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<HR><H2>[COLD] Performance notes</H2>
<H3>daemon@ATHENA.MIT.EDU (Wed Dec  4 06:35:36 1996
)</H3>
<PRE>
Date: Wed, 4 Dec 1996 12:27:21 +0100
From: silovic@srce.hr (Miroslav Silovic)
To: coldstuff@cold.org


I thought to send some notes on the driver performance here. At least I
hope this will help you write more efficient code.

1) @ operator

	foo = [@foo, bar]

copies foo on the stack, appends bar, then copies the whole think into
a new list. On the other hand,

	foo += [bar]

will copy the list at most once (I need to look into the driver, I *hope*
it will not copy even once in most cases. If it does, it will be fixed).

Same way, foo = [@foo, @bar] should be replaced with foo += bar. 
I thought of only 2-3 rare cases where @ does make sense.

2) functions and native methods

	foo = foo.replace(5,bar)

actually overwrites foo unless something else references the contents
of foo. Similarily,

	dict = dict.add(key, val)

overwrites the dict if nothing else is using it. However,

	dict = dict.add(key, val).add(key, val)

will always copy the dict. The reason for this is that if a native
call or function call is followed by assignment, some natives will
overwrite the variable as soon as they're sure that there will be
no throw from the function. This way, one of the references (from
the argument stack and the variable) is cleared. The new function,
anticipate_assignment(), implements this in driver. But be careful
when using it, because if your method throws, a_a will cause the
assigned variable to be zeroed (it's allright if you expect it to
happen, though). In the last case, the first .add is followed by .add,
not assignment, so the driver doesn't know that everything will go
okay. Therefore, it much leave both refs, and dict gets copied.

3) natives vs functions

Every native method call has to do full method lookup. It takes
about 3x longer to execute a native than a function. So, be
careful with them in tight loops.

4) .eval()

Some admins might be tempted to abuse $root.eval. Note that it will
totally kill the server performance. First, compiler is not fast.
Second, method lookups are complex (because of MI), and each
.eval modifies the class hierarchy (since it adds and dels a method).
Method lookups are cached for speed, and the cache has very good
hit rate. Unfortunately, each class modification negates the cache,
so the method lookups after each modification take ages to execute.

5) cache configuration

Simply use depth 20-30 (that's the good range for it), and width so
that it can hold all the objects you might need together. Depth is
the parameter that affects performance, 20-30 is a good choice (IMO).


Hmm, have I forgotten anything? :) I might send more posts like these
in the future.


	Miro





</PRE>
