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64 lines
1.6 KiB
Markdown
64 lines
1.6 KiB
Markdown
# Aggregate functions {#aggregate_functions}
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Aggregate functions work in the [normal](http://www.sql-tutorial.com/sql-aggregate-functions-sql-tutorial) way as expected by database experts.
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ClickHouse also supports:
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- [Parametric aggregate functions](parametric_functions.md#aggregate_functions_parametric), which accept other parameters in addition to columns.
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- [Combinators](combinators.md#aggregate_functions_combinators), which change the behavior of aggregate functions.
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## NULL processing
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During aggregation, all `NULL`s are skipped.
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**Examples:**
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Consider this table:
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```
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┌─x─┬────y─┐
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│ 1 │ 2 │
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│ 2 │ ᴺᵁᴸᴸ │
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│ 3 │ 2 │
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│ 3 │ 3 │
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│ 3 │ ᴺᵁᴸᴸ │
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└───┴──────┘
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```
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Let's say you need to total the values in the `y` column:
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```
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:) SELECT sum(y) FROM t_null_big
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SELECT sum(y)
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FROM t_null_big
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┌─sum(y)─┐
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│ 7 │
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└────────┘
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1 rows in set. Elapsed: 0.002 sec.
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```
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The `sum` function interprets `NULL` as `0`. In particular, this means that if the function receives input of a selection where all the values are `NULL`, then the result will be `0`, not `NULL`.
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Now you can use the `groupArray` function to create an array from the `y` column:
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```
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:) SELECT groupArray(y) FROM t_null_big
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SELECT groupArray(y)
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FROM t_null_big
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┌─groupArray(y)─┐
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│ [2,2,3] │
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└───────────────┘
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1 rows in set. Elapsed: 0.002 sec.
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```
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`groupArray` does not include `NULL` in the resulting array.
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[Original article](https://clickhouse.yandex/docs/en/query_language/agg_functions/) <!--hide-->
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