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129 lines
4.5 KiB
Markdown
129 lines
4.5 KiB
Markdown
---
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slug: /en/engines/table-engines/mergetree-family/aggregatingmergetree
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sidebar_position: 60
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sidebar_label: AggregatingMergeTree
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---
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# AggregatingMergeTree
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The engine inherits from [MergeTree](../../../engines/table-engines/mergetree-family/mergetree.md#table_engines-mergetree), altering the logic for data parts merging. ClickHouse replaces all rows with the same primary key (or more accurately, with the same [sorting key](../../../engines/table-engines/mergetree-family/mergetree.md)) with a single row (within a one data part) that stores a combination of states of aggregate functions.
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You can use `AggregatingMergeTree` tables for incremental data aggregation, including for aggregated materialized views.
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The engine processes all columns with the following types:
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## [AggregateFunction](../../../sql-reference/data-types/aggregatefunction.md)
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## [SimpleAggregateFunction](../../../sql-reference/data-types/simpleaggregatefunction.md)
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It is appropriate to use `AggregatingMergeTree` if it reduces the number of rows by orders.
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## Creating a Table {#creating-a-table}
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``` sql
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CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster]
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(
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name1 [type1] [DEFAULT|MATERIALIZED|ALIAS expr1],
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name2 [type2] [DEFAULT|MATERIALIZED|ALIAS expr2],
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...
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) ENGINE = AggregatingMergeTree()
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[PARTITION BY expr]
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[ORDER BY expr]
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[SAMPLE BY expr]
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[TTL expr]
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[SETTINGS name=value, ...]
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```
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For a description of request parameters, see [request description](../../../sql-reference/statements/create/table.md).
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**Query clauses**
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When creating an `AggregatingMergeTree` table the same [clauses](../../../engines/table-engines/mergetree-family/mergetree.md) are required, as when creating a `MergeTree` table.
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<details markdown="1">
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<summary>Deprecated Method for Creating a Table</summary>
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:::note
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Do not use this method in new projects and, if possible, switch the old projects to the method described above.
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:::
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``` sql
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CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster]
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(
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name1 [type1] [DEFAULT|MATERIALIZED|ALIAS expr1],
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name2 [type2] [DEFAULT|MATERIALIZED|ALIAS expr2],
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...
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) ENGINE [=] AggregatingMergeTree(date-column [, sampling_expression], (primary, key), index_granularity)
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```
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All of the parameters have the same meaning as in `MergeTree`.
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</details>
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## SELECT and INSERT {#select-and-insert}
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To insert data, use [INSERT SELECT](../../../sql-reference/statements/insert-into.md) query with aggregate -State- functions.
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When selecting data from `AggregatingMergeTree` table, use `GROUP BY` clause and the same aggregate functions as when inserting data, but using `-Merge` suffix.
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In the results of `SELECT` query, the values of `AggregateFunction` type have implementation-specific binary representation for all of the ClickHouse output formats. If dump data into, for example, `TabSeparated` format with `SELECT` query then this dump can be loaded back using `INSERT` query.
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## Example of an Aggregated Materialized View {#example-of-an-aggregated-materialized-view}
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We will create the table `test.visits` that contain the raw data:
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``` sql
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CREATE TABLE test.visits
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(
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StartDate DateTime64 NOT NULL,
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CounterID UInt64,
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Sign Nullable(Int32),
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UserID Nullable(Int32)
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) ENGINE = MergeTree ORDER BY (StartDate, CounterID);
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```
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`AggregatingMergeTree` materialized view that watches the `test.visits` table, and use the `AggregateFunction` type:
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``` sql
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CREATE MATERIALIZED VIEW test.mv_visits
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(
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StartDate DateTime64 NOT NULL,
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CounterID UInt64,
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Visits AggregateFunction(sum, Nullable(Int32)),
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Users AggregateFunction(uniq, Nullable(Int32))
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)
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ENGINE = AggregatingMergeTree() ORDER BY (StartDate, CounterID)
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AS SELECT
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StartDate,
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CounterID,
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sumState(Sign) AS Visits,
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uniqState(UserID) AS Users
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FROM test.visits
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GROUP BY StartDate, CounterID;
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```
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Inserting data into the `test.visits` table.
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``` sql
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INSERT INTO test.visits (StartDate, CounterID, Sign, UserID)
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VALUES (1667446031, 1, 3, 4)
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INSERT INTO test.visits (StartDate, CounterID, Sign, UserID)
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VALUES (1667446031, 1, 6, 3)
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```
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The data is inserted in both the table and the materialized view `test.mv_visits`.
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To get the aggregated data, we need to execute a query such as `SELECT ... GROUP BY ...` from the materialized view `test.mv_visits`:
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``` sql
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SELECT
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StartDate,
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sumMerge(Visits) AS Visits,
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uniqMerge(Users) AS Users
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FROM test.mv_visits
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GROUP BY StartDate
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ORDER BY StartDate;
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```
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## Related Content
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- Blog: [Using Aggregate Combinators in ClickHouse](https://clickhouse.com/blog/aggregate-functions-combinators-in-clickhouse-for-arrays-maps-and-states)
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