Re: [PERFORM] Partioning tsearch2 a table into chunks and accessing via views

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Benjamin Arai wrote:
> This kind of disappointing, I was hoping there was more that could be done.
>
> There has to be another way to do incremental indexing without loosing
> that much performance.

What makes you think you are loosing performance by using partitioning?

Joshua D. Drake

>
> Benjamin
>
> On Aug 24, 2007, at 6:29 PM, Joshua D. Drake wrote:
>
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>> Brandon Shalton wrote:
>>> Benjamin,
>>>
>>>
>>>>
>>>> In order to avoid the re-indexing I was thinking of instead creating
>>>> a new
>>>> table each month (building its indexes and etc) and accessing them all
>>>> through a view. This way I only have to index the new data each month.
>>>>
>>>
>>> Take a look at bizgres.org (based on postgres).
>>>
>>> They have a parent-child structure.
>>>
>>> The way i use it, is I have about 30M records a day that are inserted
>>> into the database.
>>>
>>> Each day is a "child" table to the "parent".
>>>
>>> so example:
>>>
>>> the parent table is called "logfile"
>>>
>>> each day, is a child, with the structure like "logfile_YYMMDD"
>>>
>>> the "child" inherits the table structure of the parent, such that you
>>> could query the child table name directly, or you run the query against
>>> the parent (ie. logfile table) and get all the data.
>>>
>>> the indexes are done on a per table basis, so new data that comes in, is
>>> a lesser amount, and doesn't require re-indexing.
>
>
>> PostgreSQL can do all of this too.
>
>> Sincerely,
>
>> Joshua D. Drake
>
>>>
>>>
>>> example:
>>>
>>> select * from logfile_070825 where datafield = 'foo'
>>>
>>> if i knew i wanted to specifically go into that child, or:
>>>
>>> select * from logfile where datafield = 'foo'
>>>
>>> and all child tables are searched and results merged. You can perform
>>> any kind of sql query and field structures are you normally do.
>>>
>>> the downside is that the queries are run sequentially.
>>>
>>> so if you had 100 child tables, each table is queried via indexes, then
>>> results are merged.
>>>
>>> but, this approach does allow me to dump alot of data in, without having
>>> the re-indexing issues you are facing.
>>>
>>> at some point, you could roll up the days, in to weekly child tables,
>>> then monthly tables, etc.
>>>
>>> I believe Bizgres has a new version of their system that does parallel
>>> queries which would certainly speed things up.
>>>
>>> For your documents, you can do it by the day it was checked in, or maybe
>>> you have some other way of logically grouping, but the parent/child
>>> table structure really helped to solve my problem of adding in millions
>>> of records each day.
>>>
>>> The closest thing in mysql is using merge tables, which is not really
>>> practical when it comes time to do the joins to the tables.
>>>
>>> -brandon
>>>
>>> http://www.t3report.com - marketing intelligence for online marketing
>>> and affiliate programs
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
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>
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