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Add sumMapFiltered and sumMapFilteredWithOverflow
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@ -507,14 +507,116 @@ HAVING uniqUpTo(4)(UserID) >= 5
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## sumMapFiltered
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## sumMapFiltered
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Same behavior as [sumMap](../../sql-reference/aggregate-functions/reference/summap.md#agg_functions-summap) except that an array of keys is passed as a parameter. This can be especially useful when working with a high cardinality of keys.
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This function behaves the same as [sumMap](../../sql-reference/aggregate-functions/reference/summap.md#agg_functions-summap) except that it also accepts an array of keys to filter with as a parameter. This can be especially useful when working with a high cardinality of keys.
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**Syntax**
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**Syntax**
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`sumMapFiltered(keys_to_keep)(keys, values)`
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`sumMapFiltered(keys_to_keep)(keys, values)`
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**Parameters**
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- `keys_to_keep`: [Array](../data-types/array.md) of keys to filter with.
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- `keys`: [Array](../data-types/array.md) of keys.
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- `values`: [Array](../data-types/array.md) of values.
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**Returned Value**
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- Returns a tuple of two arrays: keys in sorted order, and values summed for the corresponding keys.
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**Example**
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Query:
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```sql
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CREATE TABLE sum_map
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(
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`date` Date,
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`timeslot` DateTime,
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`statusMap` Nested(status UInt16, requests UInt64)
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)
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ENGINE = Log
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INSERT INTO sum_map VALUES
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('2000-01-01', '2000-01-01 00:00:00', [1, 2, 3], [10, 10, 10]),
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('2000-01-01', '2000-01-01 00:00:00', [3, 4, 5], [10, 10, 10]),
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('2000-01-01', '2000-01-01 00:01:00', [4, 5, 6], [10, 10, 10]),
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('2000-01-01', '2000-01-01 00:01:00', [6, 7, 8], [10, 10, 10]);
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```
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```sql
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SELECT sumMapFiltered([1, 4, 8])(statusMap.status, statusMap.requests) FROM sum_map;
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```
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Result:
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```response
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┌─sumMapFiltered([1, 4, 8])(statusMap.status, statusMap.requests)─┐
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1. │ ([1,4,8],[10,20,10]) │
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└─────────────────────────────────────────────────────────────────┘
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```
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## sumMapFilteredWithOverflow
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## sumMapFilteredWithOverflow
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This function behaves the same as [sumMap](../../sql-reference/aggregate-functions/reference/summap.md#agg_functions-summap) except that it also accepts an array of keys to filter with as a parameter. This can be especially useful when working with a high cardinality of keys. It differs from the [sumMapFiltered](#summapfiltered) function in that it does summation with overflow - i.e. returns the same data type for the summation as the argument data type.
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**Syntax**
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`sumMapFilteredWithOverflow(keys_to_keep)(keys, values)`
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**Parameters**
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- `keys_to_keep`: [Array](../data-types/array.md) of keys to filter with.
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- `keys`: [Array](../data-types/array.md) of keys.
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- `values`: [Array](../data-types/array.md) of values.
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**Returned Value**
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- Returns a tuple of two arrays: keys in sorted order, and values summed for the corresponding keys.
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**Example**
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In this example we create a table `sum_map`, insert some data into it and then use both `sumMapFilteredWithOverflow` and `sumMapFiltered` and the `toTypeName` function for comparison of the result. Where `requests` was of type `UInt8` in the created table, `sumMapFiltered` has promoted the type of the summed values to `UInt64` to avoid overflow whereas `sumMapFilteredWithOverflow` has kept the type as `UInt8` which is not large enough to store the result - i.e. overflow has occured.
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Query:
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```sql
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CREATE TABLE sum_map
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(
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`date` Date,
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`timeslot` DateTime,
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`statusMap` Nested(status UInt8, requests UInt8)
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)
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ENGINE = Log
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INSERT INTO sum_map VALUES
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('2000-01-01', '2000-01-01 00:00:00', [1, 2, 3], [10, 10, 10]),
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('2000-01-01', '2000-01-01 00:00:00', [3, 4, 5], [10, 10, 10]),
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('2000-01-01', '2000-01-01 00:01:00', [4, 5, 6], [10, 10, 10]),
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('2000-01-01', '2000-01-01 00:01:00', [6, 7, 8], [10, 10, 10]);
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```
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```sql
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SELECT sumMapFilteredWithOverflow([1, 4, 8])(statusMap.status, statusMap.requests) as summap_overflow, toTypeName(summap_overflow) FROM sum_map;
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```
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```sql
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SELECT sumMapFiltered([1, 4, 8])(statusMap.status, statusMap.requests) as summap, toTypeName(summap) FROM sum_map;
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```
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Result:
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```response
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┌─sum──────────────────┬─toTypeName(sum)───────────────────┐
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1. │ ([1,4,8],[10,20,10]) │ Tuple(Array(UInt8), Array(UInt8)) │
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└──────────────────────┴───────────────────────────────────┘
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```
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```response
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┌─summap───────────────┬─toTypeName(summap)─────────────────┐
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1. │ ([1,4,8],[10,20,10]) │ Tuple(Array(UInt8), Array(UInt64)) │
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└──────────────────────┴────────────────────────────────────┘
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```
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## sequenceNextNode
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## sequenceNextNode
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Returns a value of the next event that matched an event chain.
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Returns a value of the next event that matched an event chain.
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@ -16,8 +16,8 @@ Alias: `sumMappedArrays`.
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**Arguments**
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**Arguments**
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- `key`. [Array](../../data-types/array.md) of keys.
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- `key`: [Array](../../data-types/array.md) of keys.
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- `value`. [Array](../../data-types/array.md) of values.
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- `value`: [Array](../../data-types/array.md) of values.
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Passing a tuple of key and value arrays is a synonym to passing seperately an array of keys and an array of values.
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Passing a tuple of key and value arrays is a synonym to passing seperately an array of keys and an array of values.
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@ -6,7 +6,7 @@ sidebar_position: 141
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# sumMapWithOverflow
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# sumMapWithOverflow
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Totals a `value` array according to the keys specified in the `key` array. Returns a tuple of two arrays: keys in sorted order, and values summed for the corresponding keys.
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Totals a `value` array according to the keys specified in the `key` array. Returns a tuple of two arrays: keys in sorted order, and values summed for the corresponding keys.
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It differs from the [sumMap](../reference/summap.md) function in that it does summation with overflow - i.e. returns the same data type for the summation as the argument type.
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It differs from the [sumMap](../reference/summap.md) function in that it does summation with overflow - i.e. returns the same data type for the summation as the argument data type.
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**Syntax**
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**Syntax**
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@ -15,8 +15,8 @@ It differs from the [sumMap](../reference/summap.md) function in that it does su
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**Arguments**
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**Arguments**
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- `key`. [Array](../../data-types/array.md) of keys.
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- `key`: [Array](../../data-types/array.md) of keys.
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- `value`. [Array](../../data-types/array.md) of values.
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- `value`: [Array](../../data-types/array.md) of values.
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Passing a tuple of key and value arrays is a synonym to passing seperately an array of keys and an array of values.
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Passing a tuple of key and value arrays is a synonym to passing seperately an array of keys and an array of values.
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@ -24,6 +24,10 @@ Passing a tuple of key and value arrays is a synonym to passing seperately an ar
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The number of elements in `key` and `value` must be the same for each row that is totaled.
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The number of elements in `key` and `value` must be the same for each row that is totaled.
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:::
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:::
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**Returned Value**
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- Returns a tuple of two arrays: keys in sorted order, and values summed for the corresponding keys.
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**Example**
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**Example**
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First we create a table called `sum_map`, and insert some data into it. Arrays of keys and values are stored separately as a column called `statusMap` of [Nested](../../data-types/nested-data-structures/index.md) type, and together as a column called `statusMapTuple` of [tuple](../../data-types/tuple.md) type to illustrate the use of the two different syntaxes of this function described above.
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First we create a table called `sum_map`, and insert some data into it. Arrays of keys and values are stored separately as a column called `statusMap` of [Nested](../../data-types/nested-data-structures/index.md) type, and together as a column called `statusMapTuple` of [tuple](../../data-types/tuple.md) type to illustrate the use of the two different syntaxes of this function described above.
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