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Type:
New Feature
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Resolution: Won't Fix
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Priority:
Minor - P4
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None
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Affects Version/s: None
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Component/s: Diagnostics
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None
SERVER-7593 adds the (experimental) administrative command pagesInRAM.
The command is helpful but can be misleading if one is interested in how many documents of a collection are in memory (cached).
Example of pagesInRAM()
Given collection with "nrecords" : 155219, "deletedCount" : 80617.
Run a query to page-in all documents (they need to fit in RAM):
db.coll.find({doesnexist:1})
The output of db.coll.getPagesInRAM() is the following:
0 size [=================================== ] 50.00% 1 size [========= ] 12.50% 2 size [==================== ] 28.13% 3 size [===== ] 6.25% 4 size [===== ] 6.25% 5 size [= ] 0.78% 6 size [= ] 0.04% 7 size [= ] 0.54% 8 size [= ] 0.03% 9 size [=========================== ] 37.15% 10 size [======================================================================] 100.00% 11 size [======================================================================] 100.00% 12 size [======================================================================] 100.00% 13 size [================================ ] 44.33%
Still, all documents are in memory although the output might be interpreted differently.
Deleted documents need not be in RAM in order to cache all documents that are alive.
documentsInRAM()
I propose to add a subcommand documentsInRAM, that doesn't scan extents, but uses the id index to scan through all non-deleted documents and check if they are in memory. Furthermore, the command can output an estimate of memory fragmentation caused by the page-structure of virtual memory.
Example of documentsInRAM()
> db.coll.documentsInRAM()
{
"inMem" : 1,
"nscanned" : 155219,
"netBytesInRAM" : 95626152,
"pageBytesInRAM" : 98111488,
"memFragmentation" : 0.02533175319897296,
"ok" : 1
}
All documents are fully in memory ("inMem" : 1.0). The memory fragmentation is only about 2.5% since the overhead caused by virtual memory paging (pageBytesInRAM - netBytesInRAM) is low in this case.
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