leewyang commented on code in PR #37734:
URL: https://github.com/apache/spark/pull/37734#discussion_r974626628


##########
python/pyspark/ml/functions.py:
##########
@@ -106,6 +111,167 @@ def array_to_vector(col: Column) -> Column:
     return 
Column(sc._jvm.org.apache.spark.ml.functions.array_to_vector(_to_java_column(col)))
 
 
+def batched(df: pd.DataFrame, batch_size: int = -1) -> Iterator[pd.DataFrame]:
+    """Generator that splits a pandas dataframe/series into batches."""
+    if batch_size <= 0 or batch_size >= len(df):
+        yield df
+    else:
+        # for batch in np.array_split(df, (len(df.index) + batch_size - 1) // 
batch_size):
+        for _, batch in df.groupby(np.arange(len(df)) // batch_size):
+            yield batch
+
+
+def has_tensor_cols(df: pd.DataFrame) -> bool:
+    """Check if input DataFrame contains any tensor-valued columns"""
+    if any(df.dtypes == np.object_):
+        # pd.DataFrame object types can contain different types, e.g. string, 
dates, etc.
+        # so inspect a row and check for array/list type
+        sample = df.iloc[0]
+        return any([isinstance(x, np.ndarray) or isinstance(x, list) for x in 
sample])
+    else:
+        return False
+
+
+def batch_infer_udf(
+    predict_batch_fn: Callable,
+    return_type: DataType = ArrayType(FloatType()),
+    batch_size: int = -1,
+    input_names: list[str] = [],
+    input_tensor_shapes: list[list[int]] = [],
+    **kwargs: Any,
+) -> Callable:
+    """Given a function which loads a model, returns a pandas_udf for 
inferencing over that model.
+
+    This will handle:
+    - conversion of the Spark DataFrame to numpy arrays.
+    - batching of the inputs sent to the model predict() function.
+    - caching of the model and prediction function on the executors.
+
+    This assumes that the `predict_batch_fn` encapsulates all of the necessary 
dependencies for
+    running the model or the Spark executor environment already satisfies all 
runtime requirements.
+
+    When selecting columns in pyspark SQL, users are required to always use 
`struct` for simplicity.

Review Comment:
   Updated the code to support `col` and `str` column selections, so `struct` 
is not a requirement any more.



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