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<div>I just did some hand-wavy math on that:</div>
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<div>>>> import random</div>
<div>>>> r=random.Random()</div>
<div>>>> import sets</div>
<div>>>> s=sets.Set([r.randint(1, 10000000) for x in range(30000)])</div>
<div>>>> len(s)</div>
<div>29950</div>
<div>>>> len(','.join([str(i) for i in s]))</div>
<div>236301</div>
<div>>>> import zlib</div>
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<div>>>> compressed=zlib.compress(','.join([str(i) for i in s]), 9)</div>
<div>>>> len(compressed)</div>
<div>109568</div><br> </div></div>
<div><span style="WHITE-SPACE: pre"></span>So, a user with about 30k friends with numeric IDs fairly even distributed from 1 to 10,000,000 (my average ID was 4,979,961, min was 236, max was 9,999,931) would take a little over 100k of cache when comma separated and compressed.
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<div><span style="WHITE-SPACE: pre"></span>I would expect the normal case to be much smaller.</div></div></blockquote>
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<div>Great analysis!</div>
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<div>Thinking further on this issue though, gives me more questions...</div>
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<div>Storing a list of a user's friends in a Memcache array, then getting them back in and searching through them... while it avoids the database altogether, wouldn't it be sorta slow? For instance, every time a user visits user B's profile page, the system would need to iterate through this array and see if they are connected.
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<div> </div>In this case would it be just better to have a heap mysql database and query that instead?<br> </div>