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From Jack Krupansky <jack.krupan...@gmail.com>
Subject Re: SELECT some_column vs SELECT *
Date Tue, 24 Nov 2015 20:17:01 GMT
Are all or ost of the 1000+ columns populated for a given row? If they are
sparse you can replace them with a single map collection column which would
only occupy the entries that are populated.

-- Jack Krupansky

On Tue, Nov 24, 2015 at 11:04 AM, Jack Krupansky <jack.krupansky@gmail.com>
wrote:

> As always, your queries should drive your data model. Unless you really
> need 1000+ columns for most queries, you should consider separate tables
> for the subsets of the columns that need to be returned for a given query.
>
> The new 3.0 Materialized View feature can be used to easily create subsets
> of a base table, although that begs the question of whether you ever really
> need all 1000+ columns in the same table.
>
> -- Jack Krupansky
>
> On Tue, Nov 24, 2015 at 10:45 AM, Kai Wang <depend@gmail.com> wrote:
>
>> Hi all,
>>
>> If I have the following table:
>> CREATE TABLE t (
>>   pk int,
>>   ck int,
>>   c1 int,
>>   c2 int,
>>   ...
>>   PRIMARY KEY (pk, ck)
>> )
>>
>> There are lots of non-clustering columns (1000+). From time to time I
>> need to do a query like this:
>>
>> SELECT c1 FROM t WHERE pk = abc AND ck > xyz;
>>
>> How efficient is this query compared to SELECT * ...? Apparently SELECT
>> c1 would save a lot of network bandwidth since only c1 needs to be
>> transferred on the wire. But I am more interested in the impact on disk IO.
>> If I understand C* storage engine correctly, one CQL row is clustered
>> together on disk. That means c1 from different rows are stored apart. In
>> the case of SELECT c1, does C* do multiple seeks to only lift c1 of each
>> row from disk or lift the whole row into memory and return c1 from there?
>>
>> From comments on https://issues.apache.org/jira/browse/CASSANDRA-5762 it
>> seems C* lifts the whole row as of 1.2.7. Is this still the case on 2.1.*?
>>
>> Thanks.
>>
>
>

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