So, if I'm getting this right, you're trying to extract the values from the Lidar Raster (which is 11TeraBytes in size!) at any given point (of which you have a few million)?

 

 

With those data quantities you're going to have to do a *lot* of optimisation.

 

 

You're kind of on the right track, but only just starting.

 

 

Suggestions:

 

1) Your attempt to get a subset of the lidar data is suboptimal. Instead, take the BBoxAccumulator, and then follow with a FeatureReader, setting it to only select features within the bbox. This reduces the data read in the first place, and removes the need for a clipper too, further benefiting.

 

 

2) Use FME 2015; historically Safe are good at ensuring each version is faster than the last, so it may help.

 

 

3) Then it gets a little more tricky. It depends on the distribution of the points and the data structure. If the points are in groups (ideally spatial, but potentially attribute based), I would suggest splitting them up somehow, and using WorkspaceRunner to process the subsets. This can massively speed things up, even if you only run one child process at a time.

 

 

Those should be enough to get you started; but the core is: split the dataset as much as possible and only process small subsets at a time.

 

See how far you get and update here if it's still slow after some more fiddling.

 

 

Cheers,

 

Jonathan

 

 

 

(P.s. Note: I'm not sure you ever needed the "Dissolver" there, as the output for the BBoxAccumulator should be a single box).

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