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From Christian Schäfer <syrious3...@yahoo.de>
Subject Re: How to query by rowKey-infix
Date Mon, 06 Aug 2012 12:54:03 GMT
The point is that I / we want to make reports for each session that could be present on many
rows distributed over all regions.

As I expect it to be slower to scan Columns than rowkeys I chose the latter.

I guess I may not (yet) share the schema.

The userID and session stuff mentioned is just there to illustrate an comparable situation.


----- Ursprüngliche Message -----
Von: Michael Segel <michael_segel@hotmail.com>
An: user@hbase.apache.org; Christian Schäfer <syrious3000@yahoo.de>
Gesendet: 14:21 Freitag, 3.August 2012
Betreff: Re: How to query by rowKey-infix


What does your schema look like? 

Would it make sense to changing the key to user_id '|' timestamp and then use the session_id
in the column name? 

On Aug 2, 2012, at 7:23 AM, Christian Schäfer <syrious3000@yahoo.de> wrote:

> 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 some kind of
filter chaining)
> The key:  userId-dateInMllis-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:
> ----- 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
> 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

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