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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. Differs from the sumMap function in that it does summation with overflow.

# sumMapWithOverflow

<h2 id="sumMapWithOverflow">
  sumMapWithOverflow
</h2>

Introduced in: v20.1.0

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`](/reference/functions/aggregate-functions/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.
</Note>

**Syntax**

```sql theme={null}
sumMapWithOverflow(key, value)
sumMapWithOverflow(Tuple(key, value))
```

**Arguments**

* `key` — Array of keys. [`Array`](/reference/data-types/array)
* `value` — Array of values. [`Array`](/reference/data-types/array)

**Returned value**

Returns a tuple of two arrays: keys in sorted order, and values summed for the corresponding keys. [`Tuple(Array, Array)`](/reference/data-types/tuple)

**Examples**

**Array syntax demonstrating overflow behavior**

```sql title=Query theme={null}
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;
```

```response title=Response theme={null}
┌────────────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**

```sql title=Query theme={null}
SELECT
    timeslot,
    toTypeName(sumMap(statusMapTuple)),
    toTypeName(sumMapWithOverflow(statusMapTuple))
FROM sum_map
GROUP BY timeslot;
```

```response title=Response theme={null}
┌────────────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**

* [sumMap](/reference/functions/aggregate-functions/sumMap)