| # | |
| # 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. | |
| # | |
| from typing import Set, Iterable | |
| import json | |
| import base64 | |
| import cloudpickle | |
| import requests | |
| import subprocess | |
| import time | |
| from pywy.core.platform import Platform | |
| from pywy.core.functions import ChainedFunctions | |
| from pywy.graph.graph import WayangGraph | |
| from pywy.graph.types import WGraphOfVec, NodeOperator, NodeVec | |
| from pywy.types import get_java_type, NDimArray, ndim_from_type | |
| from pywy.operators import SinkOperator, UnaryToUnaryOperator, SourceUnaryOperator | |
| class JSONSerializer: | |
| id_table: Iterable[int] | |
| def __init__(self, id_table: Iterable[int]): | |
| self.id_table = id_table | |
| def serialize(self, operator): | |
| json_operator = {} | |
| json_operator["id"] = self.id_table[operator] | |
| json_operator["operatorName"] = operator.json_name | |
| json_operator["cat"] = operator.cat | |
| if operator.cat != "input": | |
| json_operator["input"] = list(map(lambda x: self.id_table[x], operator.inputOperator)) | |
| else: | |
| json_operator["input"] = [] | |
| if operator.cat != "output": | |
| json_operator["output"] = list(map(lambda x: self.id_table[x], operator.outputOperator)) | |
| else: | |
| json_operator["output"] = [] | |
| json_operator["data"] = {} | |
| if hasattr(operator, "input_type") and operator.input_type is not None: | |
| json_operator["data"]["inputType"] = ndim_from_type(operator.input_type).to_json() | |
| if hasattr(operator, "output_type") and operator.output_type is not None: | |
| json_operator["data"]["outputType"] = ndim_from_type(operator.output_type).to_json() | |
| if operator.json_name == "filter": | |
| json_operator["data"]["udf"] = base64.b64encode(cloudpickle.dumps(operator.use_predicate)).decode('utf-8') | |
| elif operator.json_name == "reduceBy": | |
| json_operator["data"]["keyUdf"] = base64.b64encode(cloudpickle.dumps(operator.key_function)).decode('utf-8') | |
| json_operator["data"]["udf"] = base64.b64encode(cloudpickle.dumps(operator.reduce_function)).decode('utf-8') | |
| elif operator.json_name == "join": | |
| json_operator["data"]["thisKeyUdf"] = base64.b64encode(cloudpickle.dumps(operator.this_key_function)).decode('utf-8') | |
| json_operator["data"]["thatKeyUdf"] = base64.b64encode(cloudpickle.dumps(operator.that_key_function)).decode('utf-8') | |
| elif operator.json_name == "cartesian": | |
| del json_operator["data"] | |
| elif operator.json_name == "dlTraining": | |
| json_operator["data"]["model"] = {"modelType": "DLModel", "op": operator.model.get_out().to_dict()} | |
| json_operator["data"]["option"] = operator.option.to_dict() | |
| else: | |
| if hasattr(operator, "get_udf"): | |
| json_operator["data"]["udf"] = base64.b64encode(cloudpickle.dumps(operator.get_udf)).decode('utf-8') | |
| if hasattr(operator, "path"): | |
| json_operator["data"]["filename"] = operator.path | |
| if hasattr(operator, "projection"): | |
| json_operator["data"]["projection"] = operator.projection | |
| if hasattr(operator, "column_names"): | |
| json_operator["data"]["column_names"] = operator.column_names | |
| return json_operator | |
| def serialize_pipeline(self, pipeline): | |
| assert len(pipeline) > 0 | |
| json_operator = {} | |
| json_operator["id"] = self.id_table[pipeline[0]] | |
| json_operator["operatorName"] = "mapPartitions" | |
| json_operator["cat"] = "unary" | |
| json_operator["data"] = {} | |
| json_operator["input"] = list(map(lambda x: self.id_table[x], pipeline[0].inputOperator)) | |
| json_operator["output"] = list(map(lambda x: self.id_table[x], pipeline[-1].outputOperator)) | |
| if len(pipeline) == 1: | |
| return self.serialize(pipeline[0]) | |
| chainedUdfs = ChainedFunctions() | |
| for operator in pipeline: | |
| self.id_table[operator] = json_operator["id"] | |
| if hasattr(operator, "get_udf"): | |
| chainedUdfs.add_function(operator.get_udf) | |
| json_operator["data"]["udf"] = base64.b64encode(cloudpickle.dumps(chainedUdfs.execute)).decode('utf-8') | |
| return json_operator |