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sumMap

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Description

The Map combinator can be applied to the sum function to calculate the sum of values in a Map according to each key, using the sumMap aggregate combinator function.

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Example usage

In this example, we’ll create a table that stores status codes and their counts for different timeslots, where each row contains a Map of status codes to their corresponding counts. We’ll use sumMap to calculate the total count for each status code within each timeslot.
Query
CREATE TABLE metrics(
    date Date,
    timeslot DateTime,
    status Map(String, UInt64)
) ENGINE = MergeTree
ORDER BY ();

INSERT INTO metrics VALUES
    ('2000-01-01', '2000-01-01 00:00:00', (['a', 'b', 'c'], [15, 25, 35])),
    ('2000-01-01', '2000-01-01 00:00:00', (['c', 'd', 'e'], [45, 55, 65])),
    ('2000-01-01', '2000-01-01 00:01:00', (['d', 'e', 'f'], [75, 85, 95])),
    ('2000-01-01', '2000-01-01 00:01:00', (['f', 'g', 'g'], [105, 115, 125]));

SELECT
    timeslot,
    sumMap(status),
FROM metrics
GROUP BY timeslot;
The sumMap function will calculate the total count for each status code within each timeslot. For example:
  • In timeslot ‘2000-01-01 00:00:00’:
    • Status ‘a’: 15
    • Status ‘b’: 25
    • Status ‘c’: 35 + 45 = 80
    • Status ‘d’: 55
    • Status ‘e’: 65
  • In timeslot ‘2000-01-01 00:01:00’:
    • Status ‘d’: 75
    • Status ‘e’: 85
    • Status ‘f’: 95 + 105 = 200
    • Status ‘g’: 115 + 125 = 240
Response
   ┌────────────timeslot─┬─sumMap(status)───────────────────────┐
1. │ 2000-01-01 00:01:00 │ {'d':75,'e':85,'f':200,'g':240}      │
2. │ 2000-01-01 00:00:00 │ {'a':15,'b':25,'c':80,'d':55,'e':65} │
   └─────────────────────┴──────────────────────────────────────┘

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See also