HyukjinKwon commented on code in PR #41316:
URL: https://github.com/apache/spark/pull/41316#discussion_r1214001988
##########
python/pyspark/worker.py:
##########
@@ -456,6 +456,54 @@ def assign_cols_by_name(runner_conf):
)
+def read_udtf(pickleSer, infile, eval_type):
+ num_udtfs = read_int(infile)
+ if num_udtfs != 1:
+ raise RuntimeError("Got more than 1 UDTF")
+
+ # See `PythonUDFRunner.writeUDFs`.
+ num_arg = read_int(infile)
+ arg_offsets = [read_int(infile) for _ in range(num_arg)]
+ num_chained_funcs = read_int(infile)
+ if num_chained_funcs != 1:
+ raise RuntimeError("Got more than 1 chained UDTF")
+
+ handler, return_type = read_command(pickleSer, infile)
+ if not isinstance(handler, type):
+ raise RuntimeError(f"UDTF handler must be a class, but got
{type(handler)}.")
+
+ # Instantiate the UDTF class.
+ try:
+ udtf = handler()
+ except Exception as e:
+ raise RuntimeError(f"Failed to init the UDTF handler: {str(e)}") from
None
+
+ # Wrap the eval method.
+ if not hasattr(udtf, "eval"):
+ raise RuntimeError("Python UDTF must implement the eval method.")
+
+ def wrap_udtf(f, return_type):
+ if return_type.needConversion():
+ toInternal = return_type.toInternal
+ return lambda *a: map(toInternal, f(*a))
+ else:
+ return lambda *a: f(*a)
+
+ f = wrap_udtf(getattr(udtf, "eval"), return_type)
+
+ def mapper(a):
+ results = tuple(f(*[a[o] for o in arg_offsets]))
+ return results
+
+ # Return an iterator of iterators.
+ def func(_, it):
+ return map(mapper, it)
+
+ ser = BatchedSerializer(CPickleSerializer(), 100)
Review Comment:
no reason as far as I know. I think we picked this number like 10 years ago.
BTW, we should better use Arrow one here.
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