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88 lines
3.6 KiB
Markdown
88 lines
3.6 KiB
Markdown
# AggregatingMergeTree
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This engine differs from `MergeTree` in that the merge combines the states of aggregate functions stored in the table for rows with the same primary key value.
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For this to work, it uses the `AggregateFunction` data type, as well as `-State` and `-Merge` modifiers for aggregate functions. Let's examine it more closely.
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There is an `AggregateFunction` data type. It is a parametric data type. As parameters, the name of the aggregate function is passed, then the types of its arguments.
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Examples:
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```sql
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CREATE TABLE t
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(
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column1 AggregateFunction(uniq, UInt64),
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column2 AggregateFunction(anyIf, String, UInt8),
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column3 AggregateFunction(quantiles(0.5, 0.9), UInt64)
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) ENGINE = ...
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```
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This type of column stores the state of an aggregate function.
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To get this type of value, use aggregate functions with the `State` suffix.
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Example:`uniqState(UserID), quantilesState(0.5, 0.9)(SendTiming)`
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In contrast to the corresponding `uniq` and `quantiles` functions, these functions return the state, rather than the prepared value. In other words, they return an `AggregateFunction` type value.
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An `AggregateFunction` type value can't be output in Pretty formats. In other formats, these types of values are output as implementation-specific binary data. The `AggregateFunction` type values are not intended for output or saving in a dump.
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The only useful thing you can do with `AggregateFunction` type values is to combine the states and get a result, which essentially means to finish aggregation. Aggregate functions with the 'Merge' suffix are used for this purpose.
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Example: `uniqMerge(UserIDState)`, where `UserIDState` has the `AggregateFunction` type.
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In other words, an aggregate function with the 'Merge' suffix takes a set of states, combines them, and returns the result.
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As an example, these two queries return the same result:
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```sql
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SELECT uniq(UserID) FROM table
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SELECT uniqMerge(state) FROM (SELECT uniqState(UserID) AS state FROM table GROUP BY RegionID)
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```
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There is an `AggregatingMergeTree` engine. Its job during a merge is to combine the states of aggregate functions from different table rows with the same primary key value.
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You can't use a normal INSERT to insert a row in a table containing `AggregateFunction` columns, because you can't explicitly define the `AggregateFunction` value. Instead, use `INSERT SELECT` with `-State` aggregate functions for inserting data.
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With SELECT from an `AggregatingMergeTree` table, use GROUP BY and aggregate functions with the '-Merge' modifier in order to complete data aggregation.
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You can use `AggregatingMergeTree` tables for incremental data aggregation, including for aggregated materialized views.
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Example:
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Create an `AggregatingMergeTree` materialized view that watches the `test.visits` table:
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```sql
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CREATE MATERIALIZED VIEW test.basic
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ENGINE = AggregatingMergeTree(StartDate, (CounterID, StartDate), 8192)
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AS SELECT
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CounterID,
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StartDate,
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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 CounterID, StartDate;
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```
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Insert data in the `test.visits` table. Data will also be inserted in the view, where it will be aggregated:
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```sql
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INSERT INTO test.visits ...
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```
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Perform `SELECT` from the view using `GROUP BY` in order to complete data aggregation:
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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.basic
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GROUP BY StartDate
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ORDER BY StartDate;
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```
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You can create a materialized view like this and assign a normal view to it that finishes data aggregation.
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Note that in most cases, using `AggregatingMergeTree` is not justified, since queries can be run efficiently enough on non-aggregated data.
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