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sumMapWithOverflow

sumMapWithOverflow

Introduced in: v20.1

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. It differs from the sumMap function in that it does summation with overflow - i.e. returns the same data type for the summation as the argument data type.

Note
  • Passing a tuple of key and value arrays is identical to passing an array of keys and an array of values.
  • The number of elements in key and value must be the same for each row that is totaled.

Syntax

sumMapWithOverflow(key, value)
sumMapWithOverflow(Tuple(key, value))

Arguments

  • key — Array of keys. Array
  • value — Array of values. Array

Returned value

Returns a tuple of two arrays: keys in sorted order, and values summed for the corresponding keys. Tuple(Array, Array)

Examples

Array syntax demonstrating overflow behavior

CREATE TABLE sum_map(
    date Date,
    timeslot DateTime,
    statusMap Nested(
        status UInt8,
        requests UInt8
    ),
    statusMapTuple Tuple(Array(Int8), Array(Int8))
) ENGINE = Memory;

INSERT INTO sum_map VALUES
    ('2000-01-01', '2000-01-01 00:00:00', [1, 2, 3], [10, 10, 10], ([1, 2, 3], [10, 10, 10])),
    ('2000-01-01', '2000-01-01 00:00:00', [3, 4, 5], [10, 10, 10], ([3, 4, 5], [10, 10, 10])),
    ('2000-01-01', '2000-01-01 00:01:00', [4, 5, 6], [10, 10, 10], ([4, 5, 6], [10, 10, 10])),
    ('2000-01-01', '2000-01-01 00:01:00', [6, 7, 8], [10, 10, 10], ([6, 7, 8], [10, 10, 10]));

SELECT
    timeslot,
    toTypeName(sumMap(statusMap.status, statusMap.requests)),
    toTypeName(sumMapWithOverflow(statusMap.status, statusMap.requests))
FROM sum_map
GROUP BY timeslot;
┌────────────timeslot─┬─toTypeName(sumMap⋯usMap.requests))─┬─toTypeName(sumMa⋯usMap.requests))─┐
│ 2000-01-01 00:01:00 │ Tuple(Array(UInt8), Array(UInt64)) │ Tuple(Array(UInt8), Array(UInt8)) │
│ 2000-01-01 00:00:00 │ Tuple(Array(UInt8), Array(UInt64)) │ Tuple(Array(UInt8), Array(UInt8)) │
└─────────────────────┴────────────────────────────────────┴───────────────────────────────────┘

Tuple syntax with same result

SELECT
    timeslot,
    toTypeName(sumMap(statusMapTuple)),
    toTypeName(sumMapWithOverflow(statusMapTuple))
FROM sum_map
GROUP BY timeslot;
┌────────────timeslot─┬─toTypeName(sumMap(statusMapTuple))─┬─toTypeName(sumM⋯tatusMapTuple))─┐
│ 2000-01-01 00:01:00 │ Tuple(Array(Int8), Array(Int64))   │ Tuple(Array(Int8), Array(Int8)) │
│ 2000-01-01 00:00:00 │ Tuple(Array(Int8), Array(Int64))   │ Tuple(Array(Int8), Array(Int8)) │
└─────────────────────┴────────────────────────────────────┴─────────────────────────────────┘

See Also