<div dir="ltr"><div><div><div><div><div>Hey,<br>from what I tried PostGis Raster is (relatively) slow and not adapted to multi bands<br></div>(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).<br>
<br></div>The GDAL driver + QGIS should be considered an experimental function at the moment, <br>because it is still easily broken (and I'm speaking cutting edge gdal + qgis v 2, 2.2, 2.3 on win and linux).<br></div>
<div>More generaly using QGIS with postgis is easily broken (i restart qgis several dozen times a day)<br></div><div><br></div><div>Taking that into consideration, <br></div>My conclusion is that for the moment there is no incentive to use __in base__ postgis raster, <br>
</div><div>because there is no stable way to access raster from outside base.<br><br></div>Sadly in my general use case, this translate to no incentive to use postgis raster at all :-(<br><br></div>Cheers,<br>Rémi-C<br><div>
<div><div><br><br></div></div></div></div><div class="gmail_extra"><br><br><div class="gmail_quote">2014-04-17 17:43 GMT+02:00 Tumasgiu Rossini <span dir="ltr"><<a href="mailto:rossini.t@gmail.com" target="_blank">rossini.t@gmail.com</a>></span>:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div>Remi,<br><br></div>I'm interested in the way you handled this problem.<br></div><div><br>In my opinion, the problem is on the duality of your needs.<br>
</div><div>Out-db is known to be faster for visualisation.<br>
</div><div>In-db is better for analysis.<br><br></div><div>So, a compromise should be made Maybe storing each tile per "band type" ? So accessing data from qgis would be less painful ?<br></div><div><br></div><div>
<br></div>
</div><div class="gmail_extra"><br><br><div class="gmail_quote">2014-03-10 10:54 GMT+01:00 Rémi Cura <span dir="ltr"><<a href="mailto:remi.cura@gmail.com" target="_blank">remi.cura@gmail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div><div class="h5">
<div dir="ltr"><div><div><div><div><div><div><div><div><div>Hey Dear List,<br><br></div>I would appreciate some advice about the best way to store my raster :<br><br></div>1 million tiles,<br></div>50*50 pixels each (1 m2 or less in real world), around 24 bands (mostly doubles)<br>
</div><div>,in db.<br></div><div><br></div><div>About half the pixels are empty, some tiles overlaps, but most are regularly spaced.<br></div><div><br></div>I would query it mainly by localisation (intersects), and also based on id of the tile.<br>
<br></div><div>The use would be fast visualisation with qgis (and latest gdal), interpolation, classification, matching and so.<br></div><div><br></div>What is the best strategy?<br></div>1 table with many lines and indexes, indb,<br>
</div>1 table, out db<br></div><div>1 table, 1 line<br></div>multiple tables, heritage?<br><br><br></div><div>Thanks for inputs!<br></div>Cheers,<br><br>Rémi-C<br></div>
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