From: | Richard Guo <guofenglinux(at)gmail(dot)com> |
---|---|
To: | David Rowley <dgrowleyml(at)gmail(dot)com> |
Cc: | Andy Fan <zhihui(dot)fan1213(at)gmail(dot)com>, PostgreSQL-development <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: Support run-time partition pruning for hash join |
Date: | 2023-08-24 09:27:21 |
Message-ID: | CAMbWs49+p6hBxXJHFiSwOtPCSkAHwhJj3hTpCR_pmMiUUVLZ1Q@mail.gmail.com |
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Lists: | pgsql-hackers |
On Tue, Aug 22, 2023 at 2:38 PM David Rowley <dgrowleyml(at)gmail(dot)com> wrote:
> It would be good to see some performance comparisons of the worst case
> to see how much overhead the pruning code adds to Hash Join. It may
> well be that we need to consider two Hash Join paths, one with and one
> without run-time pruning. It's pretty difficult to meaningfully cost,
> as I already mentioned, however.
I performed some performance comparisons of the worst case with two
tables as below:
1. The partitioned table has 1000 children, and 100,000 tuples in total.
2. The other table is designed that
a) its tuples occupy every partition of the partitioned table so
that no partitions can be pruned during execution,
b) tuples belong to the same partition are placed together so that
we need to scan all its tuples before we could know that no
pruning would happen and we could stop trying to prune,
c) the tuples are unique on the hash key so as to minimize the cost
of hash probe, so that we can highlight the impact of the pruning
codes.
Here is the execution time (ms) I get with different sizes of the other
table.
tuples unpatched patched
10000 45.74 53.46 (+0.17)
20000 54.48 70.18 (+0.29)
30000 62.57 85.18 (+0.36)
40000 69.14 99.19 (+0.43)
50000 76.46 111.09 (+0.45)
60000 82.68 126.37 (+0.53)
70000 92.69 137.89 (+0.49)
80000 94.49 151.46 (+0.60)
90000 101.53 164.93 (+0.62)
100000 107.22 178.44 (+0.66)
So the overhead the pruning code adds to Hash Join is too large to be
accepted :(. I think we need to solve this problem first before we can
make this new partition pruning mechanism some useful in practice, but
how? Some thoughts currently in my mind include
1) we try our best to estimate the cost of this partition pruning when
creating hash join paths, and decide based on the cost whether to use it
or not. But this does not seem to be an easy task.
2) we use some heuristics when executing hash join, such as when we
notice that a $threshold percentage of the partitions must be visited
we just abort the pruning and assume that no partitions can be pruned.
Any thoughts or comments?
Thanks
Richard
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