Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/7453#discussion_r35819857
--- Diff: python/pyspark/sql/context.py ---
@@ -277,6 +277,59 @@ def applySchema(self, rdd, schema):
return self.createDataFrame(rdd, schema)
+ def _createFromRDD(self, rdd, schema, samplingRatio):
+ if schema is None or isinstance(schema, (list, tuple)):
+ struct = self._inferSchema(rdd, samplingRatio)
+ converter = _create_converter(struct)
+ rdd = rdd.map(converter)
+ if isinstance(schema, (list, tuple)):
+ for i, name in enumerate(schema):
+ struct.fields[i].name = name
+ struct.names[i] = name
+ schema = struct
+
+ elif isinstance(schema, StructType):
+ # take the first few rows to verify schema
+ rows = rdd.take(10)
+ for row in rows:
+ _verify_type(row, schema)
+
+ else:
+ raise TypeError("schema should be StructType or list or None")
+
+ # convert python objects to sql data
+ rdd = rdd.map(schema.toInternal)
+ return rdd, schema
+
+ def _createFromLocal(self, data, schema):
+ if has_pandas and isinstance(data, pandas.DataFrame):
+ if schema is None:
+ schema = [str(x) for x in data.columns]
+ data = [r.tolist() for r in data.to_records(index=False)]
+
+ # make sure data could consumed multiple times
+ if not isinstance(data, list):
+ data = list(data)
+
+ if schema is None or isinstance(schema, (list, tuple)):
+ struct = self._inferSchemaFromList(data)
+ if isinstance(schema, (list, tuple)):
+ for i, name in enumerate(schema):
+ struct.fields[i].name = name
+ struct.names[i] = name
+ schema = struct
+
+ elif isinstance(schema, StructType):
+ for row in data:
+ _verify_type(row, schema)
+
+ else:
+ raise TypeError("schema should be StructType or list or None")
--- End diff --
ditto, include input `schema` in the error message
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