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.
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