Hi Bryan, Thanks for bringing this up.
For questions 1 and 2, I think FFT/DFT can be provided as built-in table-valued functions in the table model. Their semantics naturally fit the TVF abstraction, since a time-ordered sequence is transformed into multiple frequency-domain result rows. For question 3, I think it would be helpful to do some further research before finalizing the parameters and output schema. As far as I know, MATLAB and Python's SciPy both provide similar FFT/DFT functions, and their APIs may be useful references. I have not looked into how other databases expose this kind of functionality yet. It may be worth checking both these library functions and other databases to see what inputs they require and what outputs they return, then decide what design best fits IoTDB's table model. Best, Yuan On Mon, Jun 8, 2026 at 3:37 PM Bryan Yang <[email protected]> wrote: > Hi IoTDB community, > > I would like to discuss a possible feature for the IoTDB table model: > adding built-in FFT and DFT functions for time-series frequency-domain > analysis. > > FFT stands for Fast Fourier Transform, and DFT stands for Discrete Fourier > Transform. Both are used to transform time-domain data into > frequency-domain data. FFT is essentially a fast algorithm for computing > DFT, so I think these two functions can be designed together, sharing > similar parameters, output schema, and test cases. > > For IoTDB, this could be useful for scenarios such as sensor vibration > analysis, dominant frequency detection, and periodic signal analysis. > Preliminary Analysis > > After some preliminary analysis, I think FFT/DFT are more suitable as > table-valued functions (TVFs), rather than scalar functions or window > functions. > > The reason is that FFT/DFT do not work as one-row-in, one-row-out scalar > functions like abs(), sin(), or round(). They also do not aggregate > multiple rows into a single value like avg() or sum(). > > Instead, their semantics are: > > a time-ordered sequence -> multiple frequency points > > Possible SQL Form > > SELECT * > FROM FFT( > DATA => ( > SELECT time, device_id, value > FROM sensor > ) PARTITION BY device_id ORDER BY time, > VALUE => 'value' > ); > > This means that the input table is partitioned by device_id, each partition > is ordered by time, and the value column is transformed into > frequency-domain results. > > Similarly, DFT could use the same form: > > SELECT * > FROM DFT( > DATA => ( > SELECT time, value > FROM sensor > WHERE device_id = 'd1' > ) ORDER BY time, > VALUE => 'value' > ); > > Possible Output Schema > > A possible output schema could be: > > frequency_index, frequency(optional), real, imag, amplitude, phase > > Here, frequency_index, real, and imag are the core results of FFT/DFT. > amplitude and phase can be derived from real/imag and may be useful for > analysis. > > The frequency column would require the user to provide a sample rate or > sample interval; otherwise, only frequency_index can be returned. > Existing Related Work > > I also noticed that IoTDB already has FFT-related UDF support in the > library-udf module. This proposal focuses on whether FFT/DFT should be > provided as built-in functions in the table model, and whether TVF is the > right abstraction. > Questions > > I would appreciate your feedback on this direction, especially: > > 1. > > Whether FFT/DFT are suitable as built-in functions in the table model. > 2. > > Whether TVF is the right function type for them. > 3. > > What the expected parameters and output schema should be. > > Best regards, Bryan Yang（杨易达） >
