import CreateHypertablePolicyNote from "versionContent/_partials/_create-hypertable-columnstore-policy-note.mdx";
To create a _timescaledb_internal.dimension_info instance, you call add_dimension
to an existing hypertable.
Hypertables must always have a primary range dimension, followed by an arbitrary number of additional dimensions that can be either range or hash, Typically this is just one hash. For example:
SELECT add_dimension('conditions', by_range('time'));
SELECT add_dimension('conditions', by_hash('location', 2));For incompatible data types such as jsonb, you can specify a function to the partition_func argument
of the dimension build to extract a compatible data type. Look in the example section below.
By default, $TIMESCALE_DB calls $PG's internal hash function for the given type. You use a custom partitioning function for value types that do not have a native $PG hash function.
You can specify a custom partitioning function for both range and hash partitioning. A partitioning function should
take a anyelement argument as the only parameter and return a positive integer hash value. This hash value is
not a partition identifier, but rather the inserted value's position in the dimension's key space, which is then
divided across the partitions.
Create a by-range dimension builder. You can partition by_range on it's own.
-
Partition on time using
CREATE TABLEThe simplest usage is to partition on a time column:
CREATE TABLE conditions ( time TIMESTAMPTZ NOT NULL, location TEXT NOT NULL, device TEXT NOT NULL, temperature DOUBLE PRECISION NULL, humidity DOUBLE PRECISION NULL ) WITH ( tsdb.hypertable );
This is the default partition, you do not need to add it explicitly.
-
Extract time from a non-time column using
create_hypertableIf you have a table with a non-time column containing the time, such as a JSON column, add a partition function to extract the time:
CREATE TABLE my_table ( metric_id serial not null, data jsonb, ); CREATE FUNCTION get_time(jsonb) RETURNS timestamptz AS $$ SELECT ($1->>'time')::timestamptz $$ LANGUAGE sql IMMUTABLE; SELECT create_hypertable('my_table', by_range('data', '1 day', 'get_time'));
| Name | Type | Default | Required | Description |
|---|---|---|---|---|
column_name |
NAME |
- | ✔ | Name of column to partition on. |
partition_func |
REGPROC |
- | ✖ | The function to use for calculating the partition of a value. |
partition_interval |
ANYELEMENT |
- | ✖ | Interval to partition column on. |
If the column to be partitioned is a:
-
TIMESTAMP,TIMESTAMPTZ, orDATE: specifypartition_intervaleither as anINTERVALtype or an integer value in microseconds. -
Another integer type: specify
partition_intervalas an integer that reflects the column's underlying semantics. For example, if this column is in UNIX time, specifypartition_intervalin milliseconds.
The partition type and default value depending on column type is:
| Column Type | Partition Type | Default value |
|---|---|---|
TIMESTAMP WITHOUT TIMEZONE |
INTERVAL/INTEGER | 1 week |
TIMESTAMP WITH TIMEZONE |
INTERVAL/INTEGER | 1 week |
DATE |
INTERVAL/INTEGER | 1 week |
SMALLINT |
SMALLINT | 10000 |
INT |
INT | 100000 |
BIGINT |
BIGINT | 1000000 |
The main purpose of hash partitioning is to enable parallelization across multiple disks within the same time interval. Every distinct item in hash partitioning is hashed to one of N buckets. By default, $TIMESCALE_DB uses flexible range intervals to manage chunk sizes.
You use Parallel I/O in the following scenarios:
- Two or more concurrent queries should be able to read from different disks in parallel.
- A single query should be able to use query parallelization to read from multiple disks in parallel.
For the following options:
-
RAID: use a RAID setup across multiple physical disks, and expose a single logical disk to the hypertable. That is, using a single tablespace.
Best practice is to use RAID when possible, as you do not need to manually manage tablespaces in the database.
-
Multiple tablespaces: for each physical disk, add a separate tablespace to the database. $TIMESCALE_DB allows you to add multiple tablespaces to a single hypertable. However, although under the hood, a hypertable's chunks are spread across the tablespaces associated with that hypertable.
When using multiple tablespaces, a best practice is to also add a second hash-partitioned dimension to your hypertable and to have at least one hash partition per disk. While a single time dimension would also work, it would mean that the first chunk is written to one tablespace, the second to another, and so on, and thus would parallelize only if a query's time range exceeds a single chunk.
When adding a hash partitioned dimension, set the number of partitions to a multiple of number of disks. For example, the number of partitions P=N*Pd where N is the number of disks and Pd is the number of partitions per disk. This enables you to add more disks later and move partitions to the new disk from other disks.
$TIMESCALE_DB does not benefit from a very large number of hash partitions, such as the number of unique items you expect in partition field. A very large number of hash partitions leads both to poorer per-partition load balancing (the mapping of items to partitions using hashing), as well as much increased planning latency for some types of queries.
CREATE TABLE conditions (
"time" TIMESTAMPTZ NOT NULL,
location TEXT NOT NULL,
device TEXT NOT NULL,
temperature DOUBLE PRECISION NULL,
humidity DOUBLE PRECISION NULL
) WITH (
tsdb.hypertable
tsdb.chunk_interval='1 day'
);
SELECT add_dimension('conditions', by_hash('location', 2));| Name | Type | Default | Required | Description |
|---|---|---|---|---|
column_name |
NAME |
- | ✔ | Name of column to partition on. |
partition_func |
REGPROC |
- | ✖ | The function to use to calcule the partition of a value. |
number_partitions |
ANYELEMENT |
- | ✔ | Number of hash partitions to use for partitioning_column. Must be greater than 0. |
by_range and by-hash return an opaque _timescaledb_internal.dimension_info instance, holding the
dimension information used by this function.