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6.1 KiB
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144 lines
6.1 KiB
Markdown
---
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slug: /en/engines/table-engines/mergetree-family/summingmergetree
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sidebar_position: 50
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sidebar_label: SummingMergeTree
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---
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# SummingMergeTree
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The engine inherits from [MergeTree](../../../engines/table-engines/mergetree-family/mergetree.md#table_engines-mergetree). The difference is that when merging data parts for `SummingMergeTree` tables ClickHouse replaces all the rows with the same primary key (or more accurately, with the same [sorting key](../../../engines/table-engines/mergetree-family/mergetree.md)) with one row which contains summarized values for the columns with the numeric data type. If the sorting key is composed in a way that a single key value corresponds to large number of rows, this significantly reduces storage volume and speeds up data selection.
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We recommend using the engine together with `MergeTree`. Store complete data in `MergeTree` table, and use `SummingMergeTree` for aggregated data storing, for example, when preparing reports. Such an approach will prevent you from losing valuable data due to an incorrectly composed primary key.
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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 = SummingMergeTree([columns])
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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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[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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### Parameters of SummingMergeTree
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#### columns
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`columns` - a tuple with the names of columns where values will be summarized. Optional parameter.
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The columns must be of a numeric type and must not be in the primary key.
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If `columns` is not specified, ClickHouse summarizes the values in all columns with a numeric data type that are not in the primary key.
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### Query clauses
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When creating a `SummingMergeTree` 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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:::warning
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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 [=] SummingMergeTree(date-column [, sampling_expression], (primary, key), index_granularity, [columns])
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```
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All of the parameters excepting `columns` have the same meaning as in `MergeTree`.
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- `columns` — tuple with names of columns values of which will be summarized. Optional parameter. For a description, see the text above.
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</details>
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## Usage Example {#usage-example}
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Consider the following table:
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``` sql
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CREATE TABLE summtt
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(
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key UInt32,
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value UInt32
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)
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ENGINE = SummingMergeTree()
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ORDER BY key
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```
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Insert data to it:
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``` sql
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INSERT INTO summtt Values(1,1),(1,2),(2,1)
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```
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ClickHouse may sum all the rows not completely ([see below](#data-processing)), so we use an aggregate function `sum` and `GROUP BY` clause in the query.
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``` sql
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SELECT key, sum(value) FROM summtt GROUP BY key
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```
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``` text
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┌─key─┬─sum(value)─┐
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│ 2 │ 1 │
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│ 1 │ 3 │
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└─────┴────────────┘
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```
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## Data Processing {#data-processing}
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When data are inserted into a table, they are saved as-is. ClickHouse merges the inserted parts of data periodically and this is when rows with the same primary key are summed and replaced with one for each resulting part of data.
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ClickHouse can merge the data parts so that different resulting parts of data can consist rows with the same primary key, i.e. the summation will be incomplete. Therefore (`SELECT`) an aggregate function [sum()](../../../sql-reference/aggregate-functions/reference/sum.md#agg_function-sum) and `GROUP BY` clause should be used in a query as described in the example above.
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### Common Rules for Summation {#common-rules-for-summation}
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The values in the columns with the numeric data type are summarized. The set of columns is defined by the parameter `columns`.
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If the values were 0 in all of the columns for summation, the row is deleted.
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If column is not in the primary key and is not summarized, an arbitrary value is selected from the existing ones.
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The values are not summarized for columns in the primary key.
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### The Summation in the Aggregatefunction Columns {#the-summation-in-the-aggregatefunction-columns}
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For columns of [AggregateFunction type](../../../sql-reference/data-types/aggregatefunction.md) ClickHouse behaves as [AggregatingMergeTree](../../../engines/table-engines/mergetree-family/aggregatingmergetree.md) engine aggregating according to the function.
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### Nested Structures {#nested-structures}
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Table can have nested data structures that are processed in a special way.
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If the name of a nested table ends with `Map` and it contains at least two columns that meet the following criteria:
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- the first column is numeric `(*Int*, Date, DateTime)` or a string `(String, FixedString)`, let’s call it `key`,
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- the other columns are arithmetic `(*Int*, Float32/64)`, let’s call it `(values...)`,
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then this nested table is interpreted as a mapping of `key => (values...)`, and when merging its rows, the elements of two data sets are merged by `key` with a summation of the corresponding `(values...)`.
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Examples:
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``` text
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[(1, 100)] + [(2, 150)] -> [(1, 100), (2, 150)]
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[(1, 100)] + [(1, 150)] -> [(1, 250)]
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[(1, 100)] + [(1, 150), (2, 150)] -> [(1, 250), (2, 150)]
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[(1, 100), (2, 150)] + [(1, -100)] -> [(2, 150)]
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```
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When requesting data, use the [sumMap(key, value)](../../../sql-reference/aggregate-functions/reference/summap.md) function for aggregation of `Map`.
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For nested data structure, you do not need to specify its columns in the tuple of columns for summation.
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[Original article](https://clickhouse.com/docs/en/operations/table_engines/summingmergetree/) <!--hide-->
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