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I'm looking for any performance tips for mosaicking a large number of rasters.

I already know about parallel processing and don't need any further advice on that aspect (thanks!).

I'm wondering if anything can be gained from using a large number of FME Server Engines or FME Cloud instances and if there's a simple workflow for achieving this. My initial thought is to build my own version of parallel processing and split the mosaicking into several workspaces for submission by the FMEServerJobSubmitter. Anyone got any other ideas?

PS. I'd be particularly interested in hearing from @donatsafe if there's some way of using Docker Swarms or Kubernetes to help with this. :)

 

I have in the past when dealing with mosaicking very large amounts of files, created a child workspace the would mosaic a subset of the data (say 512 files) in either a strip or tile (depending on how the input data was structured), and a parent workspace that would call the child workspace for each subset, and then read in the resultant files and mosaic them.

I have in the past when dealing with mosaicking very large amounts of files, created a child workspace the would mosaic a subset of the data (say 512 files) in either a strip or tile (depending on how the input data was structured), and a parent workspace that would call the child workspace for each subset, and then read in the resultant files and mosaic them.

Thanks @jdh. Given the 512 open file limit, this might be the way to go. The child workspaces would each be sent to different Engines, which would help with performance.

 

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