Hi,
This is my patch, before I forgot to add attachments, and the following address is also discussed.
https://www.postgresql.org/message-id/2017082612390093777512%40highgo.com
---youngHighGo Database: http://www.highgo.com
On 8/28/2017 16:28，Yugo Nagata wrote：
Hi young,
On Mon, 28 Aug 2017 15:33:46 +0800
"yang...@highgo.com" wrote:
> Hello
>
> Looking at your hash partitioning syntax, I implemented a hash partition in a more concise way, with no need to determine the number of sub-tables, and dynamically add partitions.
I think it is great work, but the current consensus about hash-partitioning supports
Amul's patch[1], in which the syntax is different from the my original proposal.
So, you will have to read Amul's patch and make a discussion if you still want to
propose your implementation.
Regards,
[1] https://www.postgresql.org/message-id/CAAJ_b965A2oog=6efuhelexl3rmgfssb3g7lwkva1bw0wuj...@mail.gmail.com
>
> Description
>
> The hash partition's implement is on the basis of the original range / list partition,and using similar syntax.
>
> To create a partitioned table ,use:
>
> CREATE TABLE h (id int) PARTITION BY HASH(id);
>
> The partitioning key supports only one value, and I think the partition key can support multiple values,
> which may be difficult to implement when querying, but it is not impossible.
>
> A partition table can be create as bellow:
>
> CREATE TABLE h1 PARTITION OF h;
> CREATE TABLE h2 PARTITION OF h;
> CREATE TABLE h3 PARTITION OF h;
>
> FOR VALUES clause cannot be used, and the partition bound is calclulated automatically as partition index of single integer value.
>
> An inserted record is stored in a partition whose index equals
> DatumGetUInt32(OidFunctionCall1(lookup_type_cache(key->parttypid[0], TYPECACHE_HASH_PROC)->hash_proc, values[0])) % nparts/* Number of partitions */
> ;
> In the above example, this is DatumGetUInt32(OidFunctionCall1(lookup_type_cache(key->parttypid[0], TYPECACHE_HASH_PROC)->hash_proc, id)) % 3;
>
> postgres=# insert into h select generate_series(1,20);
> INSERT 0 20
> postgres=# select tableoid::regclass,* from h;
> tableoid | id
> --+
> h1 | 3
> h1 | 5
> h1 | 17
> h1 | 19
> h2 | 2
> h2 | 6
> h2 | 7
> h2 | 11
> h2 | 12
> h2 | 14
> h2 | 15
> h2 | 18
> h2 | 20
> h3 | 1
> h3 | 4
> h3 | 8
> h3 | 9
> h3 | 10
> h3 | 13
> h3 | 16
> (20 rows)
>
> The number of partitions here can be dynamically added, and if a new partition is created, the number of partitions changes, the calculated target partitions will change, and the same data is not reasonable in different partitions,So you need to re-calculate the existing data and insert the target partition when you create a new partition.
>
> postgres=# create table h4 partition of h;
> CREATE TABLE
> postgres=# select tableoid::regclass,* from h;
> tableoid | id
> --+
> h1 | 5
> h1 | 17
> h1 | 19
> h1 | 6
> h1 | 12
> h1 | 8
> h1 | 13
> h2 | 11
> h2 | 14
> h3 | 1
> h3 | 9
> h3 | 2
> h3 | 15
> h4 | 3
> h4 | 7
> h4 | 18
> h4 | 20
> h4 | 4
> h4 | 10
> h4 | 16
> (20 rows)
>
> When querying the data, the hash partition uses the same algorithm as the insertion, and filters out the table that does not need to be scanned.
>
> postgres=# explain analyze select * from h where id = 1;
> QUERY PLAN
>
> Append (cost=0.00..41.88 rows=13 width=4) (actual time=0.020..0.023 rows=1 loops=1)
>-> Seq Scan on h3 (cost=0.00..41.88 rows=13 width=4) (actual time=0.013..0.016 rows=1 loops=1)
> Filter: (id = 1)
> Rows Removed by Filter: 3
> Planning time: 0.346 ms
> Execution time: 0.061 ms
> (6 rows)
>
> postgres=# explain analyze select * from h where id in (1,5);;
> QUERY PLAN
>
> Append (cost=0.00..83.75 rows=52 width=4) (actual time=0.016..0.028 rows=2 loops=1)
>-> Seq Scan on h1 (cost=0.00..41.88 rows=26 width=4) (actual time=0.015..0.018 rows=1 loops=1)
> Filter: (id = ANY ('{1,5}'::integer[]))
> Rows Removed by Filter: 6
>-> Seq Scan on h3 (cost=0.00..41.88 rows=26 width=4) (actual time=0.005..0.007 rows=1 loops=1)
> Filter: (id = ANY ('{1,5}'::integer[]))
