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Arcpy multiprocessing arcpy.Select_analysis


Why Can't ArcPy Search the Newly Created FeatureArcGIS Copy Features tool extremely slow when exporting to ArcSDE?Multiprocessing issues with ArcPySetting ArcPy environment variables with Python multiprocessing?Arcpy and multiprocessing not workingBatch intersect and multiprocessing with arcpyCombining python (parallel) multiprocessing toolbox with arcpyAccessing differing geodatabase schemas from arcpyarcpy and multiprocessing: switch workflow to shapefiles to avoid schemalocksMultiprocessing GALayerToRasters













1















I have the following script:



import arcpy
from arcpy import env
import datetime
import os


env.workspace = r"Q:\SDEDirect Connection to Contours.sde"
dataFC = arcpy.ListFeatureClasses("","","Contours")
outpath = r'C:UsersTESTDesktopSDE Conversion ProjectTEST.gdb'
query = "objectid > 0 AND objectid <= 200000 "

for fc in dataFC:
if fc == 'Contours':
output = outpath + os.sep + fc
arcpy.Select_analysis(fc, output+'200k', query)


Currently it selects records that have objectid between 0 and 200,000 and creates a feature class called Contours 200k in the TEST gdb.



What I want to be able to do is make a multiprocessing script that utilises one core to calculated between object id 0 and 200k, another that calculates betweek 200,001 and 400k and so on until the whole feature class is copied over as separate feature sets to the TEST gdb.



How would I go about doing that?
I'm trying to do this since the bottleneck of copying from the sde is the network connection and testing with separate files where I had the ranges set manually improved the overall speed a lot.










share|improve this question









New contributor




Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.















  • 1





    ArcGIS desktop is a single thread application, you can use subprocess.Popen to call multiple scripts but you will run into a self locking situation as only one process can write to a geodatabase at a time, you could create a GDB in your os.environ.get('TEMP') for each process and write there then use append or merge to join the multiple databases together though I would think that this would be no quicker in the long run... select by location on the other hand could be split up like this to gain better performance.

    – Michael Stimson
    2 days ago











  • I wrote a short blog providing a template over on geonet, suggest you read that to understand how to implement multiprocessing in arcpy. There are also many other related threads on geonet you should explore.

    – Hornbydd
    2 days ago











  • This has the feel of an XY Problem. The best way to improve contour line performance is to intersect with a coarse fishnet and dissolve on fishnet_fid (or FID plus elevation). This reduces the extent of individual features to the point that the spatial index is useful and reduces the feature count so that it is performant. Multi-threading is not generally a solution to a networking bottleneck.

    – Vince
    2 days ago















1















I have the following script:



import arcpy
from arcpy import env
import datetime
import os


env.workspace = r"Q:\SDEDirect Connection to Contours.sde"
dataFC = arcpy.ListFeatureClasses("","","Contours")
outpath = r'C:UsersTESTDesktopSDE Conversion ProjectTEST.gdb'
query = "objectid > 0 AND objectid <= 200000 "

for fc in dataFC:
if fc == 'Contours':
output = outpath + os.sep + fc
arcpy.Select_analysis(fc, output+'200k', query)


Currently it selects records that have objectid between 0 and 200,000 and creates a feature class called Contours 200k in the TEST gdb.



What I want to be able to do is make a multiprocessing script that utilises one core to calculated between object id 0 and 200k, another that calculates betweek 200,001 and 400k and so on until the whole feature class is copied over as separate feature sets to the TEST gdb.



How would I go about doing that?
I'm trying to do this since the bottleneck of copying from the sde is the network connection and testing with separate files where I had the ranges set manually improved the overall speed a lot.










share|improve this question









New contributor




Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.















  • 1





    ArcGIS desktop is a single thread application, you can use subprocess.Popen to call multiple scripts but you will run into a self locking situation as only one process can write to a geodatabase at a time, you could create a GDB in your os.environ.get('TEMP') for each process and write there then use append or merge to join the multiple databases together though I would think that this would be no quicker in the long run... select by location on the other hand could be split up like this to gain better performance.

    – Michael Stimson
    2 days ago











  • I wrote a short blog providing a template over on geonet, suggest you read that to understand how to implement multiprocessing in arcpy. There are also many other related threads on geonet you should explore.

    – Hornbydd
    2 days ago











  • This has the feel of an XY Problem. The best way to improve contour line performance is to intersect with a coarse fishnet and dissolve on fishnet_fid (or FID plus elevation). This reduces the extent of individual features to the point that the spatial index is useful and reduces the feature count so that it is performant. Multi-threading is not generally a solution to a networking bottleneck.

    – Vince
    2 days ago













1












1








1








I have the following script:



import arcpy
from arcpy import env
import datetime
import os


env.workspace = r"Q:\SDEDirect Connection to Contours.sde"
dataFC = arcpy.ListFeatureClasses("","","Contours")
outpath = r'C:UsersTESTDesktopSDE Conversion ProjectTEST.gdb'
query = "objectid > 0 AND objectid <= 200000 "

for fc in dataFC:
if fc == 'Contours':
output = outpath + os.sep + fc
arcpy.Select_analysis(fc, output+'200k', query)


Currently it selects records that have objectid between 0 and 200,000 and creates a feature class called Contours 200k in the TEST gdb.



What I want to be able to do is make a multiprocessing script that utilises one core to calculated between object id 0 and 200k, another that calculates betweek 200,001 and 400k and so on until the whole feature class is copied over as separate feature sets to the TEST gdb.



How would I go about doing that?
I'm trying to do this since the bottleneck of copying from the sde is the network connection and testing with separate files where I had the ranges set manually improved the overall speed a lot.










share|improve this question









New contributor




Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.












I have the following script:



import arcpy
from arcpy import env
import datetime
import os


env.workspace = r"Q:\SDEDirect Connection to Contours.sde"
dataFC = arcpy.ListFeatureClasses("","","Contours")
outpath = r'C:UsersTESTDesktopSDE Conversion ProjectTEST.gdb'
query = "objectid > 0 AND objectid <= 200000 "

for fc in dataFC:
if fc == 'Contours':
output = outpath + os.sep + fc
arcpy.Select_analysis(fc, output+'200k', query)


Currently it selects records that have objectid between 0 and 200,000 and creates a feature class called Contours 200k in the TEST gdb.



What I want to be able to do is make a multiprocessing script that utilises one core to calculated between object id 0 and 200k, another that calculates betweek 200,001 and 400k and so on until the whole feature class is copied over as separate feature sets to the TEST gdb.



How would I go about doing that?
I'm trying to do this since the bottleneck of copying from the sde is the network connection and testing with separate files where I had the ranges set manually improved the overall speed a lot.







arcpy select parallel-processing






share|improve this question









New contributor




Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|improve this question









New contributor




Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|improve this question




share|improve this question








edited 2 days ago









PolyGeo

53.9k1781245




53.9k1781245






New contributor




Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









asked 2 days ago









AndyAndy

141




141




New contributor




Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.





New contributor





Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






Andy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







  • 1





    ArcGIS desktop is a single thread application, you can use subprocess.Popen to call multiple scripts but you will run into a self locking situation as only one process can write to a geodatabase at a time, you could create a GDB in your os.environ.get('TEMP') for each process and write there then use append or merge to join the multiple databases together though I would think that this would be no quicker in the long run... select by location on the other hand could be split up like this to gain better performance.

    – Michael Stimson
    2 days ago











  • I wrote a short blog providing a template over on geonet, suggest you read that to understand how to implement multiprocessing in arcpy. There are also many other related threads on geonet you should explore.

    – Hornbydd
    2 days ago











  • This has the feel of an XY Problem. The best way to improve contour line performance is to intersect with a coarse fishnet and dissolve on fishnet_fid (or FID plus elevation). This reduces the extent of individual features to the point that the spatial index is useful and reduces the feature count so that it is performant. Multi-threading is not generally a solution to a networking bottleneck.

    – Vince
    2 days ago












  • 1





    ArcGIS desktop is a single thread application, you can use subprocess.Popen to call multiple scripts but you will run into a self locking situation as only one process can write to a geodatabase at a time, you could create a GDB in your os.environ.get('TEMP') for each process and write there then use append or merge to join the multiple databases together though I would think that this would be no quicker in the long run... select by location on the other hand could be split up like this to gain better performance.

    – Michael Stimson
    2 days ago











  • I wrote a short blog providing a template over on geonet, suggest you read that to understand how to implement multiprocessing in arcpy. There are also many other related threads on geonet you should explore.

    – Hornbydd
    2 days ago











  • This has the feel of an XY Problem. The best way to improve contour line performance is to intersect with a coarse fishnet and dissolve on fishnet_fid (or FID plus elevation). This reduces the extent of individual features to the point that the spatial index is useful and reduces the feature count so that it is performant. Multi-threading is not generally a solution to a networking bottleneck.

    – Vince
    2 days ago







1




1





ArcGIS desktop is a single thread application, you can use subprocess.Popen to call multiple scripts but you will run into a self locking situation as only one process can write to a geodatabase at a time, you could create a GDB in your os.environ.get('TEMP') for each process and write there then use append or merge to join the multiple databases together though I would think that this would be no quicker in the long run... select by location on the other hand could be split up like this to gain better performance.

– Michael Stimson
2 days ago





ArcGIS desktop is a single thread application, you can use subprocess.Popen to call multiple scripts but you will run into a self locking situation as only one process can write to a geodatabase at a time, you could create a GDB in your os.environ.get('TEMP') for each process and write there then use append or merge to join the multiple databases together though I would think that this would be no quicker in the long run... select by location on the other hand could be split up like this to gain better performance.

– Michael Stimson
2 days ago













I wrote a short blog providing a template over on geonet, suggest you read that to understand how to implement multiprocessing in arcpy. There are also many other related threads on geonet you should explore.

– Hornbydd
2 days ago





I wrote a short blog providing a template over on geonet, suggest you read that to understand how to implement multiprocessing in arcpy. There are also many other related threads on geonet you should explore.

– Hornbydd
2 days ago













This has the feel of an XY Problem. The best way to improve contour line performance is to intersect with a coarse fishnet and dissolve on fishnet_fid (or FID plus elevation). This reduces the extent of individual features to the point that the spatial index is useful and reduces the feature count so that it is performant. Multi-threading is not generally a solution to a networking bottleneck.

– Vince
2 days ago





This has the feel of an XY Problem. The best way to improve contour line performance is to intersect with a coarse fishnet and dissolve on fishnet_fid (or FID plus elevation). This reduces the extent of individual features to the point that the spatial index is useful and reduces the feature count so that it is performant. Multi-threading is not generally a solution to a networking bottleneck.

– Vince
2 days ago










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