R – How to improve performance and memory usage with a large number of polygons on a canvas

Here's some advice from someone with an environment where we have folders containing tens of millions of files.

1. A folder stores the index information (links to child files & child folder) in an index file. This file will get very large when you have a lot of children. Note that it doesn't distinguish between a child that's a folder and a child that's a file. The only difference really is the content of that child is either the child's folder index or the child's file data. Note: I am simplifying this somewhat but this gets the point across.
2. The index file will get fragmented. When it gets too fragmented, you will be unable to add files to that folder. This is because there is a limit on the # of fragments that's allowed. It's by design. I've confirmed it with Microsoft in a support incident call. So although the theoretical limit to the number of files that you can have in a folder is several billions, good luck when you start hitting tens of million of files as you will hit the fragmentation limitation first.
3. It's not all bad however. You can use the tool: contig.exe to defragment this index. It will not reduce the size of the index (which can reach up to several Gigs for tens of million of files) but you can reduce the # of fragments. Note: The Disk Defragment tool will NOT defrag the folder's index. It will defrag file data. Only the contig.exe tool will defrag the index. FYI: You can also use that to defrag an individual file's data.
4. If you DO defrag, don't wait until you hit the max # of fragment limit. I have a folder where I cannot defrag because I've waited until it's too late. My next test is to try to move some files out of that folder into another folder to see if I could defrag it then. If this fails, then what I would have to do is 1) create a new folder. 2) move a batch of files to the new folder. 3) defrag the new folder. repeat #2 & #3 until this is done and then 4) remove the old folder and rename the new folder to match the old.

To answer your question more directly: If you're looking at 100K entries, no worries. Go knock yourself out. If you're looking at tens of millions of entries, then either:

a) Make plans to sub-divide them into sub-folders (e.g., lets say you have 100M files. It's better to store them in 1000 folders so that you only have 100,000 files per folder than to store them into 1 big folder. This will create 1000 folder indices instead of a single big one that's more likely to hit the max # of fragments limit or

b) Make plans to run contig.exe on a regular basis to keep your big folder's index defragmented.

Read below only if you're bored.

The actual limit isn't on the # of fragment, but on the number of records of the data segment that stores the pointers to the fragment.

So what you have is a data segment that stores pointers to the fragments of the directory data. The directory data stores information about the sub-directories & sub-files that the directory supposedly stored. Actually, a directory doesn't "store" anything. It's just a tracking and presentation feature that presents the illusion of hierarchy to the user since the storage medium itself is linear.

Clearly the machine code the JIT compiler can generate for the first case is much more efficient. One rule that really helps there is that an object can only be unboxed to a variable that has the same type as the boxed value. That allows the JIT compiler to generate very efficient code, no value conversions have to be considered.

The is operator test is easy, just check if the object isn't null and is of the expected type, takes but a few machine code instructions. The cast is also easy, the JIT compiler knows the location of the value bits in the object and uses them directly. No copying or conversion occurs, all machine code is inline and takes but about a dozen instructions. This needed to be really efficient back in .NET 1.0 when boxing was common.

Casting to int? takes a lot more work. The value representation of the boxed integer is not compatible with the memory layout of Nullable<int>. A conversion is required and the code is tricky due to possible boxed enum types. The JIT compiler generates a call to a CLR helper function named JIT_Unbox_Nullable to get the job done. This is a general purpose function for any value type, lots of code there to check types. And the value is copied. Hard to estimate the cost since this code is locked up inside mscorwks.dll, but hundreds of machine code instructions is likely.

The Linq OfType() extension method also uses the is operator and the cast. This is however a cast to a generic type. The JIT compiler generates a call to a helper function, JIT_Unbox() that can perform a cast to an arbitrary value type. I don't have a great explanation why it is as slow as the cast to Nullable<int>, given that less work ought to be necessary. I suspect that ngen.exe might cause trouble here.