My primary purpose was to verify the reliability of OpenJPA's
ConcurrentHashMap implementation. As I got into it, I saw the
opportunity to get some performance metrics out of the test.
The biggest part of my task was coming up with a reliable and
useful
testing framework. I design it with the following two factors in
mind: First, I wanted to test the edge conditions where an
entry had
just been added or removed or where a key's value had just been
updated. The idea is that a number of threads add, remove, and
update
entries, while other threads check to see if these recent
modifications are visible (or in the case of removals, not
visible).
Second, I wanted the testing framework itself to be free of
synchronization. If the testing framework used synchronization
then
it would tend to serialize the readers and writers and thereby
mask
concurrency issues in the map implementation under test.
The testing framework uses a non-synchronizing, non-blocking FIFO
queue as the mechanism for the writing threads to communicate
their
recent modifications to the reading threads.
To prevent writing threads from overwriting recent modifications
before they could be read and verified, the testing framework
walks
the hash map keys in in a linear (or in the case of updates,
circular) order. By using a hash map with a large enough
capacity,
readers have the time to verify the recent modifications
before the
writer threads come back to modify that part of the key space
again.
Using an adapter for the map implementation, the testing
framework
starts five writer threads and ten reader threads at the same
time.
These threads run wide open for 30 seconds, except that the
readers
will give up their time slice if they find nothing on the
queue. The
HashMaps were all sized for the needed capacity upon creation,
so no
resizing occurred during testing.
I got some interesting results.
Four implementations were tested, Java's unsynchronized HashMap
implementation, Java's synchronized HashMap implementation,
Java's
ConcurrentHashMap implementation, and OpenJPA's ConcurrentHashMap
implementation.
Only Java's unsynchronized HashMap failed, as expected, under
test.
Under test, this implementation demonstrates its inability to
handle
concurrency. The other three implementations worked flawlessly
under
test.
The java.util.concurrent.ConcurrentHashMap implementation
(available
with Java 5 and 6) was the fastest implementation tested.
Java's synchronized wrapper for the HashMap implementation is
one to
two orders of magnitude slower than Java's ConcurrentHashMap
implementation.
OpenJPA's ConcurrentHashMap compares equally with Java's
ConcurrentHashMap in find operations and is 2-4 times slower in
mutating operations.
Implementation Add Remove Update Find-a Find-r Find-u
---------------+------+-------+--------+-------+-------+------
synchronized 103 35 50 40 37 54
concurrent 13.2 6.4 6.1 0.6 0.3 1.1
OpenJPA 29.8 26.6 27.9 0.6 0.6 0.6
Legend:
synchronized:
java.util.Collections.synchronizedMap(new java.util.HashMap())
concurrent: java.util.concurrent.ConcurrentHashMap
OpenJPA: org.apache.openjpa.lib.util.concurrent.ConcurrentHashMap
Add: time for average add operation
Remove: time for average remove operation
Update: time for average update of new value for existing key
Find-a: time to find a recent addition
Find-r: time to NOT find a recent removal
Find-u: time to find a recent update
These times (in microseconds) are representative, but are not the
average of several runs. The tests were run on a Dell Dual Core
laptop under Windows. The performance meter was pegged during the
