That timing seems much slower than I recall.

 

FWIW expression based mapalgebra as I recall is slower than using the call back 
function approach.  So you could try wrapping your CASE in a call back function.

 

However I think something else might be going on here and postgres might be 
repeating work.  I forgot under what conditions it decides to reevaluate a 
function call, I just remember being really surprised by it.

 

To avoid that, you can try using a CTE, also you don't need that ST_Union call 
which for larger number of rasters is expensive, and you might even generate a 
raster that is too big to compute.

 

I'm also guessing your rasts are all tiled the same, so you really don't need 
ST_Intersects, just use the same box operator

 

So try this:

 

WITH  foo AS (

  SELECT ST_SummaryStats( ST_MapAlgebra(deposition.rast, concentrated.rast, 
'CASE WHEN [rast2] > 0.0 THEN [rast1] ELSE NULL END' ) ) As st

            FROM mymodel.deposition INNER JOIN mymodel.concentrated ON ( 
deposition.rast  ~=  concentrated.rast )

            WHERE deposition.rid=1

 

)

SELECT SUM( (st).sum )

FROM foo;

 

 

Hope that helps,

Regina

http://www.postgis.us

http://postgis.net

 

 

From: postgis-users [mailto:[email protected]] On Behalf Of 
Darrel Maddy
Sent: Wednesday, November 25, 2015 5:06 PM
To: PostGIS Users Discussion <[email protected]>; Brent Wood 
<[email protected]>
Subject: Re: [postgis-users] Help with SQL query?

 

Dear Brent,

 

I must confess that my attempts to do this are so far proving very unsuccessful

 

If  I run the following query:

 

SELECT  (ST_SummaryStats(ST_Union(rast))).sum AS sum

FROM  (SELECT ST_MapAlgebra(deposition.rast, concentrated.rast, 'CASE WHEN 
[rast2] > 0.0 THEN [rast1] ELSE NULL END' ) As rast

            FROM mymodel.deposition, mymodel.concentrated

            WHERE ST_Intersects(deposition.rast, concentrated.rast) AND 
deposition.rid=1 ) foo ;

 

It takes around 30 seconds to complete as I assume it is only looking at one 
tile(they are 256x256 pixels) i.e. rid 1. It is not easy to check the sum – for 
that I need one complete raster.

 

For the record this was marginally faster than

SELECT (ST_SummaryStats(ST_Union(rast))).sum AS sum

FROM (SELECT ST_MapAlgebra(deposition.rast, concentrated.rast, 'CASE WHEN 
[rast2] > 0.0 THEN [rast1] ELSE NULL END' ) As rast

            FROM mymodel.deposition, mymodel.concentrated

            WHERE mymodel.deposition.filename='10_depo.tif' AND 
ST_UpperleftX(mymodel.deposition.rast) = 
ST_UpperleftX(mymodel.concentrated.rast) AND 

                         ST_UpperleftY(mymodel.deposition.rast) = 
ST_UpperleftY(mymodel.deposition.rast) ) foo ;

Even after I built indexes for the clauses after the WHERE.

 

Now there are 144 tiles in each of the rasters I want to perform this operation 
on.  Logic would therefore suggest this should take ~4500s

 

However when I perform the following query

 

SELECT  (ST_SummaryStats(ST_Union(rast))).sum AS sum

FROM  (SELECT ST_MapAlgebra(deposition.rast, concentrated.rast, 'CASE WHEN 
[rast2] > 0.0 THEN [rast1] ELSE NULL END' ) As rast

            FROM mymodel.deposition, mymodel.concentrated

            WHERE ST_Intersects(deposition.rast, concentrated.rast) AND 
deposition.filename='10_depo.tif' ) foo ;

 

The query is still running after 18000s!  I must therefore assume I have done 
something wrong but as you may have guessed the answer eludes me.

 

Any further suggestions would be welcome but I will continue to try and find a 
solution as I have 135 rasters to perform this operations on now and 
potentially many thousands more in the future.

 

Darrel

 

.

 

I

 

 

 

 

 

From: postgis-users [mailto:[email protected]] On Behalf Of 
Darrel Maddy
Sent: 24 November 2015 19:52
To: Brent Wood <[email protected] <mailto:[email protected]> >; 
[email protected] <mailto:[email protected]> 
Subject: Re: [postgis-users] Help with SQL query?

 

Dear Brent,

 

Many thanks. The data are tiled (256x256) hence the large number of rows from 
the original 135 tifs. I did not build any indexes however, so I will do some 
reading and see how best to approach that (the threads you listed look useful 
so thanks for that).

 

I will run some additional mini queries limited to just one comparison and 
check using QGIS as you suggest – I probably should have done that first!

 

My workstation has 64GB Ram and I would be surprised if it was significantly 
caching to disk. I also have a hexacore intel extreme processor so I would not 
expect this to be hardware limited. I must confess I expected it to finish 
within a couple of hours.

 

Anyhow very many thanks. I will continue to explore and report back hopefully 
with positive news.

 

Darrel

 

 

From: Brent Wood [mailto:[email protected]] 
Sent: 24 November, 2015 7:36 PM
To: Darrel Maddy <[email protected] 
<mailto:[email protected]> >; [email protected] 
<mailto:[email protected]> 
Subject: Re: [postgis-users] Help with SQL query?

 

Indexing can improve performance by 100s of x, without them things can be slow. 
Also, did you tile the images when you imported them? If not, then each 
iteration is working through all the pixels in the image, rather than a small 
subset. Essentially with tiles, you have a deep (long) table rather than a wide 
one. RDBMSs work better with lots of small records than a few wide ones, 
especially when indexes are used.

 

This might help:

http://gis.stackexchange.com/questions/43053/how-to-speed-up-queries-for-raster-databases

 

and see the raster tutorial they mention for the SRTM data, as to how that is 
loaded into Postgis:

https://trac.osgeo.org/postgis/wiki/WKTRasterTutorial01

 

To test the logic (the syntax is correct or it wouldn't be working) you could 
add to the "where" clause an extra filter so that only a small subset of the 
entire dataset is included (like just one QGIS operation) then compare this 
with the QGIS result.

 

That would be much faster that testing on the entire dataset. Once you know it 
is correct for the test case(s), then you can run it on the complete set.

 

Note that some queries can build up large in-memory objects, so make sure your 
system is not swapping to disk, as that will also slow things down (hugely).

 

Cheers

 

Brent

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