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Aggregate by Time Window

Aggregation by time window is supported in TDengine. For example, in the case where temperature sensors report the temperature every seconds, the average temperature for every 10 minutes can be retrieved by performing a query with a time window. Window related clauses are used to divide the data set to be queried into subsets and then aggregation is performed across the subsets. There are three kinds of windows: time window, status window, and session window. There are two kinds of time windows: sliding window and flip time/tumbling window.

Time Window

The INTERVAL clause is used to generate time windows of the same time interval. The SLIDING parameter is used to specify the time step for which the time window moves forward. The query is performed on one time window each time, and the time window moves forward with time. When defining a continuous query, both the size of the time window and the step of forward sliding time need to be specified. As shown in the figure blow, [t0s, t0e] ,[t1s , t1e], [t2s, t2e] are respectively the time ranges of three time windows on which continuous queries are executed. The time step for which time window moves forward is marked by sliding time. Query, filter and aggregate operations are executed on each time window respectively. When the time step specified by SLIDING is same as the time interval specified by INTERVAL, the sliding time window is actually a flip time/tumbling window.

TDengine Database Time Window

INTERVAL and SLIDING should be used with aggregate functions and select functions. The SQL statement below is illegal because no aggregate or selection function is used with INTERVAL.

SELECT * FROM temp_tb_1 INTERVAL(1m);

The time step specified by SLIDING cannot exceed the time interval specified by INTERVAL. The SQL statement below is illegal because the time length specified by SLIDING exceeds that specified by INTERVAL.


When the time length specified by SLIDING is the same as that specified by INTERVAL, the sliding window is actually a flip/tumbling window. The minimum time range specified by INTERVAL is 10 milliseconds (10a) prior to version Since version, the minimum time range by INTERVAL can be 1 microsecond (1u). However, if the DB precision is millisecond, the minimum time range is 1 millisecond (1a). Please note that the timezone parameter should be configured to be the same value in the taos.cfg configuration file on client side and server side.

Status Window

In case of using integer, bool, or string to represent the status of a device at any given moment, continuous rows with the same status belong to a status window. Once the status changes, the status window closes. As shown in the following figure, there are two status windows according to status, [2019-04-28 14:22:07,2019-04-28 14:22:10] and [2019-04-28 14:22:11,2019-04-28 14:22:12]. Status window is not applicable to STable for now.

TDengine Database Status Window

STATE_WINDOW is used to specify the column on which the status window will be based. For example:

SELECT COUNT(*), FIRST(ts), status FROM temp_tb_1 STATE_WINDOW(status);

Session Window

SELECT COUNT(*), FIRST(ts) FROM temp_tb_1 SESSION(ts, tol_val);

The primary key, i.e. timestamp, is used to determine which session window a row belongs to. If the time interval between two adjacent rows is within the time range specified by tol_val, they belong to the same session window; otherwise they belong to two different session windows. As shown in the figure below, if the limit of time interval for the session window is specified as 12 seconds, then the 6 rows in the figure constitutes 2 time windows, [2019-04-28 14:22:10,2019-04-28 14:22:30] and [2019-04-28 14:23:10,2019-04-28 14:23:30], because the time difference between 2019-04-28 14:22:30 and 2019-04-28 14:23:10 is 40 seconds, which exceeds the time interval limit of 12 seconds.

TDengine Database Session Window

If the time interval between two continuous rows are within the time interval specified by tol_value they belong to the same session window; otherwise a new session window is started automatically. Session window is not supported on STable for now.

More On Window Aggregate


The full syntax of aggregate by window is as follows:

SELECT function_list FROM tb_name
[WHERE where_condition]
[SESSION(ts_col, tol_val)]
[INTERVAL(interval [, offset]) [SLIDING sliding]]

SELECT function_list FROM stb_name
[WHERE where_condition]
[INTERVAL(interval [, offset]) [SLIDING sliding]]
[GROUP BY tags]


  • Aggregate functions and select functions can be used in function_list, with each function having only one output. For example COUNT, AVG, SUM, STDDEV, LEASTSQUARES, PERCENTILE, MIN, MAX, FIRST, LAST. Functions having multiple outputs, such as DIFF or arithmetic operations can't be used.
  • LAST_ROW can't be used together with window aggregate.
  • Scalar functions, like CEIL/FLOOR, can't be used with window aggregate.
  • WHERE clause can be used to specify the starting and ending time and other filter conditions
  • FILL clause is used to specify how to fill when there is data missing in any window, including:
    1. NONE: No fill (the default fill mode)
    2. VALUE:Fill with a fixed value, which should be specified together, for example FILL(VALUE, 1.23)
    3. PREV:Fill with the previous non-NULL value, FILL(PREV)
    4. NULL:Fill with NULL, FILL(NULL)
    5. LINEAR:Fill with the closest non-NULL value, FILL(LINEAR)
    6. NEXT:Fill with the next non-NULL value, FILL(NEXT)
  1. A huge volume of interpolation output may be returned using FILL, so it's recommended to specify the time range when using FILL. The maximum number of interpolation values that can be returned in a single query is 10,000,000.
  2. The result set is in ascending order of timestamp when you aggregate by time window.
  3. If aggregate by window is used on STable, the aggregate function is performed on all the rows matching the filter conditions. If GROUP BY is not used in the query, the result set will be returned in ascending order of timestamp; otherwise the result set is not exactly in the order of ascending timestamp in each group.

Aggregate by time window is also used in continuous query, please refer to Continuous Query.


A table of intelligent meters can be created by the SQL statement below:

CREATE TABLE meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS (location BINARY(64), groupId INT);

The average current, maximum current and median of current in every 10 minutes for the past 24 hours can be calculated using the SQL statement below, with missing values filled with the previous non-NULL values.

SELECT AVG(current), MAX(current), APERCENTILE(current, 50) FROM meters
WHERE ts>=NOW-1d and ts<=now