blob: a7f5e383fa53f717a4aec2af6d01fec5340b53e0 [file] [log] [blame]
#
# 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.sql import SparkSession
spark = SparkSession\
.builder\
.appName("Cloudant Spark SQL Example in Python using dataframes with options")\
.getOrCreate()
cloudant_host = "ACCOUNT.cloudant.com"
cloudant_username = "USERNAME"
cloudant_password = "PASSWORD"
# ***1. Loading dataframe from Cloudant db
df = spark.read.format("org.apache.bahir.cloudant") \
.option("cloudant.host", cloudant_host) \
.option("cloudant.username", cloudant_username) \
.option("cloudant.password", cloudant_password) \
.load("n_airportcodemapping")
df.cache() # persisting in memory
df.printSchema()
df.filter(df._id >= 'CAA').select("_id",'airportName').show()
# ***2.Saving dataframe to Cloudant db
df.filter(df._id >= 'CAA').select("_id",'airportName') \
.write.format("org.apache.bahir.cloudant") \
.option("cloudant.host", cloudant_host) \
.option("cloudant.username", cloudant_username) \
.option("cloudant.password",cloudant_password) \
.option("bulkSize","100") \
.option("createDBOnSave", "true") \
.save("airportcodemapping_df")
df = spark.read.format("org.apache.bahir.cloudant") \
.option("cloudant.host", cloudant_host) \
.option("cloudant.username", cloudant_username) \
.option("cloudant.password", cloudant_password) \
.load("n_flight")
df.printSchema()
total = df.filter(df.flightSegmentId >'AA9') \
.select("flightSegmentId", "scheduledDepartureTime") \
.orderBy(df.flightSegmentId).count()
print ("Total", total, "flights from table")
# ***3. Loading dataframe from Cloudant search index
df = spark.read.format("org.apache.bahir.cloudant") \
.option("cloudant.host",cloudant_host) \
.option("cloudant.username",cloudant_username) \
.option("cloudant.password",cloudant_password) \
.option("index","_design/view/_search/n_flights").load("n_flight")
df.printSchema()
total = df.filter(df.flightSegmentId >'AA9') \
.select("flightSegmentId", "scheduledDepartureTime") \
.orderBy(df.flightSegmentId).count()
print ("Total", total, "flights from index")