Writing geoprocessing outputs to memory is another to writing output to a geodatabase or file-based format. It is usually significantly sooner than writing to on-disk formats. Information written to memory is temporary and is deleted when the applying is closed. The memory workspace is a perfect location to write down intermediate information in a ModelBuilder model or Python script. ArcGIS gives two memory-primarily based workspaces where geoprocessing outputs could be written. Memory-based mostly workspaces don't help geodatabase components similar to feature datasets, representations, topologies, geometric networks, or community datasets. Since memory-based mostly workspaces are saved in your system's physical memory, or Memory Wave RAM, your system might run low on memory when writing massive datasets into the workspace. This will negatively impression processing performance. Folders cannot be created in memory-primarily based workspaces. The memory workspace is a memory-based mostly workspace that supports output feature lessons, tables, and raster datasets. You can add memory datasets to a map in ArcGIS Pro. ArcMap that supports output characteristic courses, tables, and raster datasets. The tool then adds the output from the mission geodatabase to the map. To show memory-primarily based knowledge in a map, use the memory workspace as an alternative. When utilizing a memory-based workspace, any intermediate data must be deleted as soon as possible to free up system memory resources. The Delete instrument can be utilized to delete information in a Memory Wave Routine-based mostly workspace. Delete individual datasets, or your entire workspace to clear the workspace contents. Use of memory-based mostly workspaces in Python is simply valid for Memory Wave Routine geoprocessing instruments. Memory will not be a common-purpose virtual listing the place files or different information can be written.

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