I was wondering if anyone else in the community here has attempted to use multi-processing for spatial analyses. Namely I am trying to iterate through a series of rasters, create a multiprocessing job for each and run them through a number of geoprocessing steps within one def function. Something along the lines of
def net(RasterImage, OutFolderDir): arcpy.env.overwriteOutput = True arcpy.env.workspace = OutFolderDir DEM_Prj = DEM_Prj.tif try: arcpy.ProjectRaster_management(RasterImage, DEM_Prj.... FocalStatistics(DEM_prj....) ... if __name__ == '__main__': InputFolder = r'C:\test\somepath' Output = r'C:\test\somepath2' arcpy.env.workspace = InputFolder arcpy.env.scratchWorkspace = r'C:\test.gdb' fcs = arcpy.ListRasters('*') pool = multiprocessing.Pool(4) jobs =  for fc in fcs: rIn = os.path.join(InputFolder,fc) rOut = os.path.join(Output,fc[:-4]) jobs.append(pool.apply_async(net,(rIn, rOut)))
Now the multiprocessing does run, usually for the first batch! However, I keep running into several different errors when attempting several datasets(more than 4 files - i.e. 4 core multiprocessing) including:
ERROR 010302: Unable to create the output raster: C:\somepath\sr6f8~1\FocalSt_srtm1 ERROR 010067: Error in executing grid expression. Failed to execute (FocalStatistics).
ERROR 999999: Error executing function. Failed to copy raster dataset Failed to execute (ProjectRaster)
Notice in the first error the strange folder that is created (in the OutFolderDir location) associated with the focal statistics that nearly creates an exact replica of the final output.
My question is based off your experience is it impossible to create several step geoprocessing within one multiprocessing function? Or do I need to tile these steps into their individual geoprocessing steps?
Kind Regards, Bjorn
Still encoutering similar errors - moving the import functions to the def function has shown that
import arcpy from arcpy.sa import *
cannot create an output with an added syntax warning that of import * is not allowed.
I know this is a late reply but I thought it might benefit someone else for future reference to my workaround that allows multiprocessing to work with arcpy. The main problem I found after returning to this problem is not the competition of the arcpy modules but rather competition over the scratchWorkspace that the ArcObjects utilize to save the temporary files. Therefore consider running a counter into the multiprocessing parsing argument to make a unique scratchWorkspace for each process i.e.
Counter = 0 for fc in fcs: rIn = os.path.join(InputFolder,fc) rOut = os.path.join(Output,fc[:-4]) jobs.append(pool.apply_async(net,(rIn, rOut,Counter))) Counter += 1
Then in the main function make a specific temporary directory and assign an unique scratchWorkspace to each multiprocessing task.
def main(RasterImage,OutFolderDir,Counter) TempFolder = os.path.join(os.path.dirname(OutFolderDir),'Temp_%s'% (Counter)) os.mkdir(TempFolder) arcpy.scratchWorkspace = TempFolder ...
Hope that helps and thanks to Ragi for the inital suggestion to use separate temp workspaces - still baffled by why it originally did not work.