In my experience, this is only true if you need to partition both sides into three sets:

You can formulate these as three SQL queries:

SELECT left.keycol as onlyleft
FROM left LEFT JOIN right ON left.keycol = right.keycol
WHERE right.keycol IS NULL


SELECT right.keycol as onlyright
FROM right LEFT JOIN left ON left.keycol = right.keycol
WHERE left.keycol IS NULL


SELECT right.keycol as onlyright
FROM right INNER JOIN left ON left.keycol = right.keycol

[download]

But you can get the same results by using a hash and "colliding out" the elements from the hash and then looking what's left over. The SQL approach does not handle duplicate keys well, while the hash-based approach is extended trivially to handle duplicate keys by storing arrayrefs of the rows instead of just using the keys as indicators.

I have to confesss, I've done lots and lots of such comparison programs. I haven't collected together the code into a released framework yet, because there are different business rules for when two rows are to be considered equal/identical, and I haven't found a convenient way to hide that in a framework.

In reply to Re^2: Matching data between huge files by Corion
in thread Matching data between huge files by est

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