ueshin commented on code in PR #41948:
URL: https://github.com/apache/spark/pull/41948#discussion_r1267138618
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sql/core/src/main/scala/org/apache/spark/sql/execution/python/UserDefinedPythonFunction.scala:
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@@ -91,3 +138,123 @@ case class UserDefinedPythonTableFunction(
Dataset.ofRows(session, udtf)
}
}
+
+object UserDefinedPythonTableFunction {
+
+ private[this] val workerModule = "pyspark.sql.worker.analyze_udtf"
+
+ /**
+ * Runs the Python UDTF's `analyze` static method.
+ *
+ * When the Python UDTF is defined without a static return type,
+ * the analyze will call this while resolving table-valued functions.
+ *
+ * This expects the Python UDTF to have `analyze` static method that take
arguments:
+ *
+ * - The number and order of arguments are the same as the UDTF inputs
+ * - Each argument is an `AnalyzeArgument`, containing:
+ * - data_type: DataType
+ * - value: Any: if the argument is foldable; otherwise None
+ * - is_table: bool: True if the argument is TABLE
+ *
+ * and that return an `AnalyzeResult`.
+ *
+ * It serializes/deserializes the data types via JSON,
+ * and the values for the case the argument is foldable are pickled.
+ *
+ * `AnalysisException` with the error class
"TABLE_VALUED_FUNCTION_FAILED_TO_ANALYZE_IN_PYTHON"
+ * will be thrown when an exception is raised in Python.
+ */
+ def analyzeInPython(
+ tableArgs: Seq[Boolean])(func: PythonFunction, exprs: Seq[Expression]):
StructType = {
Review Comment:
Once it's analyzed, it will be `PythonUDTF` with the returned fixed schema.
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