>>
>>>
>>
>>
>>--
>>
>>Alex Baranau
>>------
>>Sematext :: http://blog.sematext.com/ :: Hadoop - HBase - ElasticSearch - Solr 
>>
>
>
>
>-- 
>
>Alex Baranau
>------
>Sematext :: http://blog.sematext.com/ :: Hadoop - HBase - ElasticSearch - Solr
>

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