[postgis-users] Better storage strategy for 1 million tile of 50*50 pixels, 24 bands?

[Peter Baumann]

On 04/17/2014 08:11 PM, guido lemoine wrote:
> So what do you use instead? Your data set is not exactly common (400+ Gb, 24 
> band doubles (complex data?), overlapping tiles, which are half empty). Is 
> this LiDAR data? What exactly are you trying to visualise?
>
> We have little issue with postgis raster speed using multi-temporal, 
> multi-frame, all bands Landsat-8, either in-db or out-db.
> Over 100 Gb by now. We prefer out-of-db, because it keeps the raster db of 
> manageable size. We expect it to work up to Terrabyte limits (I am told I 
> should use SciDB

when doing that, give rasdaman a try and compare then. It's operational on n-D 
multi-TB objects :)
-Peter

> beyond that). This works with mounted network disk as well, which is even nicer.
>
> GL
>
>
> On 04/17/14, *Rémi Cura * <remi.cura at gmail.com> wrote:
>> Hey,
>> from what I tried PostGis Raster is (relatively) slow and not adapted to 
>> multi bands
>> (for instance, no way to set multiple bands at once. For my use case this 
>> would mean about 300k*0.1sec i.e. about 8 hours at best).
>>
>> The GDAL driver + QGIS should be considered an experimental function at the 
>> moment,
>> because it is still easily broken (and I'm speaking cutting edge gdal + qgis 
>> v 2, 2.2, 2.3 on win and linux).
>> More generaly using QGIS with postgis is easily broken (i restart qgis 
>> several dozen times a day)
>>
>> Taking that into consideration,
>> My conclusion is that for the moment there is no incentive to use __in base__ 
>> postgis raster,
>> because there is no stable way to access raster from outside base.
>>
>> Sadly in my general use case, this translate to no incentive to use postgis 
>> raster at all :-(
>>
>> Cheers,
>> Rémi-C
>>
>>
>>
>>
>> 2014-04-17 17:43 GMT+02:00 Tumasgiu Rossini <rossini.t at gmail.com 
>> <rossini.t at gmail.com>>:
>>
>>     Remi,
>>
>>     I'm interested in the way you handled this problem.
>>
>>     In my opinion, the problem is on the duality of your needs.
>>     Out-db is known to be faster for visualisation.
>>     In-db is better for analysis.
>>
>>     So, a compromise should be made Maybe storing each tile per "band type" ?
>>     So accessing data from qgis would be less painful ?
>>
>>
>>
>>
>>     2014-03-10 10:54 GMT+01:00 Rémi Cura <remi.cura at gmail.com
>>     <remi.cura at gmail.com>>:
>>
>>         Hey Dear List,
>>
>>         I would appreciate some advice about the best way to store my raster :
>>
>>         1 million tiles,
>>         50*50 pixels each (1 m2 or less in real world), around 24 bands
>>         (mostly doubles)
>>         ,in db.
>>
>>         About half the pixels are empty, some tiles overlaps, but most are
>>         regularly spaced.
>>
>>         I would query it mainly by localisation (intersects), and also based
>>         on id of the tile.
>>
>>         The use would be fast visualisation with qgis (and latest gdal),
>>         interpolation, classification, matching and so.
>>
>>         What is the best strategy?
>>         1 table with many lines and indexes, indb,
>>         1 table, out db
>>         1 table, 1 line
>>         multiple tables, heritage?
>>
>>
>>         Thanks for inputs!
>>         Cheers,
>>
>>         Rémi-C
>>
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>>
>>
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>
>
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-- 
Dr. Peter Baumann
  - Professor of Computer Science, Jacobs University Bremen
    www.faculty.jacobs-university.de/pbaumann
    mail: p.baumann at jacobs-university.de
    tel: +49-421-200-3178, fax: +49-421-200-493178
  - Executive Director, rasdaman GmbH Bremen (HRB 26793)
    www.rasdaman.com, mail: baumann at rasdaman.com
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