The wpdec function in the hana_ml.algorithms.pal.tsa.wavelet module is a Python wrapper for the PAL multi-level (discrete) wavelet packet transformation, which applies a discrete wavelet transform to time-series data using specified parameters such as wavelet filter, padding method for boundary values, decompose level, order of node, thresholding method, and threshold value.
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Here is the executable code template based on the provided help doc:

```python
from hana_ml.algorithms.pal.tsa.wavelet import wpdec
from hana_ml import DataFrame

# Assuming that connection_context is the connection to the HANA system
data = DataFrame(connection_context, 'SELECT * FROM TIME_SERIES_DATA')

# Apply discrete wavelet transform
wpres = wpdec(
    data=data,
    wavelet='db2',
    key='ID',
    col='VAL',
    boundary='symmetric',
    level=2,
    order='frequency',
    compression=False,
    method='no',
    threshold=1e-9
)

# Print the wavelet packet transformation of data
print(wpres.coeff_.collect())

# Print the decomposition result
print(wpres.stats_.collect())
```

Please replace `'SELECT * FROM TIME_SERIES_DATA'` with your actual SQL query to fetch the time-series data. Also, make sure that the `connection_context` is properly defined and connected to your HANA system.