Replace `scalarfn` with the name of your function. This function performs scalar calculations on data blocks. You can configure a value through the parameters in the `resultColumn` structure.
The parameters in the function are defined as follows:
- inputDataBlock: The data block to input.
- resultColumn: The column to output. The column to output.
- resultColumn: The column to output. The column to output.
#### Aggregate Interface
...
...
@@ -197,7 +197,7 @@ The data structure is described as follows:
- The SUdfDataBlock block includes the number of rows (numOfRows) and the number of columns (numCols). udfCols[i] (0 <= i <= numCols-1) indicates that each column is of type SUdfColumn.
- SUdfColumn includes the definition of the data type of the column (colMeta) and the data in the column (colData).
- The member definitions of SUdfColumnMeta are the same as the data type definitions in `taos.h`.
- The data in SUdfColumnData can become longer. varLenCol indicates variable-length data, and fixLenCol indicates fixed-length data.
- The data in SUdfColumnData can become longer. varLenCol indicates variable-length data, and fixLenCol indicates fixed-length data.
- SUdfInterBuf defines the intermediate structure `buffer` and the number of results in the buffer `numOfResult`.
Additional functions are defined in `taosudf.h` to make it easier to work with these structures.
# use inputs.data(i,j) to access python ojbect of location(i,j)
# reduce the inputs and state into new_state.
# use inputs.data(i,j) to access python object of location(i,j)
# serialize new_state into new_state_bytes
return new_state_bytes
return new_state_bytes
def finish(buf: bytes) -> output_type:
#return obj of type outputtype
#return obj of type outputtype
```
Note: aggregate UDF requires init(), destroy(), start(), reduce() and finish() to be impemented. start() generates the initial result in buffer, then the input data is divided into multiple row data blocks, reduce() is invoked for each data block `inputs` and intermediate `buf`, finally finish() is invoked to generate final result from the intermediate result `buf`.
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...
@@ -844,8 +847,9 @@ select * from ins_functions \G;
SHOWfunctions;
DROPFUNCTIONfunction_name;
```
### More Python UDF Samples
#### Scalar Function [pybitand](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/pybitand.py)
The `pybitand` function implements bitwise addition for multiple columns. If there is only one column, the column is returned. The `pybitand` function ignores null values.
system sh/cfg.sh -n dnode1 -c filterScalarMode -v 1
system sh/exec.sh -n dnode1 -s start
sql connect
sql drop database if exists db1;
sql create database if not exists db1;
sql use db1;
sql create stable sta (ts timestamp, f1 double, f2 binary(200)) tags(t1 int);
sql create table tba1 using sta tags(1);
sql insert into tba1 values ('2022-04-26 15:15:01', 1.0, "a");
sql insert into tba1 values ('2022-04-26 15:15:02', 2.0, "b");
sql insert into tba1 values ('2022-04-26 15:15:04', 4.0, "b");
sql insert into tba1 values ('2022-04-26 15:15:05', 5.0, "b");
sql select last_row(*) from sta where ts >= 1678901803783 and ts <= 1678901803783 and _c0 <= 1678901803782 interval(10d,8d) fill(linear) order by _wstart desc;
