Gregory Stark wrote:
Simon Riggs <si...@2ndquadrant.com> writes:
The amount of I/O could stay the same, just sample all rows on block. [....]
It will also introduce strange biases. For instance in a clustered table it'll
think there are a lot more duplicates than there really are because it'll see
lots of similar values.
But for ndistinct - it seems it could only help things. If the
ndistinct guesser just picks
max(the-current-one-row-per-block-guess,
a-guess-based-on-all-the-rows-on-the-blocks)
it seems we'd be no worse off for clustered tables; and much
better off for randomly organized tables.
In some ways I fear *not* sampling all rows on the block also
introduces strange biases by largely overlooking the fact that
the table's clustered.
In my tables clustered on zip-code we don't notice info like
"state='AZ' is present in well under 1% of blocks in the table",
while if we did scan all rows on the blocks it might guess this.
But I guess a histogram of blocks would be additional stat rather
than an improved one.
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