Relational Data - Data Types - Datetime

Allows to store an instant in time, that can be expressed as a calendar date and a time of a day.

Syntax:

DateTime([timezone])

Supported range of values: [1970-01-01 00:00:00, 2106-02-07 06:28:15].

Resolution: 1 second.

Speed

The Date datatype is faster than DateTime under most conditions.

The Date type requires 2 bytes of storage, while DateTime requires 4. However, when the database compresses the database, this difference is amplified. This amplification is due to the minutes and seconds in DateTime being less compressible. Filtering and aggregating Date instead of DateTime is also faster.

Usage Remarks

The point in time is saved as a Unix timestamp, regardless of the time zone or daylight saving time. The time zone affects how the values of the DateTime type values are displayed in text format and how the values specified as strings are parsed (‘2020-01-01 05:00:01’).

Timezone agnostic Unix timestamp is stored in tables, and the timezone is used to transform it to text format or back during data import/export or to make calendar calculations on the values (example: toDate, toHour functions etc.). The time zone is not stored in the rows of the table (or in resultset), but is stored in the column metadata.

A list of supported time zones can be found in the IANA Time Zone Database and also can be queried by SELECT * FROM system.time_zones. The list is also available at Wikipedia.

You can explicitly set a time zone for DateTime-type columns when creating a table. Example: DateTime('UTC'). If the time zone isn’t set, ClickHouse uses the value of the timezone parameter in the server settings or the operating system settings at the moment of the ClickHouse server start.

The clickhouse-client applies the server time zone by default if a time zone isn’t explicitly set when initializing the data type. To use the client time zone, run clickhouse-client with the --use_client_time_zone parameter.

ClickHouse outputs values depending on the value of the date_time_output_format setting. YYYY-MM-DD hh:mm:ss text format by default. Additionally, you can change the output with the formatDateTime function.

When inserting data into ClickHouse, you can use different formats of date and time strings, depending on the value of the date_time_input_format setting.

Examples

1. Creating a table with a DateTime-type column and inserting data into it:

CREATE TABLE dt
(
    `timestamp` DateTime('Asia/Istanbul'),
    `event_id` UInt8
)
ENGINE = TinyLog;

-- Parse DateTime
-- - from string,
-- - from integer interpreted as number of seconds since 1970-01-01.
INSERT INTO dt VALUES ('2019-01-01 00:00:00', 1), (1546300800, 3);

SELECT * FROM dt;

┌───────────timestamp─┬─event_id─┐
│ 2019-01-01 00:00:00 │        2 │
│ 2019-01-01 03:00:00 │        1 │
└─────────────────────┴──────────┘

When inserting datetime as an integer, it is treated as Unix Timestamp (UTC). 1546300800 represents '2019-01-01 00:00:00' UTC. However, as timestamp column has Asia/Istanbul (UTC+3) timezone specified, when outputting as string the value will be shown as '2019-01-01 03:00:00'
When inserting string value as datetime, it is treated as being in column timezone. '2019-01-01 00:00:00' will be treated as being in Asia/Istanbul timezone and saved as 1546290000.

2. Filtering on DateTime values

SELECT * FROM dt WHERE timestamp = toDateTime('2019-01-01 00:00:00', 'Asia/Istanbul')

┌───────────timestamp─┬─event_id─┐
│ 2019-01-01 00:00:00 │        1 │
└─────────────────────┴──────────┘

DateTime column values can be filtered using a string value in WHERE predicate. It will be converted to DateTime automatically:

SELECT * FROM dt WHERE timestamp = '2019-01-01 00:00:00'

┌───────────timestamp─┬─event_id─┐
│ 2019-01-01 00:00:00 │        1 │
└─────────────────────┴──────────┘

3. Getting a time zone for a DateTime-type column:

SELECT toDateTime(now(), 'Asia/Istanbul') AS column, toTypeName(column) AS x

┌──────────────column─┬─x─────────────────────────┐
│ 2019-10-16 04:12:04 │ DateTime('Asia/Istanbul') │
└─────────────────────┴───────────────────────────┘

4. Timezone conversion

SELECT
toDateTime(timestamp, 'Europe/London') as lon_time,
toDateTime(timestamp, 'Asia/Istanbul') as mos_time
FROM dt

┌───────────lon_time──┬────────────mos_time─┐
│ 2019-01-01 00:00:00 │ 2019-01-01 03:00:00 │
│ 2018-12-31 21:00:00 │ 2019-01-01 00:00:00 │
└─────────────────────┴─────────────────────┘

As timezone conversion only changes the metadata, the operation has no computation cost.

Limitations on time zones support

Some time zones may not be supported completely. There are a few cases:

If the offset from UTC is not a multiple of 15 minutes, the calculation of hours and minutes can be incorrect. For example, the time zone in Monrovia, Liberia has offset UTC -0:44:30 before 7 Jan 1972. If you are doing calculations on the historical time in Monrovia timezone, the time processing functions may give incorrect results. The results after 7 Jan 1972 will be correct nevertheless.

If the time transition (due to daylight saving time or for other reasons) was performed at a point of time that is not a multiple of 15 minutes, you can also get incorrect results at this specific day.

Non-monotonic calendar dates. For example, in Happy Valley - Goose Bay, the time was transitioned one hour backwards at 00:01:00 7 Nov 2010 (one minute after midnight). So after 6th Nov has ended, people observed a whole one minute of 7th Nov, then time was changed back to 23:01 6th Nov and after another 59 minutes the 7th Nov started again. ClickHouse does not (yet) support this kind of fun. During these days the results of time processing functions may be slightly incorrect.

Similar issue exists for Casey Antarctic station in year 2010. They changed time three hours back at 5 Mar, 02:00. If you are working in antarctic station, please don’t be afraid to use ClickHouse. Just make sure you set timezone to UTC or be aware of inaccuracies.

Time shifts for multiple days. Some pacific islands changed their timezone offset from UTC+14 to UTC-12. That’s alright but some inaccuracies may present if you do calculations with their timezone for historical time points at the days of conversion.

Speed

Usage Remarks

Examples

Limitations on time zones support

See Also