Re: GSOC PostgreSQL partitioning issue

From: Necati Batur <necatibatur(at)gmail(dot)com>
To: pgsql-hackers(at)postgresql(dot)org
Subject: Re: GSOC PostgreSQL partitioning issue
Date: 2010-04-09 21:12:04
Message-ID: w2z7c3006191004091412w8643c3fawbdabef082afec39c@mail.gmail.com
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Well, If the project criterias and other neccessary information were
collected under a single link that would be great for not only gsoc students
but also for other enthusiastic students :).By provided info we would spend
less time to understand the project phases and requirements and more time on
dediciding part we will develop and do more research on how to develop.
As far as I can see the mailing list is a good way of communication but not
a really good way to inform newbies.
It may be another open-source project to have a project idea to have a
single site and a treeview of all projects and the detailed project
information part to have a really good way of information exchange :)

Thanks all,

2010/4/8 Necati Batur <necatibatur(at)gmail(dot)com>

> Benefits of Project
>
> Partitioning refers to splitting what is logically one large table
> into smaller physical pieces. Partitioning can provide several
> benefits:
>
> Query performance can be improved dramatically in certain situations,
> particularly when most of the heavily accessed rows of the table are
> in a single partition or a small number of partitions. The
> partitioning substitutes for leading columns of indexes, reducing
> index size and making it more likely that the heavily-used parts of
> the indexes fit in memory.
>
> When queries or updates access a large percentage of a single
> partition, performance can be improved by taking advantage of
> sequential scan of that partition instead of using an index and random
> access reads scattered across the whole table.
>
> Bulk loads and deletes can be accomplished by adding or removing
> partitions, if that requirement is planned into the partitioning
> design. ALTER TABLE is far faster than a bulk operation. It also
> entirely avoids the VACUUM overhead caused by a bulk DELETE.
>
> Seldom-used data can be migrated to cheaper and slower storage media.
>
> Delivarables
>
> *The trigger based operations can be done automatically
>
> *The stored procedures can help us to do some functionalities like
> check constraint problem
>
> *manual VACUUM or ANALYZE commands can be handled by using triggers
> DBMS SQL can help to provide faster executions
>
> *Some more functionalities can be added to UPDATE operations to make
> administrations easy
>
> Timeline (not exact but most probably)
>
> Start at june 7 and End around 7 september
>
> *Warm up to environment to Postgresql(1-2 weeks)
>
> *Determine exact operations to be addded on postgresql
>
> *Initial coding as to workbreakdown structure
>
> *Start implementing on distributed environment to check inital functions
> work
>
> *Write test cases for code
>
> *Further implementation to support full functionalities on ideas
>
> *Write it to discussion site and collect feedbacks
>
> *More support upon feedbacks
>
> *Last tests and documentation of final operations
>
> About me
>
> I am a senior student at computer engineering at iztech in turkey. My
> areas of inetrests are information management, OOP(Object Oriented
> Programming) and currently bioinformatics. I have been working with a
> Asistan Professor(Jens Allmer) in molecular biology genetics
> department for one year.Firstly, we worked on a protein database 2DB
> and we presented the project in HIBIT09 organization. The Project was
> “Database management system independence by amending 2DB with a
> database access layer”. Currently, I am working on another project
> (Kerb) as my senior project which is a general sqeuential task
> management system intend to reduce the errors and increase time saving
> in biological experiments. We will present this project in HIBIT2010
> too. Moreover,I am good at data structures and implementations on C.
>
>
> Contact: e-mails; necatibatur(at)gmail(dot)com , necati_batur(at)hotmail(dot)com(msn)
>

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