On Fri, Sep 20, 2013 at 4:38 AM, Julian wrote:
> However, I tend to go with partitions when required to be generated on
> demand dynamically and automatically (which probably isn't the case
> here). SCHEMAs have other uses, provide a level of security (GRANT) and
> useful in design when partitioni
On 21/09/13 02:51, Gregory Haase wrote:
I would look towards how PostGis handles the Tiger census data for
guidance. It's a similar, massive data set.
Greg Haase
I'm not sure why it wouldn't handle it fine?
The question is at what point would third party "imported" datasets,
required for l
I would look towards how PostGis handles the Tiger census data for
guidance. It's a similar, massive data set.
Greg Haase
On Sep 20, 2013 9:47 AM, "Jeff Janes" wrote:
> On Thu, Sep 19, 2013 at 12:02 AM, Dave Potts wrote:
>
>> Hi List
>>
>> I am looking for some general advice about the best was
On Thu, Sep 19, 2013 at 12:02 AM, Dave Potts wrote:
> Hi List
>
> I am looking for some general advice about the best was of splitting a
> large data table,I have 2 different choices, partitioning or different
> schemas.
>
I don't think there is much of a choice there. If you put them in
dif
Hi Dave,
How many rows of data are we talking here and how much information? (GiB)
Are you able to provide the table definition? (can normalisation
partition off some of this data?).
Have you addressed dedicated options for lookup data, tune the database
appropriately and keep that single table?
If I were you I will use partitioning. In my experience, partitioning is
easier and transparent. I just have to set it up and then refers just to
one table and done.
About speed, if you have the value "constraint_exclusion" = partition,
postgres will examine constraints only for inheritance child t
Hi List
I am looking for some general advice about the best was of splitting a
large data table,I have 2 different choices, partitioning or different
schemas.
The data table refers to the number of houses that can be include in a
city, as such there are large number of records.
I am won