The PageRank class in the hana_ml.algorithms.pal.pagerank module is a model that calculates the rank for each node in a given data set, with optional parameters for damping factor, maximum iterations, stop condition, and thread ratio.
------
Here is a Python code template based on the provided help doc:

```python
from hana_ml.algorithms.pal.pagerank import PageRank
from hana_ml import DataFrame

# Assuming that a connection context to HANA is available
# conn is the connection context

# Create DataFrame for training data
df = DataFrame(conn, 'SELECT * FROM TRAINING_DATA')

# Create a PageRank instance
pr = PageRank(damping=0.85, max_iter=0, tol=1e-6, thread_ratio=0)

# Run the PageRank algorithm
result = pr.run(data=df)

# Collect the result
print(result.collect())
```

Please replace `'SELECT * FROM TRAINING_DATA'` with your actual SQL query to fetch the training data. Also, you need to provide a valid HANA connection context in place of `conn`.