# -*- coding: utf-8 -*-
#
# 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 argparse
from pyspark.sql import SparkSession
[docs]def set_common_options(spark_source,
url='localhost:5432',
jdbc_table='default.default',
user='root',
password='root',
driver='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
[docs]def spark_write_to_jdbc(spark, url, user, password, metastore_table, jdbc_table, driver,
truncate, save_mode, batch_size, num_partitions,
create_table_column_types):
writer = spark \
.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)
[docs]def spark_read_from_jdbc(spark, url, user, password, metastore_table, jdbc_table, driver,
save_mode, save_format, fetch_size, num_partitions,
partition_column, lower_bound, upper_bound):
# first set common options
reader = set_common_options(spark.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)
if __name__ == "__main__": # pragma: no cover
# parse the parameters
[docs] 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')
arguments = parser.parse_args()
# Disable dynamic allocation by default to allow num_executors to take effect.
spark = SparkSession.builder \
.appName(arguments.name) \
.enableHiveSupport() \
.getOrCreate()
if arguments.cmd_type == "spark_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 == "jdbc_to_spark":
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)