| From: | Heikki Linnakangas <hlinnakangas(at)vmware(dot)com> |
|---|---|
| To: | Yuri Levinsky <yuril(at)celltick(dot)com> |
| Cc: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us>, Christopher Browne <cbbrowne(at)gmail(dot)com>, Robert Haas <robertmhaas(at)gmail(dot)com>, Bruce Momjian <bruce(at)momjian(dot)us>, PostgreSQL Mailing Lists <pgsql-hackers(at)postgresql(dot)org> |
| Subject: | Re: Hash partitioning. |
| Date: | 2013-06-26 11:23:08 |
| Message-ID: | 51CACF1C.7070104@vmware.com |
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| Lists: | pgsql-hackers |
On 26.06.2013 11:17, Yuri Levinsky wrote:
> The main purpose of partitioning in my world
> is to store billions of rows and be able to search by date, hour or even
> minute as fast as possible.
Hash partitioning sounds like a bad fit for that use case. A regular
b-tree, possibly with range partitioning, sounds optimal for that.
> When you dealing with company, which has
> ~350.000.000 users, and you don't want to use key/value data stores: you
> need hash partitioned tables and hash partitioned table clusters to
> perform fast search and 4-6 tables join based on user phone number for
> example.
B-trees are surprisingly fast for key-value lookups. There is no reason
to believe that a hash partitioned table would be faster for that than a
plain table.
- Heikki
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