Creating and Selecting in Rollup Table
Creating Rollup Table
When user create tag table, Rollup does not created default, user must create by themselves. Syntax is as follow.
- rollup name : rollup table’s name (Can be freely created with string up to 40)
- source table name : Name of source table which rollup will aggregate data.
- src_table_column : rollup target data column name
- Only numeric type columns are allowed
- If the source table is a rollup table, it is omitted and automatically designated as the rollup target column of the source table
- number sec/min/hour : time and time unit for aggregate
ex) 1 sec aggregate : 1 sec
ex) 30 seconds aggregate : 30 sec
ex) 1 minute aggregate : 1 min
ex) 1 hour aggregate : 1 hour - constraint
- Source table for aggregation can specify only tag table or rollup table
- Only one rollup table can be exist to source table for aggregation
- If source table for aggregation is rollup table, time for rollup table must be bigger than time for source table. And it must be multiple.
Example for Creating rollup table
Mach> CREATE TAG TABLE tag (name VARCHAR(20) PRIMARY KEY, time DATETIME BASETIME, value DOUBLE, strvalue VARCHAR(20));
Executed successfully.
-- creating 1 second rollup for tag table
Mach> CREATE ROLLUP _tag_rollup_sec ON tag(value) INTERVAL 1 SEC;
-- creating 1 minute rollup for tag table
Mach> CREATE ROLLUP _tag_rollup_min ON tag(value) INTERVAL 1 MIN;
-- creating 1 hour rollup for tag table
Mach> CREATE ROLLUP _tag_rollup_hour ON tag(value) INTERVAL 1 HOUR;
-- creating 30 seconds rollup for tag table
Mach> CREATE ROLLUP _tag_rollup_30sec ON tag(value) INTERVAL 30 SEC;
-- creating 10 minutes rollup for roll up table above
Mach> CREATE ROLLUP _tag_rollup_10min ON _tag_rollup_30sec INTERVAL 10 MIN;
-- Error when creating rollup for non-numeric type columns
Mach> CREATE ROLLUP _tag_rollup_sec ON tag(strvalue) INTERVAL 1 SEC;
[ERR-02671: Invalid type for ROLLUP column (STRVALUE).]Automatically create a ROLLUP table
A roll-up table can be automatically generated using the keyword with ROLLUP (time_unit)
CREATE TAG TABLE tagtbl (name VARCHAR(20) PRIMARY KEY, time DATETIME BASETIME, value DOUBLE SUMMARIZED) WITH ROLLUP (time_unit)
time_unit := {SEC|MIN|HOUR}If the time_unit is not specified as below, it will proceed based on SEC.
CREATE TAG TABLE tagtbl (name VARCHAR(20) PRIMARY KEY, time DATETIME BASETIME, value DOUBLE SUMMARIZED) WITH ROLLUPThe name of the automatically generated rollup is generated in the following format. (tagtbl contains tag table name.)
- _
tagtbl_ROLLUP_SEC - _
tagtbl_ROLLUP_MIN - _
tagtbl_ROLLUP_HOUR
Mach> CREATE TAG TABLE tagtbl (name VARCHAR(20) PRIMARY KEY, time DATETIME BASETIME, value DOUBLE SUMMARIZED) WITH ROLLUP (SEC)
Mach> SHOW TABLES;
USER_NAME DB_NAME TABLE_NAME TABLE_TYPE
-----------------------------------------------------------------------------------------------------------------------------------------------
SYS MACHBASEDB TAGTBL TAGDATA
SYS MACHBASEDB _TAGTBL_DATA_0 KEYVALUE
SYS MACHBASEDB _TAGTBL_DATA_1 KEYVALUE
SYS MACHBASEDB _TAGTBL_DATA_2 KEYVALUE
SYS MACHBASEDB _TAGTBL_DATA_3 KEYVALUE
SYS MACHBASEDB _TAGTBL_META LOOKUP
SYS MACHBASEDB _TAGTBL_ROLLUP_HOUR KEYVALUE
SYS MACHBASEDB _TAGTBL_ROLLUP_MIN KEYVALUE
SYS MACHBASEDB _TAGTBL_ROLLUP_SEC KEYVALUE
[9] row(s) selected.
Elapsed time: 0.001
Mach>The criteria entered in time_unit are viewed as the smallest criteria and even the upper time unit is automatically generated.
When a rollup table name conflict occurs, all rollup table creation fails and only tag tables are generated.
Extended ROLLUP
By adding the EXTENSION keyword at the end of the syntax for creating Rollup tables, you can create an extended Rollup. An extended Rollup includes both the starting and ending values of the specified interval.
-- Manually create an Extended Rollup table
CREATE ROLLUP _tag_rollup_sec ON tag(value) INTERVAL 1 SEC EXTENSION;
-- Automatically generate Extended Rollup tables
CREATE TAG TABLE tagtbl (name VARCHAR(20) PRIMARY KEY, time DATETIME BASETIME, value DOUBLE SUMMARIZED) WITH ROLLUP EXTENSION;Start/Stop Rollup Table
When rollup is created, rollup thread is automatically started, and the user can start/stop rollup thread arbitrarily.
-- Start specific rollup
EXEC ROLLUP_START(rollup_name)
-- Stop specific rollup
EXEC ROLLUP_STOP(rollup_name)Collect Rollup Instantly
rollup basically aggregate data in set time unit.
- ex) If it is 1 hour rollup, it aggregate data once in hour and rest in rest time. User can aggregate data in force.
-- Execute specific rollup flush immediately
EXEC ROLLUP_FORCE(rollup_name)Drop Rollup
Drop Rollup.
DROP ROLLUP rollup_name- rollup_name : Name of rollup
- constraint: if there is an rollup table that reference rollup table that will be deleted as source tree, it will cause error. User must delete it in reverse order.
mach> create tag table tag (name varchar(20) primary key, time datetime basetime, value double summarized);
mach> create rollup _tag_rollup_1 on tag(value) interval 1 sec;
mach> create rollup _tag_rollup_2 on _tag_rollup_1 interval 1 min;
mach> create rollup _tag_rollup_3 on _tag_rollup_2 interval 1 hour;
When created as above, the reference order is as follows.
tag -> _tag_rollup_1 -> _tag_rollup_2 -> _tag_rollup_3
At this time, if you try to delete the tag table or rollup in the middle, an error occurs.
mach> drop rollup tag
> [ERR-02651: Dependent ROLLUP table exists.]
mach> drop rollup _tag_rollup_1
> [ERR-02651: Dependent ROLLUP table exists.]
User must delete them in the following order to delete them normally.
mach> drop rollup _tag_rollup_3;
mach> drop rollup _tag_rollup_2;
mach> drop rollup _tag_rollup_1;
mach> drop table tag;When deleting the TAG table, delete the ROLLUP table together
When deleting a tag table using the CASCADE keyword, you can also delete a roll-up table that is dependent on the tag table.
DROP TABLE TAG CASCADE;Mach> SHOW TABLES;
USER_NAME DB_NAME TABLE_NAME TABLE_TYPE
-----------------------------------------------------------------------------------------------------------------------------------------------
SYS MACHBASEDB TAGTBL TAGDATA
SYS MACHBASEDB _TAGTBL_DATA_0 KEYVALUE
SYS MACHBASEDB _TAGTBL_DATA_1 KEYVALUE
SYS MACHBASEDB _TAGTBL_DATA_2 KEYVALUE
SYS MACHBASEDB _TAGTBL_DATA_3 KEYVALUE
SYS MACHBASEDB _TAGTBL_META LOOKUP
SYS MACHBASEDB _TAGTBL_ROLLUP_HOUR KEYVALUE
SYS MACHBASEDB _TAGTBL_ROLLUP_MIN KEYVALUE
SYS MACHBASEDB _TAGTBL_ROLLUP_SEC KEYVALUE
[9] row(s) selected.
Elapsed time: 0.001
Mach>
Mach> DROP TABLE tagtbl CASCADE;
Dropped successfully.
Mach> show tables;
USER_NAME DB_NAME TABLE_NAME TABLE_TYPE
-----------------------------------------------------------------------------------------------------------------------------------------------
[0] row(s) selected.Syntax
rollup_expr := ROLLUP(time_unit, period, basetime_column [, origin])
--ex)
SELECT ROLLUP('MIN', 30, time, '1970-01-01'), MIN(value), MAX(value), AVG(value) FROM tag ..If you use the ROLLUP keyword as above, the records are fetched from an appropriate rollup table.
- time_unit: Any time unit available in the DATE_BIN() function can be used. (see below)
- period: DATE_BIN() can specify a range for each unit of time available. (see below)
- basetime_column: Datetime column of the TAG table specified by the BASETIME attribute
- origin: The origin time to bin the ROLLUP time interval. If not specified, it is set to ‘1970-01-01’ by default.
Deprecated (version <= 8.0.19)
In version 8.0.19 and below, use the following ROLLUP expression.rollup_expr := basetime_column ROLLUP n time_unit -- ex) SELECT time ROLLUP 30 MIN, MIN(value), MAX(value), AVG(value) FROM tag ..
As above, if the ROLLUP clause is appended after the Datetime type column specified as the BASETIME attribute, the rollup table is selected.
Depending on the selection of TIME_UNIT, the searched rollup table is different.
| unit of time(Abbreviation) | rollup table |
|---|---|
| nanosecond (nsec) | SECOND |
| microsecond (usec) | SECOND |
| milisecond (msec) | SECOND |
| second (sec) | SECOND |
| minute (min) | MINUTE |
| hour | HOUR |
| day | HOUR |
| week | HOUR |
| month | HOUR |
| year | HOUR |
Since using the ROLLUP clause directly performs a rollup table lookup, to use an aggregate function, it has the following characteristics.
- The aggregate function must be called on the numeric type column. However, only the six aggregate functions (SUM, COUNT, MIN, MAX, AVG, SUMSQ) supported by the rollup table are supported.
- In the case of Extended Rollup, (FIRST, LAST) is additionally supported.
- GROUP BY must be done directly with the BASETIME column to be ROLLUP.
- You can use the ROLLUP clause with the same meaning as it is.
- Alternatively, an alias may be attached to the ROLLUP clause, and the alias may be written in GROUP BY.
SELECT rollup('sec', 3, time) mtime, avg(value)
FROM TAG
GROUP BY mtime;
-- deprecated
SELECT time rollup 3 sec mtime, avg(value)
FROM TAG
GROUP BY time rollup 3 sec mtime;
-- or
SELECT time rollup 3 sec mtime, avg(value)
FROM TAG
GROUP BY mtime;Data Sample
Below is sample data for rollup test.
create tag table TAG (name varchar(20) primary key, time datetime basetime, value double summarized) with rollup extension;
insert into tag metadata values ('TAG_0001');
insert into tag values('TAG_0001', '2018-01-01 01:00:01 000:000:000', 1);
insert into tag values('TAG_0001', '2018-01-01 01:00:02 000:000:000', 2);
insert into tag values('TAG_0001', '2018-01-01 01:01:01 000:000:000', 3);
insert into tag values('TAG_0001', '2018-01-01 01:01:02 000:000:000', 4);
insert into tag values('TAG_0001', '2018-01-01 01:02:01 000:000:000', 5);
insert into tag values('TAG_0001', '2018-01-01 01:02:02 000:000:000', 6);
insert into tag values('TAG_0001', '2018-01-01 02:00:01 000:000:000', 1);
insert into tag values('TAG_0001', '2018-01-01 02:00:02 000:000:000', 2);
insert into tag values('TAG_0001', '2018-01-01 02:01:01 000:000:000', 3);
insert into tag values('TAG_0001', '2018-01-01 02:01:02 000:000:000', 4);
insert into tag values('TAG_0001', '2018-01-01 02:02:01 000:000:000', 5);
insert into tag values('TAG_0001', '2018-01-01 02:02:02 000:000:000', 6);
insert into tag values('TAG_0001', '2018-01-01 03:00:01 000:000:000', 1);
insert into tag values('TAG_0001', '2018-01-01 03:00:02 000:000:000', 2);
insert into tag values('TAG_0001', '2018-01-01 03:01:01 000:000:000', 3);
insert into tag values('TAG_0001', '2018-01-01 03:01:02 000:000:000', 4);
insert into tag values('TAG_0001', '2018-01-01 03:02:01 000:000:000', 5);
insert into tag values('TAG_0001', '2018-01-01 03:02:02 000:000:000', 6);For one tag, different values in seconds were input for 3 hours.
Get ROLLUP AVG
Below is the case of getting average of seconds, minutes, hours of tag table.
Mach> SELECT rollup('sec', 1, time) as mtime, avg(value) FROM TAG WHERE name = 'TAG_0001' group by mtime order by mtime;
mtime avg(value)
---------------------------------------------------------------
2018-01-01 01:00:01 000:000:000 1
2018-01-01 01:00:02 000:000:000 2
2018-01-01 01:01:01 000:000:000 3
2018-01-01 01:01:02 000:000:000 4
2018-01-01 01:02:01 000:000:000 5
2018-01-01 01:02:02 000:000:000 6
2018-01-01 02:00:01 000:000:000 1
2018-01-01 02:00:02 000:000:000 2
2018-01-01 02:01:01 000:000:000 3
2018-01-01 02:01:02 000:000:000 4
2018-01-01 02:02:01 000:000:000 5
2018-01-01 02:02:02 000:000:000 6
2018-01-01 03:00:01 000:000:000 1
2018-01-01 03:00:02 000:000:000 2
2018-01-01 03:01:01 000:000:000 3
2018-01-01 03:01:02 000:000:000 4
2018-01-01 03:02:01 000:000:000 5
2018-01-01 03:02:02 000:000:000 6
[18] row(s) selected.
Mach> SELECT rollup('min', 1, time) as mtime, avg(value) FROM TAG WHERE name = 'TAG_0001' group by mtime order by mtime;
mtime avg(value)
---------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 1.5
2018-01-01 01:01:00 000:000:000 3.5
2018-01-01 01:02:00 000:000:000 5.5
2018-01-01 02:00:00 000:000:000 1.5
2018-01-01 02:01:00 000:000:000 3.5
2018-01-01 02:02:00 000:000:000 5.5
2018-01-01 03:00:00 000:000:000 1.5
2018-01-01 03:01:00 000:000:000 3.5
2018-01-01 03:02:00 000:000:000 5.5
[9] row(s) selected.
Mach> SELECT rollup('hour', 1, time) as mtime, avg(value) FROM TAG WHERE name = 'TAG_0001' group by mtime order by mtime;
mtime avg(value)
---------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 3.5
2018-01-01 02:00:00 000:000:000 3.5
2018-01-01 03:00:00 000:000:000 3.5
[3] row(s) selected.Get ROLLUP MIN/MAX Value
Below is the case of getting min/max value of seconds, minutes, hours of tag table. The difference between others, you can get minimum value and maximum value at the same time with just one query.
Mach> SELECT rollup('hour', 1, time) as mtime, min(value), max(value) FROM TAG WHERE name = 'TAG_0001' group by mtime order by mtime;
mtime min(value) max(value)
--------------------------------------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 1 6
2018-01-01 02:00:00 000:000:000 1 6
2018-01-01 03:00:00 000:000:000 1 6
[3] row(s) selected.
Mach> SELECT rollup('min', 1, time) as mtime, min(value), max(value) FROM TAG WHERE name = 'TAG_0001' group by mtime order by mtime;
mtime min(value) max(value)
--------------------------------------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 1 2
2018-01-01 01:01:00 000:000:000 3 4
2018-01-01 01:02:00 000:000:000 5 6
2018-01-01 02:00:00 000:000:000 1 2
2018-01-01 02:01:00 000:000:000 3 4
2018-01-01 02:02:00 000:000:000 5 6
2018-01-01 03:00:00 000:000:000 1 2
2018-01-01 03:01:00 000:000:000 3 4
2018-01-01 03:02:00 000:000:000 5 6
[9] row(s) selected.Get ROLLUP SUM/COUNT
Below is the case of getting sum/count value. Also you can get sum value and count value at the same time with just one query.
Mach> SELECT rollup('min', 1, time) as mtime, sum(value), count(value) FROM TAG WHERE name = 'TAG_0001' group by mtime order by mtime;
mtime sum(value) count(value)
-------------------------------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 3 2
2018-01-01 01:01:00 000:000:000 7 2
2018-01-01 01:02:00 000:000:000 11 2
2018-01-01 02:00:00 000:000:000 3 2
2018-01-01 02:01:00 000:000:000 7 2
2018-01-01 02:02:00 000:000:000 11 2
2018-01-01 03:00:00 000:000:000 3 2
2018-01-01 03:01:00 000:000:000 7 2
2018-01-01 03:02:00 000:000:000 11 2
[9] row(s) selected.Get ROLLUP Sum of Squares
Below is the case of getting sum of squares in rollup.
Mach> SELECT rollup('sec', 1, time) as mtime, SUMSQ(value) FROM tag GROUP BY mtime ORDER BY mtime;
mtime SUMSQ(value)
---------------------------------------------------------------
2018-01-01 01:00:01 000:000:000 1
2018-01-01 01:00:02 000:000:000 4
2018-01-01 01:01:01 000:000:000 9
2018-01-01 01:01:02 000:000:000 16
2018-01-01 01:02:01 000:000:000 25
2018-01-01 01:02:02 000:000:000 36
2018-01-01 02:00:01 000:000:000 1
2018-01-01 02:00:02 000:000:000 4
2018-01-01 02:01:01 000:000:000 9
2018-01-01 02:01:02 000:000:000 16
2018-01-01 02:02:01 000:000:000 25
2018-01-01 02:02:02 000:000:000 36
2018-01-01 03:00:01 000:000:000 1
2018-01-01 03:00:02 000:000:000 4
2018-01-01 03:01:01 000:000:000 9
2018-01-01 03:01:02 000:000:000 16
2018-01-01 03:02:01 000:000:000 25
2018-01-01 03:02:02 000:000:000 36
[18] row(s) selected.
Mach> SELECT rollup('min', 1, time) as mtime, SUMSQ(value) FROM tag GROUP BY mtime ORDER BY mtime;
mtime SUMSQ(value)
---------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 5
2018-01-01 01:01:00 000:000:000 25
2018-01-01 01:02:00 000:000:000 61
2018-01-01 02:00:00 000:000:000 5
2018-01-01 02:01:00 000:000:000 25
2018-01-01 02:02:00 000:000:000 61
2018-01-01 03:00:00 000:000:000 5
2018-01-01 03:01:00 000:000:000 25
2018-01-01 03:02:00 000:000:000 61
[9] row(s) selected.Get ROLLUP FIRST/LAST
Below is an example of obtaining the start and end values provided by Extended Rollup.
Mach> SELECT rollup('min', 1, time) as mtime, FIRST(time, value), LAST(time, value) FROM tag GROUP BY mtime ORDER BY mtime;
mtime FIRST(time, value) LAST(time, value)
--------------------------------------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 1 2
2018-01-01 01:01:00 000:000:000 3 4
2018-01-01 01:02:00 000:000:000 5 6
2018-01-01 02:00:00 000:000:000 1 2
2018-01-01 02:01:00 000:000:000 3 4
2018-01-01 02:02:00 000:000:000 5 6
2018-01-01 03:00:00 000:000:000 1 2
2018-01-01 03:01:00 000:000:000 3 4
2018-01-01 03:02:00 000:000:000 5 6
[9] row(s) selected.
Mach> SELECT rollup('hour', 1, time) as mtime, FIRST(time, value), LAST(time, value) FROM tag GROUP BY mtime ORDER BY mtime;
mtime FIRST(time, value) LAST(time, value)
--------------------------------------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 1 6
2018-01-01 02:00:00 000:000:000 1 6
2018-01-01 03:00:00 000:000:000 1 6
[3] row(s) selected.Grouping at Various Time Intervals
The advantage of the ROLLUP clause is that it is not necessary to intentionally use DATE_BIN() to vary the time interval.
To get the sum of the 3-second interval and the number of data, you can do as follows. Since the example time range is only 0 sec, 1 sec, and 2 sec, it can be seen that they all converge to 0 sec. As a result, it matches the ‘rollup by minute’ query result.
Mach> SELECT rollup('sec', 3, time) as mtime, sum(value), count(value) FROM TAG WHERE name = 'TAG_0001' GROUP BY mtime ORDER BY mtime;
mtime sum(value) count(value)
-------------------------------------------------------------------------------------
2018-01-01 01:00:00 000:000:000 3 2
2018-01-01 01:01:00 000:000:000 7 2
2018-01-01 01:02:00 000:000:000 11 2
2018-01-01 02:00:00 000:000:000 3 2
2018-01-01 02:01:00 000:000:000 7 2
2018-01-01 02:02:00 000:000:000 11 2
2018-01-01 03:00:00 000:000:000 3 2
2018-01-01 03:01:00 000:000:000 7 2
2018-01-01 03:02:00 000:000:000 11 2Rollup of more than 1 day
Day Rollup
Mach> SELECT ROLLUP('day', 10, time, '2023-01-01') AS mtime, COUNT(value) FROM tag WHERE time BETWEEN TO_DATE('2023-05-01') AND TO_DATE('2023-05-31') GROUP BY mtime ORDER BY mtime;
mtime COUNT(value)
--------------------------------------------------------
2023-05-01 00:00:00 000:000:000 10
2023-05-11 00:00:00 000:000:000 10
2023-05-21 00:00:00 000:000:000 10
2023-05-31 00:00:00 000:000:000 1
[4] row(s) selected.Week Rollup
If origin is not specified, it is counted in the range (Thursday-Wednesday). If you want to aggregate in the range (Sunday-Saturday), you must specify the datetime corresponding to Sunday in origin.
Month Rollup
origin should always be specified as the first day of the month (1st day).
Mach> SELECT ROLLUP('month', 2, time) AS mtime, COUNT(value) FROM tag WHERE time BETWEEN to_date('2024-05-01') AND to_date('2024-07-31') GROUP BY mtime ORDER BY mtime;
mtime COUNT(value)
--------------------------------------------------------
2024-05-01 00:00:00 000:000:000 61
2024-07-01 00:00:00 000:000:000 31
[2] row(s) selected.
Mach> SELECT ROLLUP('month', 1, time, '2024-05-05') AS mtime, COUNT(value) FROM tag WHERE time BETWEEN to_date('2024-05-01') AND to_date('2024-07-31') GROUP BY mtime ORDER BY mtime;
mtime COUNT(value)
--------------------------------------------------------
[ERR-02356: Origin must be the first day of the month.]Year Rollup
Mach> SELECT ROLLUP('year', 1, time, '2022-01-01') AS mtime, COUNT(value) FROM tag WHERE time BETWEEN TO_DATE('2022-01-01') AND TO_DATE('2023-12-31') GROUP BY mtime ORDER BY mtime;
mtime COUNT(value)
--------------------------------------------------------
2022-01-01 00:00:00 000:000:000 365
2023-01-01 00:00:00 000:000:000 365
[2] row(s) selected.Using ROLLUP for JSON type
Starting from version 7.5, ROLLUP can be used for JSON types. You can create by adding the JSON PATH and OPERATOR at create statement. A ROLLUP can be created for each PATH in one JSON column.
-- create tag table
CREATE TAG TABLE tag (name VARCHAR(20) PRIMARY KEY, time DATETIME BASETIME, jval JSON);
-- insert data
insert into tag values ('tag-01', '2022-09-01 01:01:01', "{ \"x\": 1, \"y\": 1.1}");
insert into tag values ('tag-01', '2022-09-01 01:01:02', "{ \"x\": 2, \"y\": 1.2}");
insert into tag values ('tag-01', '2022-09-01 01:01:03', "{ \"x\": 3, \"y\": 1.3}");
insert into tag values ('tag-01', '2022-09-01 01:01:04', "{ \"x\": 4, \"y\": 1.4}");
insert into tag values ('tag-01', '2022-09-01 01:01:05', "{ \"x\": 5, \"y\": 1.5}");
insert into tag values ('tag-01', '2022-09-01 01:02:00', "{ \"x\": 6, \"y\": 1.6}");
insert into tag values ('tag-01', '2022-09-01 01:03:00', "{ \"x\": 7, \"y\": 1.7}");
insert into tag values ('tag-01', '2022-09-01 01:04:00', "{ \"x\": 8, \"y\": 1.8}");
insert into tag values ('tag-01', '2022-09-01 01:05:00', "{ \"x\": 9, \"y\": 1.9}");
insert into tag values ('tag-01', '2022-09-01 01:06:00', "{ \"x\": 10, \"y\": 2.0}");
-- create rollup
CREATE ROLLUP _tag_rollup_jval_x_sec ON tag(jval->'$.x') INTERVAL 1 SEC;
CREATE ROLLUP _tag_rollup_jval_y_sec ON tag(jval->'$.y') INTERVAL 1 SEC;You can also use selecting ROLLUP in the same way.
Mach> SELECT rollup('sec', 2, time) as mtime, MIN(jval->'$.x'), MAX(jval->'$.x'), SUM(jval->'$.x'), COUNT(jval->'$.x'), SUMSQ(jval->'$.x') FROM tag GROUP BY mtime ORDER BY mtime;
mtime min(jval->'$.x') max(jval->'$.x') sum(jval->'$.x') count(jval->'$.x') sumsq(jval->'$.x')
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2022-09-01 01:01:00 000:000:000 1 1 1 1 1
2022-09-01 01:01:02 000:000:000 2 3 5 2 13
2022-09-01 01:01:04 000:000:000 4 5 9 2 41
2022-09-01 01:02:00 000:000:000 6 6 6 1 36
2022-09-01 01:03:00 000:000:000 7 7 7 1 49
2022-09-01 01:04:00 000:000:000 8 8 8 1 64
2022-09-01 01:05:00 000:000:000 9 9 9 1 81
2022-09-01 01:06:00 000:000:000 10 10 10 1 100
[8] row(s) selected.
Mach> SELECT rollup('sec', 2, time) as mtime, MIN(jval->'$.y'), MAX(jval->'$.y'), SUM(jval->'$.y'), COUNT(jval->'$.y'), SUMSQ(jval->'$.y') FROM tag GROUP BY mtime ORDER BY mtime;
mtime min(jval->'$.y') max(jval->'$.y') sum(jval->'$.y') count(jval->'$.y') sumsq(jval->'$.y')
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2022-09-01 01:01:00 000:000:000 1.1 1.1 1.1 1 1.21
2022-09-01 01:01:02 000:000:000 1.2 1.3 2.5 2 3.13
2022-09-01 01:01:04 000:000:000 1.4 1.5 2.9 2 4.21
2022-09-01 01:02:00 000:000:000 1.6 1.6 1.6 1 2.56
2022-09-01 01:03:00 000:000:000 1.7 1.7 1.7 1 2.89
2022-09-01 01:04:00 000:000:000 1.8 1.8 1.8 1 3.24
2022-09-01 01:05:00 000:000:000 1.9 1.9 1.9 1 3.61
2022-09-01 01:06:00 000:000:000 2 2 2 1 4
[8] row(s) selected.Last updated on