sdk_python/amaterasu/pyspark/runtime.py

"""
 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 pyspark import SparkContext, SparkConf
from pyspark.sql import SparkSession, DataFrame
from amaterasu.base import BaseAmaContextBuilder, LoaderAmaContext
from .datasets import DatasetManager
from pip._internal import main as pip_main
import os
import sys


# For some reason, the leader passes "_" as the PYSPARK_PYTHON env variable
os.environ['PYSPARK_PYTHON'] = os.environ.get('_') or os.environ.get('PYSPARK_PYTHON') or sys.executable


class AmaContextBuilder(BaseAmaContextBuilder):

    def __init__(self):
        super().__init__()
        try:
            self.spark_conf = spark.conf
        except:
            self.spark_conf = SparkConf()


    def setMaster(self, master_uri) -> "AmaContextBuilder":
        self.spark_conf.setMaster(master_uri)
        return self

    def set(self, key, value) -> "AmaContextBuilder":
        self.spark_conf.set(key, value)
        return self

    def prepare_user_dependencies(self):
        pip_main(["download", "-r", "requirements.txt", '-d', 'job_deps'])
        return [os.path.join('job_deps', fname) for fname in os.listdir('job_deps')]


    def build(self) -> "AmaContext":
        deps_paths = self.prepare_user_dependencies()
        spark = SparkSession.builder.config(conf=self.spark_conf).getOrCreate()
        sc: SparkContext = spark.sparkContext
        for path in deps_paths:
            sc.addPyFile(path)
        return AmaContext(self.ama_conf, sc, spark)


class AmaContext(LoaderAmaContext):

    @classmethod
    def builder(cls) -> AmaContextBuilder:
        return AmaContextBuilder()

    @property
    def dataset_manager(self) -> DatasetManager:
        return self._dataset_manager

    @property
    def sc(self) -> SparkContext:
        return self._sc

    @property
    def spark(self) -> SparkSession:
        return self._spark

    def __init__(self, ama_conf, sc: SparkContext = None, spark: SparkSession = None):
        super(AmaContext, self).__init__(ama_conf)
        self._sc, self._spark = sc, spark
        self._dataset_manager = DatasetManager(ama_conf.datasets, self.spark)

    def get_dataset(self, dataset_name: str) -> DataFrame:
        return self._dataset_manager.load_dataset(dataset_name)

    def persist(self, dataset_name: str, dataset: DataFrame, overwrite: bool = True):
        self._dataset_manager.persist_dataset(dataset_name, dataset, overwrite)