airflow spark_jdbc_script 源码

airflow spark_jdbc_script 代码

文件路径：/airflow/providers/apache/spark/hooks/spark_jdbc_script.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 __future__ import annotations

import argparse
from typing import Any

from pyspark.sql import SparkSession

SPARK_WRITE_TO_JDBC: str = "spark_to_jdbc"
SPARK_READ_FROM_JDBC: str = "jdbc_to_spark"


def set_common_options(
    spark_source: Any,
    url: str = 'localhost:5432',
    jdbc_table: str = 'default.default',
    user: str = 'root',
    password: str = 'root',
    driver: str = 'driver',
) -> Any:
    """
    Get Spark source from JDBC connection

    :param spark_source: Spark source, here is Spark reader or writer
    :param url: JDBC resource url
    :param jdbc_table: JDBC resource table name
    :param user: JDBC resource user name
    :param password: JDBC resource password
    :param driver: JDBC resource driver
    """
    spark_source = (
        spark_source.format('jdbc')
        .option('url', url)
        .option('dbtable', jdbc_table)
        .option('user', user)
        .option('password', password)
        .option('driver', driver)
    )
    return spark_source


def spark_write_to_jdbc(
    spark_session: SparkSession,
    url: str,
    user: str,
    password: str,
    metastore_table: str,
    jdbc_table: str,
    driver: Any,
    truncate: bool,
    save_mode: str,
    batch_size: int,
    num_partitions: int,
    create_table_column_types: str,
) -> None:
    """Transfer data from Spark to JDBC source"""
    writer = spark_session.table(metastore_table).write
    # first set common options
    writer = set_common_options(writer, url, jdbc_table, user, password, driver)

    # now set write-specific options
    if truncate:
        writer = writer.option('truncate', truncate)
    if batch_size:
        writer = writer.option('batchsize', batch_size)
    if num_partitions:
        writer = writer.option('numPartitions', num_partitions)
    if create_table_column_types:
        writer = writer.option("createTableColumnTypes", create_table_column_types)

    writer.save(mode=save_mode)


def spark_read_from_jdbc(
    spark_session: SparkSession,
    url: str,
    user: str,
    password: str,
    metastore_table: str,
    jdbc_table: str,
    driver: Any,
    save_mode: str,
    save_format: str,
    fetch_size: int,
    num_partitions: int,
    partition_column: str,
    lower_bound: str,
    upper_bound: str,
) -> None:
    """Transfer data from JDBC source to Spark"""
    # first set common options
    reader = set_common_options(spark_session.read, url, jdbc_table, user, password, driver)

    # now set specific read options
    if fetch_size:
        reader = reader.option('fetchsize', fetch_size)
    if num_partitions:
        reader = reader.option('numPartitions', num_partitions)
    if partition_column and lower_bound and upper_bound:
        reader = (
            reader.option('partitionColumn', partition_column)
            .option('lowerBound', lower_bound)
            .option('upperBound', upper_bound)
        )

    reader.load().write.saveAsTable(metastore_table, format=save_format, mode=save_mode)


def _parse_arguments(args: list[str] | None = None) -> Any:
    parser = argparse.ArgumentParser(description='Spark-JDBC')
    parser.add_argument('-cmdType', dest='cmd_type', action='store')
    parser.add_argument('-url', dest='url', action='store')
    parser.add_argument('-user', dest='user', action='store')
    parser.add_argument('-password', dest='password', action='store')
    parser.add_argument('-metastoreTable', dest='metastore_table', action='store')
    parser.add_argument('-jdbcTable', dest='jdbc_table', action='store')
    parser.add_argument('-jdbcDriver', dest='jdbc_driver', action='store')
    parser.add_argument('-jdbcTruncate', dest='truncate', action='store')
    parser.add_argument('-saveMode', dest='save_mode', action='store')
    parser.add_argument('-saveFormat', dest='save_format', action='store')
    parser.add_argument('-batchsize', dest='batch_size', action='store')
    parser.add_argument('-fetchsize', dest='fetch_size', action='store')
    parser.add_argument('-name', dest='name', action='store')
    parser.add_argument('-numPartitions', dest='num_partitions', action='store')
    parser.add_argument('-partitionColumn', dest='partition_column', action='store')
    parser.add_argument('-lowerBound', dest='lower_bound', action='store')
    parser.add_argument('-upperBound', dest='upper_bound', action='store')
    parser.add_argument('-createTableColumnTypes', dest='create_table_column_types', action='store')
    return parser.parse_args(args=args)


def _create_spark_session(arguments: Any) -> SparkSession:
    return SparkSession.builder.appName(arguments.name).enableHiveSupport().getOrCreate()


def _run_spark(arguments: Any) -> None:
    # Disable dynamic allocation by default to allow num_executors to take effect.
    spark = _create_spark_session(arguments)

    if arguments.cmd_type == SPARK_WRITE_TO_JDBC:
        spark_write_to_jdbc(
            spark,
            arguments.url,
            arguments.user,
            arguments.password,
            arguments.metastore_table,
            arguments.jdbc_table,
            arguments.jdbc_driver,
            arguments.truncate,
            arguments.save_mode,
            arguments.batch_size,
            arguments.num_partitions,
            arguments.create_table_column_types,
        )
    elif arguments.cmd_type == SPARK_READ_FROM_JDBC:
        spark_read_from_jdbc(
            spark,
            arguments.url,
            arguments.user,
            arguments.password,
            arguments.metastore_table,
            arguments.jdbc_table,
            arguments.jdbc_driver,
            arguments.save_mode,
            arguments.save_format,
            arguments.fetch_size,
            arguments.num_partitions,
            arguments.partition_column,
            arguments.lower_bound,
            arguments.upper_bound,
        )


if __name__ == "__main__":  # pragma: no cover
    _run_spark(arguments=_parse_arguments())

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