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Posted to reviews@spark.apache.org by "WeichenXu123 (via GitHub)" <gi...@apache.org> on 2023/06/06 12:32:49 UTC
[GitHub] [spark] WeichenXu123 opened a new pull request, #41478: [WIP][SPARK-43981][PYTHON][ML] Basic saving / loading implementation for ML on spark connect
WeichenXu123 opened a new pull request, #41478:
URL: https://github.com/apache/spark/pull/41478
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[GitHub] [spark] WeichenXu123 commented on a diff in pull request #41478: [WIP][SPARK-43981][PYTHON][ML] Basic saving / loading implementation for ML on spark connect
Posted by "WeichenXu123 (via GitHub)" <gi...@apache.org>.
WeichenXu123 commented on code in PR #41478:
URL: https://github.com/apache/spark/pull/41478#discussion_r1222997971
##########
python/pyspark/mlv2/io_utils.py:
##########
@@ -0,0 +1,159 @@
+#
+# 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.
+#
+
+import json
+import os
+import time
+from typing import Any, Dict, Optional
+from pyspark.errors import PySparkNotImplementedError, PySparkRuntimeError
+from pyspark.util import VersionUtils
+
+from pyspark import __version__ as pyspark_version
Review Comment:
For new pyspark ML module, I think we should regard it as a client side package so using client side pyspark version should be fine. Pyspark server side just runs wrapped python UDF which is unaware of concrete ML algorithm logic.
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[GitHub] [spark] WeichenXu123 closed pull request #41478: [SPARK-43981][PYTHON][ML] Basic saving / loading implementation for ML on spark connect
Posted by "WeichenXu123 (via GitHub)" <gi...@apache.org>.
WeichenXu123 closed pull request #41478: [SPARK-43981][PYTHON][ML] Basic saving / loading implementation for ML on spark connect
URL: https://github.com/apache/spark/pull/41478
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[GitHub] [spark] WeichenXu123 commented on a diff in pull request #41478: [WIP][SPARK-43981][PYTHON][ML] Basic saving / loading implementation for ML on spark connect
Posted by "WeichenXu123 (via GitHub)" <gi...@apache.org>.
WeichenXu123 commented on code in PR #41478:
URL: https://github.com/apache/spark/pull/41478#discussion_r1228182306
##########
python/pyspark/mlv2/io_utils.py:
##########
@@ -0,0 +1,159 @@
+#
+# 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.
+#
+
+import json
+import os
+import time
+from typing import Any, Dict, Optional
+from pyspark.errors import PySparkNotImplementedError, PySparkRuntimeError
+from pyspark.util import VersionUtils
+
+from pyspark import __version__ as pyspark_version
+
+
+_META_DATA_FILE_NAME = "metadata.json"
+
+
+def _get_metadata_to_save(
+ instance: "Params",
+ extra_metadata: Optional[Dict[str, Any]] = None,
+) -> str:
+ """
+ Extract metadata of Estimator / Transformer / Model / Evaluator instance.
+ """
+ uid = instance.uid
+ cls = instance.__module__ + "." + instance.__class__.__name__
+
+ # User-supplied param values
+ params = instance._paramMap
+ json_params = {}
+ for p in params:
+ json_params[p.name] = params[p]
+
+ # Default param values
+ json_default_params = {}
+ for p in instance._defaultParamMap:
+ json_default_params[p.name] = instance.json_default_params[p]
+
+ metadata = {
+ "class": cls,
+ "timestamp": int(round(time.time() * 1000)),
+ "sparkVersion": pyspark_version,
+ "uid": uid,
+ "paramMap": json_params,
+ "defaultParamMap": json_default_params,
+ "type": "spark_connect",
+ }
+ if extra_metadata is not None:
+ metadata.update(extra_metadata)
+
+ return metadata
+
+
+def _get_class(clazz: str) -> Any:
+ """
+ Loads Python class from its name.
+ """
+ parts = clazz.split(".")
+ module = ".".join(parts[:-1])
+ m = __import__(module, fromlist=[parts[-1]])
+ return getattr(m, parts[-1])
+
+
+class ParamsReadWrite:
+ """
+ The base interface Estimator / Transformer / Model / Evaluator needs to inherit
+ for supporting saving and loading.
+ """
+
+ def _get_metadata(self) -> Any:
+ """
+ Returns metadata of the object as a JSON object.
+ """
+ return _get_metadata_to_save(self)
+
+ # TODO: support saving to cloud storage file system.
+ def saveToLocal(self, path):
+ """
+ Save model to provided local path.
+ """
+ metadata = self._get_metadata()
+
+ os.makedirs(path)
+ with open(os.path.join(path, _META_DATA_FILE_NAME), "w") as fp:
+ json.dump(metadata, fp)
+
+ # TODO: support loading from cloud storage file system.
+ @classmethod
+ def loadFromLocal(cls, path):
+ """
+ Load model from provided local path.
+ """
+ with open(os.path.join(path, _META_DATA_FILE_NAME), "r") as fp:
+ metadata = json.load(fp)
+
+ if "type" not in metadata or metadata["type"] != "spark_connect":
+ raise RuntimeError("The model is not saved by spark ML under spark connect mode.")
+
+ class_name = metadata["class"]
+ instance = _get_class(class_name)()
+ instance._resetUid(metadata["uid"])
+
+ # Set user-supplied param values
+ for paramName in metadata["paramMap"]:
+ param = instance.getParam(paramName)
+ paramValue = metadata["paramMap"][paramName]
+ instance.set(param, paramValue)
+
+ for paramName in metadata["defaultParamMap"]:
+ paramValue = metadata["defaultParamMap"][paramName]
+ instance._setDefault(**{paramName: paramValue})
+
+ return instance
+
+
+class ModelReadWrite:
Review Comment:
See my latest code, "ModelReadWrite" inherits from "ParamsReadWrite"
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[GitHub] [spark] zhengruifeng commented on a diff in pull request #41478: [WIP][SPARK-43981][PYTHON][ML] Basic saving / loading implementation for ML on spark connect
Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng commented on code in PR #41478:
URL: https://github.com/apache/spark/pull/41478#discussion_r1222390649
##########
python/pyspark/mlv2/io_utils.py:
##########
@@ -0,0 +1,159 @@
+#
+# 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.
+#
+
+import json
+import os
+import time
+from typing import Any, Dict, Optional
+from pyspark.errors import PySparkNotImplementedError, PySparkRuntimeError
+from pyspark.util import VersionUtils
+
+from pyspark import __version__ as pyspark_version
Review Comment:
on python client, this version info may be different with the one `spark.version` from the sever side
##########
python/pyspark/mlv2/io_utils.py:
##########
@@ -0,0 +1,159 @@
+#
+# 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.
+#
+
+import json
+import os
+import time
+from typing import Any, Dict, Optional
+from pyspark.errors import PySparkNotImplementedError, PySparkRuntimeError
+from pyspark.util import VersionUtils
+
+from pyspark import __version__ as pyspark_version
+
+
+_META_DATA_FILE_NAME = "metadata.json"
+
+
+def _get_metadata_to_save(
+ instance: "Params",
+ extra_metadata: Optional[Dict[str, Any]] = None,
+) -> str:
+ """
+ Extract metadata of Estimator / Transformer / Model / Evaluator instance.
+ """
+ uid = instance.uid
+ cls = instance.__module__ + "." + instance.__class__.__name__
+
+ # User-supplied param values
+ params = instance._paramMap
+ json_params = {}
+ for p in params:
+ json_params[p.name] = params[p]
+
+ # Default param values
+ json_default_params = {}
+ for p in instance._defaultParamMap:
+ json_default_params[p.name] = instance.json_default_params[p]
+
+ metadata = {
+ "class": cls,
+ "timestamp": int(round(time.time() * 1000)),
+ "sparkVersion": pyspark_version,
+ "uid": uid,
+ "paramMap": json_params,
+ "defaultParamMap": json_default_params,
+ "type": "spark_connect",
+ }
+ if extra_metadata is not None:
+ metadata.update(extra_metadata)
+
+ return metadata
+
+
+def _get_class(clazz: str) -> Any:
+ """
+ Loads Python class from its name.
+ """
+ parts = clazz.split(".")
+ module = ".".join(parts[:-1])
+ m = __import__(module, fromlist=[parts[-1]])
+ return getattr(m, parts[-1])
+
+
+class ParamsReadWrite:
+ """
+ The base interface Estimator / Transformer / Model / Evaluator needs to inherit
+ for supporting saving and loading.
+ """
+
+ def _get_metadata(self) -> Any:
+ """
+ Returns metadata of the object as a JSON object.
+ """
+ return _get_metadata_to_save(self)
+
+ # TODO: support saving to cloud storage file system.
+ def saveToLocal(self, path):
+ """
+ Save model to provided local path.
+ """
+ metadata = self._get_metadata()
+
+ os.makedirs(path)
+ with open(os.path.join(path, _META_DATA_FILE_NAME), "w") as fp:
+ json.dump(metadata, fp)
+
+ # TODO: support loading from cloud storage file system.
+ @classmethod
+ def loadFromLocal(cls, path):
+ """
+ Load model from provided local path.
+ """
+ with open(os.path.join(path, _META_DATA_FILE_NAME), "r") as fp:
+ metadata = json.load(fp)
+
+ if "type" not in metadata or metadata["type"] != "spark_connect":
+ raise RuntimeError("The model is not saved by spark ML under spark connect mode.")
+
+ class_name = metadata["class"]
+ instance = _get_class(class_name)()
+ instance._resetUid(metadata["uid"])
+
+ # Set user-supplied param values
+ for paramName in metadata["paramMap"]:
+ param = instance.getParam(paramName)
+ paramValue = metadata["paramMap"][paramName]
+ instance.set(param, paramValue)
+
+ for paramName in metadata["defaultParamMap"]:
+ paramValue = metadata["defaultParamMap"][paramName]
+ instance._setDefault(**{paramName: paramValue})
+
+ return instance
+
+
+class ModelReadWrite:
Review Comment:
`ModelReadWrite` will not deal with the parameters?
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