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= Results =
== Memory usage ==
[[Image:jorendorff-dht-figure-1.png]]
This means that for a huge Map with no delete operations, a Close table could use more virtual memory but less physical memory than its open addressing counterparts. This will not be the only use case that stresses memory usage, though. Applications may also create many small tables and may delete entries from large tables.
== Insertion speed ==
[[Image:jorendorff-dht-InsertSmallTest-speed.png]]
The jagged shape of this graph is robust. It reflects the fact that the table doubles in size as it grows, and rehashing is a significant part of the expense of populating a huge table.
== Lookup speed ==
[[Image:jorendorff-dht-LookupHitTest-speed.png]]
DenseTable is only slightly slower for misses, perhaps because more lookups have zero collisions. (?)
== Deletion speed ==
[[Image:jorendorff-dht-WorklistTest-speed.png]]
This test creates a table with 700 entries, then measures the speed of alternately adding an entry and deleting the oldest remaining entry from the table. Entries are therefore removed in FIFO order. Each "operation" here includes both an insert and a delete.
[[Image:jorendorff-dht-DeleteTest-speed.png]]
This test measures the speed of deleting all entries from a very large table.
[[Image:jorendorff-dht-LookupAfterDeleteTest-speed.png]]
This test measures the performance of lookups, mostly misses, in a table that was filled to size 50000, then reduced to size 195 by deleting most of the entries.
