ClickHouse/docs/en/engines/table-engines/mergetree-family/aggregatingmergetree.md

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---
toc_priority: 35
toc_title: AggregatingMergeTree
---
# Aggregatingmergetree {#aggregatingmergetree}
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.
You can use `AggregatingMergeTree` tables for incremental data aggregation, including for aggregated materialized views.
The engine processes all columns with the following types:
- [AggregateFunction](../../../sql-reference/data-types/aggregatefunction.md)
- [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
CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster]
(
name1 [type1] [DEFAULT|MATERIALIZED|ALIAS expr1],
name2 [type2] [DEFAULT|MATERIALIZED|ALIAS expr2],
...
) ENGINE = AggregatingMergeTree()
[PARTITION BY expr]
[ORDER BY expr]
[SAMPLE BY expr]
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[TTL expr]
[SETTINGS name=value, ...]
```
For a description of request parameters, see [request description](../../../sql-reference/statements/create/table.md).
**Query clauses**
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When creating a `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>
!!! attention "Attention"
Do not use this method in new projects and, if possible, switch the old projects to the method described above.
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``` sql
CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster]
(
name1 [type1] [DEFAULT|MATERIALIZED|ALIAS expr1],
name2 [type2] [DEFAULT|MATERIALIZED|ALIAS expr2],
...
) ENGINE [=] AggregatingMergeTree(date-column [, sampling_expression], (primary, key), index_granularity)
```
All of the parameters have the same meaning as in `MergeTree`.
</details>
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## SELECT and INSERT {#select-and-insert}
To insert data, use [INSERT SELECT](../../../sql-reference/statements/insert-into.md) query with aggregate -State- functions.
When selecting data from `AggregatingMergeTree` table, use `GROUP BY` clause and the same aggregate functions as when inserting data, but using `-Merge` suffix.
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.
## Example of an Aggregated Materialized View {#example-of-an-aggregated-materialized-view}
`AggregatingMergeTree` materialized view that watches the `test.visits` table:
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``` sql
CREATE MATERIALIZED VIEW test.basic
ENGINE = AggregatingMergeTree() PARTITION BY toYYYYMM(StartDate) ORDER BY (CounterID, StartDate)
AS SELECT
CounterID,
StartDate,
sumState(Sign) AS Visits,
uniqState(UserID) AS Users
FROM test.visits
GROUP BY CounterID, StartDate;
```
Inserting data into the `test.visits` table.
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``` sql
INSERT INTO test.visits ...
```
The data are inserted in both the table and view `test.basic` that will perform the aggregation.
To get the aggregated data, we need to execute a query such as `SELECT ... GROUP BY ...` from the view `test.basic`:
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``` sql
SELECT
StartDate,
sumMerge(Visits) AS Visits,
uniqMerge(Users) AS Users
FROM test.basic
GROUP BY StartDate
ORDER BY StartDate;
```
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[Original article](https://clickhouse.tech/docs/en/operations/table_engines/aggregatingmergetree/) <!--hide-->