CREATE MATERIALIZED VIEW statement is used to create continuous
aggregates. To learn more, see the continuous aggregate how-to guides.
The syntax is:
CREATE MATERIALIZED VIEW <view_name> [ ( column_name [, ...] ) ]WITH ( timescaledb.continuous [, timescaledb.<option> = <value> ] )AS<select_query>[WITH [NO] DATA]
<select_query> is of the form:
SELECT <grouping_exprs>, <aggregate_functions>FROM <hypertable or another continuous aggregate>[WHERE ... ]GROUP BY time_bucket( <const_value>, <partition_col_of_hypertable> ),[ optional grouping exprs>][HAVING ...]
The continuous aggregate view defaults to
WITH DATA. This means that when the
view is created, it refreshes using all the current data in the underlying
hypertable or continuous aggregate. This occurs once when the view is created. If you want the view to
be refreshed regularly, you can use a refresh policy. If you do not want the
view to update when it is first created, use the
WITH NO DATA
parameter. For more information, see
Continuous aggregates have some limitations of what types of queries they can
support, described in more length below. For example, the
FROM clause must
provide only one hypertable or underlying continuous aggregate, and joins, CTEs, or subqueries are not
GROUP BY clause must include a time bucket on the underlying
time column, and all aggregates must be parallelizable.
Some important things to remember when constructing your
- Only a single hypertable or continuous aggregate can be specified in the
FROMclause of the
SELECTquery. You cannot include more hypertables, joins, tables, views, or subqueries.
- The source hypertable or continuous aggregate used in the
SELECTquery must not have row-level-security policies enabled.
GROUP BYclause must include a
time_bucketexpression that uses the time dimension of the hypertable. When creating a continuous aggregate on top of another continuous aggregate,
time_bucketmust use the time-bucketing column of the underlying continuous aggregate. For more information, see the
- You cannot use
time_bucket_gapfillin continuous aggregates, but you can run them in a
SELECTquery from the continuous aggregate view.
- You can usually use aggregates that are
parallelized by PostgreSQL in the view definition,
including most aggregates distributed by PostgreSQL. However, the
FILTERclauses are not supported.
- All functions and their arguments included in
HAVINGclauses must be immutable.
- The view cannot be a security barrier view.
- You cannot use Window functions with continuous aggregates.
The settings for continuous aggregates are in the informational views.
|TEXT||Name (optionally schema-qualified) of continuous aggregate view to create|
|TEXT||Optional list of names to be used for columns of the view. If not given, the column names are calculated from the query|
|TEXT||Specifies options for the continuous aggregate view|
WITH clause options:
WITH clause options:
|BOOLEAN||Return only materialized data when querying the continuous aggregate view|
|BOOLEAN||Create indexes on the continuous aggregate for columns in its |
|BOOLEAN||In TimescaleDB 2.7 and above, use the new version of continuous aggregates, which stores finalized results for aggregate functions. Supports all aggregate functions, including ones that use |
For more information, see the real-time aggregates section.
Create a daily continuous aggregate view:
CREATE MATERIALIZED VIEW continuous_aggregate_daily( timec, minl, sumt, sumh )WITH (timescaledb.continuous) ASSELECT time_bucket('1day', timec), min(location), sum(temperature), sum(humidity)FROM conditionsGROUP BY time_bucket('1day', timec)
Add a thirty day continuous aggregate on top of the same raw hypertable:
CREATE MATERIALIZED VIEW continuous_aggregate_thirty_day( timec, minl, sumt, sumh )WITH (timescaledb.continuous) ASSELECT time_bucket('30day', timec), min(location), sum(temperature), sum(humidity)FROM conditionsGROUP BY time_bucket('30day', timec);
Add an hourly continuous aggregate on top of the same raw hypertable:
CREATE MATERIALIZED VIEW continuous_aggregate_hourly( timec, minl, sumt, sumh )WITH (timescaledb.continuous) ASSELECT time_bucket('1h', timec), min(location), sum(temperature), sum(humidity)FROM conditionsGROUP BY time_bucket('1h', timec);
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