This topic describes how to use a TUMBLE function in Realtime Compute for Apache Flink.
Definition
A TUMBLE function assigns each element to a tumbling window that has a specific size.
In most cases, tumbling windows are fixed in size and do not overlap with each other.
For example, if a 5-minute tumbling window is defined, an infinite data stream is
divided into windows based on the time period, such as [0:00, 0:05)
, [0:05, 0:10)
, and [0:10, 0:15)
.
Syntax
You can use a TUMBLE function in a GROUP BY clause to define a tumbling window.
TUMBLE(<time-attr>, <size-interval>)
<size-interval>: INTERVAL 'string' timeUnit
Note The
<time-attr>
parameter must be a valid time attribute field in a time stream. This parameter specifies
whether the time is the processing time or the event time. For more information about
how to define time attributes, see Overview and Time Attributes.
Window identifier functions
A window identifier function specifies the start time, end time, or time attribute
of a window. The time attribute is used to aggregate lower-level windows.
Function | Type of return value | Description |
---|---|---|
TUMBLE_START(time-attr, size-interval) |
TIMESTAMP | Returns the start time, including the boundary value, of a window. For example, if
the time span of a window is [00:10, 00:15) , 00:10 is returned.
|
TUMBLE_END(time-attr, size-interval) |
TIMESTAMP | Returns the end time, including the boundary value, of a window. For example, if the
time span of a window is [00:00, 00:15] , 00:15 is returned.
|
TUMBLE_ROWTIME(time-attr, size-interval) |
TIMESTAMP(rowtime-attr) | Returns the end time, excluding the boundary value, of a window. For example, if the
time span of a window is (00:00, 00:15) , 00:14:59.999 is returned. The return value is a rowtime attribute based on which time operations
can be performed. This function can be used only in the windows that are defined based
on the event time, such as cascading windows. For more information, see Cascading windows.
|
TUMBLE_PROCTIME(time-attr, size-interval) |
TIMESTAMP(rowtime-attr) | Returns the end time, excluding the boundary value, of a window. For example, if the
time span of a window is (00:00, 00:15) , 00:14:59.999 is returned. The return value is a processing time attribute based on which time
operations can be performed. For example, this function can be used only in the windows
that are defined based on the processing time, such as cascading windows. For more
information, see Cascading windows.
|
Example 1: Count the number of clicks per user per minute for a specific website based on the event time
- Test data
username (VARCHAR) click_url (VARCHAR) eventtime (VARCHAR) Jark http://taobao.com/xxx
2017-10-10 10:00:00.0
Jark http://taobao.com/xxx
2017-10-10 10:00:10.0
Jark http://taobao.com/xxx
2017-10-10 10:00:49.0
Jark http://taobao.com/xxx
2017-10-10 10:01:05.0
Jark http://taobao.com/xxx
2017-10-10 10:01:58.0
Timo http://taobao.com/xxx
2017-10-10 10:02:10.0
- Test statements
CREATE TEMPORARY TABLE user_clicks( username varchar, click_url varchar, eventtime varchar, ts AS TO_TIMESTAMP(eventtime), WATERMARK FOR ts AS ts - INTERVAL '2' SECOND -- Define a watermark for the rowtime. ) WITH ( 'connector'='sls', ... ); CREATE TEMPORARY TABLE tumble_output( window_start TIMESTAMP, window_end TIMESTAMP, username VARCHAR, clicks BIGINT ) WITH ( 'connector'='datahub' -- Log Service allows you to export only VARCHAR-type DDL statements. Therefore, DataHub is used for storage. ... ); INSERT INTO tumble_output SELECT TUMBLE_START(ts, INTERVAL '1' MINUTE) as window_start, TUMBLE_END(ts, INTERVAL '1' MINUTE) as window_end, username, COUNT(click_url) FROM user_clicks GROUP BY TUMBLE(ts, INTERVAL '1' MINUTE),username;
- Test results
window_start (TIMESTAMP) window_end (TIMESTAMP) username (VARCHAR) clicks (BIGINT) 2017-10-10 10:00:00.0
2017-10-10 10:01:00.0
Jark 3 2017-10-10 10:01:00.0
2017-10-10 10:02:00.0
Jark 2 2017-10-10 10:02:00.0
2017-10-10 10:03:00.0
Timo 1
Example 2: Count the number of clicks per user per minute for a specific website based on the processing time
- Test data
username (VARCHAR) click_url (VARCHAR) Jark http://taobao.com/xxx
Jark http://taobao.com/xxx
Jark http://taobao.com/xxx
Jark http://taobao.com/xxx
Jark http://taobao.com/xxx
Timo http://taobao.com/xxx
- Test statements
CREATE TEMPORARY TABLE window_test ( username VARCHAR, click_url VARCHAR, ts as PROCTIME() ) WITH ( 'connector'='sls', ... ); CREATE TEMPORARY TABLE tumble_output( window_start TIMESTAMP, window_end TIMESTAMP, username VARCHAR, clicks BIGINT ) WITH ( 'connector'='datahub' -- Log Service allows you to export only VARCHAR-type DDL statements. Therefore, DataHub is used for storage. ... ); INSERT INTO tumble_output SELECT TUMBLE_START(ts, INTERVAL '1' MINUTE), TUMBLE_END(ts, INTERVAL '1' MINUTE), username, COUNT(click_url) FROM window_test GROUP BY TUMBLE(ts, INTERVAL '1' MINUTE), username;
- Test results
window_start (TIMESTAMP) window_end (TIMESTAMP) username (VARCHAR) clicks (BIGINT) 2019-04-11 14:43:00.000
2019-04-11 14:44:00.000
Jark 5 2019-04-11 14:43:00.000
2019-04-11 14:44:00.000
Timo 1