可以使用“number”函数生成零值。然后使用union all和already将您的查询和零值连接起来，并根据获得的数据进行分组。
因此，您的查询将如下所示：

SELECT SUM(metric),
       time
  FROM (
        SELECT toStartOfQuarter(toDate(1514761200+number*30*24*3600))  time,
               toUInt16(0) AS metric
          FROM numbers(30)

     UNION ALL 

          SELECT toStartOfQuarter(created_at) AS time,
               metric
          FROM mytable
         WHERE created_at >= toDate(1514761200)
           AND created_at >= toDateTime(1514761200)
           AND created_at <= toDate(1546210800)
           AND created_at <= toDateTime(1546210800)
       )
 GROUP BY time
 ORDER BY time

注意：touint16（0）-零值必须与 metrics

在clickhouse 19.14中，您可以使用 WITH FILL 条款。它可以这样填满四分之一的空间：

WITH
    (
        SELECT toRelativeQuarterNum(toDate('1970-01-01'))
    ) AS init
SELECT
    -- build the date from the relative quarter number
    toDate('1970-01-01') + toIntervalQuarter(q - init) AS time,
    metric
FROM
(
    SELECT
        toRelativeQuarterNum(created_at) AS q,
        sum(rand()) AS metric
    FROM
    (
        -- generate some dates and metrics values with gaps
        SELECT toDate(arrayJoin(range(1514761200, 1546210800, ((60 * 60) * 24) * 180))) AS created_at
    )
    GROUP BY q
    ORDER BY q ASC WITH FILL FROM toRelativeQuarterNum(toDate(1514761200)) TO toRelativeQuarterNum(toDate(1546210800)) STEP 1
)

┌───────time─┬─────metric─┐
│ 2018-01-01 │ 2950782089 │
│ 2018-04-01 │ 2972073797 │
│ 2018-07-01 │          0 │
│ 2018-10-01 │  179581958 │
└────────────┴────────────┘

作为 numbers() 某些情况下的功能 range 数组函数也很有用。
示例：对于每对（id1，id2），应生成前7天的日期。

SELECT
  id1,
  id2,
  arrayJoin(
    arrayMap( x -> today() - 7 + x, range(7) )
  ) as date2
FROM table
WHERE date >= now() - 7
GROUP BY id1, id2

该选择的结果可以在union all中用于填充数据中的“孔”。

SELECT id1, id2, date, sum(column1)
FROM (
  SELECT
    id1,
    id2,
    date,
    column1 
  FROM table
  WHERE date >= now() - 7

  UNION ALL 

  SELECT
    id1,
    id2,
    arrayJoin(
      arrayMap( x -> today() - 7 + x, range(7) )
    ) as date2,
    0 as column1
  FROM table
  WHERE date >= now() - 7
  GROUP BY id1, id2
)
GROUP BY id1, id2, date
ORDER BY date, id1, id2

这是我如何做到的小时桶（需要在格拉法纳形象化），感谢@filimonov和@mikhail

SELECT t, SUM(metric) as metric FROM (
    SELECT 
        arrayJoin(
          arrayMap( x -> toStartOfHour(addHours(toDateTime($from),x)),
              range(toUInt64(
                  dateDiff('hour', 
                      toDateTime($from), 
                      toDateTime($to)) + 1)))
        ) as t,
        0 as metric

    UNION ALL

    SELECT
        toStartOfHour(my_date) as t,
        COUNT(metric)
        FROM my_table
        WHERE t BETWEEN toDateTime($from) AND toDateTime($to)
        GROUP BY t
)
GROUP BY t ORDER BY t

例如，对于2019-01-01到2019-01-02的范围，它将为您提供：

SELECT t, SUM(metric) as metric FROM (
    SELECT 
        arrayJoin(
          arrayMap( x -> toStartOfHour(addHours(toDateTime('2019-01-01 00:00:00'),x)),
              range(toUInt64(
                  dateDiff('hour', 
                      toDateTime('2019-01-01 00:00:00'), 
                      toDateTime('2019-01-02 00:00:00')) + 1)))
        ) as t,
        0 as metric

    UNION ALL

    SELECT
        toStartOfHour(my_date) as t,
        COUNT(1) as metric
        FROM my_table
        WHERE t BETWEEN toDateTime('2019-01-01 00:00:00') AND toDateTime('2019-01-02 00:00:00')
        GROUP BY t
)
GROUP BY t ORDER BY t;

t                  |metric|
-------------------|------|
2019-01-01 00:00:00|     0|
2019-01-01 01:00:00|     0|
2019-01-01 02:00:00|     0|
2019-01-01 03:00:00|     0|
2019-01-01 04:00:00|     0|
2019-01-01 05:00:00|     0|
2019-01-01 06:00:00|     0|
2019-01-01 07:00:00|105702|
2019-01-01 08:00:00|113315|
2019-01-01 09:00:00|149837|
2019-01-01 10:00:00|185314|
2019-01-01 11:00:00|246106|
2019-01-01 12:00:00|323036|
2019-01-01 13:00:00|     0|
2019-01-01 14:00:00|409160|
2019-01-01 15:00:00|379113|
2019-01-01 16:00:00|256634|
2019-01-01 17:00:00|286601|
2019-01-01 18:00:00|280039|
2019-01-01 19:00:00|248504|
2019-01-01 20:00:00|218642|
2019-01-01 21:00:00|186152|
2019-01-01 22:00:00|148478|
2019-01-01 23:00:00|109721|
2019-01-02 00:00:00|     0|