From: | Allan Kamau <kamauallan(at)gmail(dot)com> |
---|---|
To: | Postgres General Postgres General <pgsql-general(at)postgresql(dot)org> |
Subject: | Avoiding duplicates (or at least marking them as such) in a "cumulative" transaction table. |
Date: | 2010-03-07 08:45:25 |
Message-ID: | ab1ea6541003070045h3b7b4247n8d0d6436e9052838@mail.gmail.com |
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Lists: | pgsql-general |
Hi,
I am looking for an efficient and effective solution to eliminate
duplicates in a continuously updated "cumulative" transaction table
(no deletions are envisioned as all non-redundant records are
important). Below is my situation.
I do have a “central” transaction table (A) that is expected to be
populated many records at a time by several users simultaneously. I
would like to ensure uniqueness in the tuples of this “central”
transaction table.
On average it is expected that approximately 40% to 60% of the batches
of records being presented for persistence to the “central”
transaction table to be already existing in the “central” table and
hence will be duplicates.
This batches will arrive via an insert query from another “central”
transaction table (B) that will also be populated by other data
generating processes. Table B is expected to contain duplicates. Each
client’s records in this table B will share a common value per batch.
I intend to prune out duplicates within each of these batches of
records but this will not guarantee uniqueness of the records across
all the batches.
I have thought of the following ideas, but I would like more advice
and suggestions and inclusions, including possibilities of using
triggers and so on.
1)For each population of a batch of records from a client, perform a
join of the the entire table A right join table B on … WHERE A.id IS
NULL.
Cons: I think it is likely for more than one data insert transactions
running at the same time which may result in the transactions not
seeing the updates the other(s) are performing and hence not be aware
of potential duplicates. Maybe too expensive to perform a join for
each batch insert query?
2) Simply write the records of each batch into this table then detect
duplicates later (may be at some set time intervals or may be a the
end of the clients run) by using count() like this:
UPDATE table_a b
SET is_redundant=TRUE
FROM
(
SELECT
min(b.id)AS id___b
,potentially_redundant_field
FROM
table_a b
GROUP BY
potentially_redundant_field
HAVING
count(*)>1
)a
WHERE
b.potentially_redundant_field=a.potentially_redundant_field
AND b.id>a.id___b
;
3)A combination of option 1 (if it is not too expensive to perform a
join for each batch insert query) and option 2. Assuming many of the
records of table_a will already be in memory and so will the incoming
batch of records meant for inclusion into table_a, performing a right
join may probably not be expensive and will result in less records for
table_a (as the potential duplicates to the previously fully persisted
records will have been hived-off). This will mean few records for
option 2 to process.
Allan.
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