I created a multi dimensional hypertable with the id as a 2nd dimension :
SELECT create_hypertable(
'<table>',
'<tstamp>',
'id',
1080,
migrate_data => true,
chunk_time_interval => INTERVAL '6 hours'
);
I have 1080 distinct ids in my table. My expectation was to find 1080 chunks, each with all the values for a single id in them. But for some reason, I find only 686 chunks. And When I explore the chunks, I see some with 1, 2 or 3 ids.
Is there something I dont understand ?
It does not mean you are going to have 1080 chunks. The number of chunks you will have will chance depending on the timestamp values in your table. The number_partitions means that in a specific timestamp range you can have upmost 1080 different hash partition ranges. Hash partition does not guarantee that you will have exactly the same number of partitions with the number you specified. Different values might end up with in the same partition.
In order to check number of chunks and to show example;
postgres=# insert into testtimescale select x.i%2160 , '2023-06-18 13:00:00+00'::timestamp, x.i as name from generate_series(1,10800) x(i);
INSERT 0 10800
postgres=# select count(*) from timescaledb_information.chunks where range_start = '2023-06-18 12:00:00+00' and range_end = '2023-06-18 18:00:00+00';
count
-------
932
(1 row)
postgres=# insert into testtimescale select x.i%1234 , '2023-06-18 13:00:00+00'::timestamp, x.i as name from generate_series(1,10800) x(i);
INSERT 0 10800
postgres=# select count(*) from timescaledb_information.chunks where range_start = '2023-06-18 12:00:00+00' and range_end = '2023-06-18 18:00:00+00';
count
-------
932
(1 row)
postgres=# insert into testtimescale select x.i%5000 , '2023-06-18 13:00:00+00'::timestamp, x.i as name from generate_series(1,10800) x(i);
INSERT 0 10800
postgres=# select count(*) from timescaledb_information.chunks where range_start = '2023-06-18 12:00:00+00' and range_end = '2023-06-18 18:00:00+00';
count
-------
1068
(1 row)
postgres=# insert into testtimescale select x.i%7000 , '2023-06-18 13:00:00+00'::timestamp, x.i as name from generate_series(1,10800) x(i);
INSERT 0 10800
postgres=# select count(*) from timescaledb_information.chunks where range_start = '2023-06-18 12:00:00+00' and range_end = '2023-06-18 18:00:00+00';
count
-------
1077
(1 row)
postgres=# insert into testtimescale select x.i%10000 , '2023-06-18 13:00:00+00'::timestamp, x.i as name from generate_series(1,108000) x(i);
INSERT 0 108000
postgres=# select count(*) from timescaledb_information.chunks where range_start = '2023-06-18 12:00:00+00' and range_end = '2023-06-18 18:00:00+00';
count
-------
1080
(1 row)
As you can see above when new data loaded into to id column new chunks will be created, but it cannot exceed 1080.