This article describes how to use Displayr's memory profiler to show the estimated server memory usage of the connected Displayr document.
This is useful to identify and address inefficiencies in your Displayr document. This can help optimize your document's performance. For more information on optimizing the speed of your Displayr documents, see here.
Requirements
A Displayr document
Method
From an open Displayr document, click the small arrow next to the document name and select Memory Profiling.
This will open a new tab in your browser. You may notice any of the following categories present in the memory profiler:
- Non-profiled memory - The profiler does not try to capture every object in the running process. It samples the objects we know to be large. The non-profiled memory represents objects not sampled and also reserved memory of the .NET runtime.
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Transform manager - This is the place where certain R-related cache results are stored. Examples include R data sets and variables.
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Data sets
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R grids
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R items
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Images
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Tables
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All analysis base derived items other than the 4 immediately above.
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Subscriptions - This mainly represents the size of cache that server keeps in response to network requests by the client.
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QPack stream
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Document XML - This is the size of the
.Q
file if it is loaded in memory. -
Project history (not the undo stack).
What you might be able to do about the above categories?
You can use the Memory Usage Profile to diagnose which aspects of the Displayr document are using large amounts of server memory and reduce them by noting the following points.
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A large non-profiled memory may indicate a project has been opened for a long time (so the undo history has built up in memory), in this case closing all tabs related to the project and reopening them after 20 mins may help.
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Transform manager - this indicates large cached R results. You may be able to reduce this by deleting R data sets and variables that are not necessary for your project.
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Subscriptions - this caches all network requests. If there are large objects, R results in particular, they get cached. Optimizing for it will depend on what is large in the project.
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Document XML - not much can be done about this as it keeps track of the structure of the projects.
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