[GitHub] [spark] zhengruifeng commented on a diff in pull request #40535: [SPARK-42907][CONNECT][PYTHON] Implement Avro functions

["zhengruifeng (via GitHub)" <gi...@apache.org>]

zhengruifeng commented on code in PR #40535:
URL: https://github.com/apache/spark/pull/40535#discussion_r1146040349


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python/pyspark/sql/connect/avro/functions.py:
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@@ -0,0 +1,108 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+A collections of builtin avro functions
+"""
+
+from pyspark.sql.connect.utils import check_dependencies
+
+check_dependencies(__name__)
+
+from typing import Dict, Optional, TYPE_CHECKING
+
+from pyspark.sql.avro import functions as PyAvroFunctions
+
+from pyspark.sql.connect.column import Column
+from pyspark.sql.connect.functions import _invoke_function, _to_col, _options_to_col, lit
+
+if TYPE_CHECKING:
+    from pyspark.sql.connect._typing import ColumnOrName
+
+
+def from_avro(
+    data: "ColumnOrName", jsonFormatSchema: str, options: Optional[Dict[str, str]] = None
+) -> Column:
+    if options is None:
+        return _invoke_function("from_avro", _to_col(data), lit(jsonFormatSchema))
+    else:
+        return _invoke_function(
+            "from_avro", _to_col(data), lit(jsonFormatSchema), _options_to_col(options)
+        )
+
+
+from_avro.__doc__ = PyAvroFunctions.from_avro.__doc__
+
+
+def to_avro(data: "ColumnOrName", jsonFormatSchema: str = "") -> Column:
+    if jsonFormatSchema == "":
+        return _invoke_function("to_avro", _to_col(data))
+    else:
+        return _invoke_function("to_avro", _to_col(data), lit(jsonFormatSchema))
+
+
+to_avro.__doc__ = PyAvroFunctions.to_avro.__doc__
+
+
+def _test() -> None:
+    import os
+    import sys
+    from pyspark.testing.utils import search_jar
+
+    avro_jar = search_jar("connector/avro", "spark-avro", "spark-avro")
+
+    if avro_jar is None:
+        print(
+            "Skipping all Avro Python tests as the optional Avro project was "
+            "not compiled into a JAR. To run these tests, "
+            "you need to build Spark with 'build/sbt -Pavro package' or "
+            "'build/mvn -Pavro package' before running this test."
+        )
+        sys.exit(0)
+    else:
+        existing_args = os.environ.get("PYSPARK_SUBMIT_ARGS", "pyspark-shell")
+        jars_args = "--jars %s" % avro_jar
+        os.environ["PYSPARK_SUBMIT_ARGS"] = " ".join([jars_args, existing_args])

Review Comment:
   @HyukjinKwon is it the proper way to add jars in Python Client?
   
   this doctest pass in my local, but it seems the jar is not found in CI



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