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https://issues.apache.org/jira/browse/IOTDB-59?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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suyue closed IOTDB-59.
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> GroupBy module
> --------------
>
> Key: IOTDB-59
> URL: https://issues.apache.org/jira/browse/IOTDB-59
> Project: Apache IoTDB
> Issue Type: New Feature
> Reporter: suyue
> Assignee: suyue
> Priority: Major
>
> h3. Down-Frequency Aggregate Query
> Groupby is used to partition the result set according to the user’s given
> partitioning conditions and aggregate the partitioned result set. IoTDB
> supports partitioning result sets according to time intervals, and by default
> results are sorted by time in ascending order. You can also use the [Java
> JDBC|http://iotdb.apache.org/Java-api-page,commingsoon] standard interface to
> execute related queries.
> The GROUP BY statement provides users with three types of specified
> parameters:
> * Parameter 1: Time interval for dividing the time axis
> * Parameter 2: Time axis origin position (optional)
> * Parameter 3: The display window(s) (one or more) on the time axis
> The actual meanings of the three types of parameters are shown in Figure 1
> below. Among them, the paramter 2 is optional. Next we will give three
> typical examples of frequency reduction aggregation: parameter 2 specified,
> parameter 2 not specified, and time filtering conditions specified.
> !https://user-images.githubusercontent.com/13203019/51577465-e8513380-1ef4-11e9-84c6-d0690f2a8113.jpg|width=597,height=213!
> *Figure 1 The actual meanings of the three types of parameters*
> h4. Down-Frequency Aggregate Query without Specifying the Time Axis Origin
> Position
> The SQL statement is:
> '''
> select count(status), max_value(temperature) from root.ln.wf01.wt01 group by
> (1d, [2017-11-01T00:00:00, 2017-11-07T23:00:00]);
> '''
> which means:
> Since the user does not specify the time axis origin position, the GROUP BY
> statement will by default set the origin at 0 (+0 time zone) on January 1,
> 1970.
> The first parameter of the GROUP BY statement above is the time interval for
> dividing the time axis. Taking this parameter (1d) as time interval and the
> default origin as the dividing origin, the time axis is divided into several
> continuous intervals, which are [0,1d], [1d, 2d], [2d, 3d], etc.
> The second parameter of the GROUP BY statement above is the display window
> paramter, which determines the final display range is [2017-11-01T00:00:00,
> 2017-11-07T23:00:00].
> Then the system will use the time and value filtering condition in the WHERE
> clause and the second parameter of the GROUP BY statement as the data
> filtering condition to obtain the data satisfying the filtering condition
> (which in this case is the data in the range of [2017-11-01T00:00:00,
> 2017-11-07 T23:00:00]), and map these data to the previously segmented time
> axis (in this case there are mapped data in every 1-day period from
> 2017-11-01T00:00:00 to 2017-11-07T23:00:00:00).
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