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# Author: Gary A. Stafford
# License: MIT
# Arguments Example:
# gs://dataproc-demo-bucket
# ibrd-statement-of-loans-historical-data.csv
# ibrd-summary-large-python
from pyspark.sql import SparkSession
import sys
def main(argv):
storage_bucket = argv[0]
data_file = argv[1]
results_directory = argv[2]
print "Number of arguments: {0} arguments.".format(len(sys.argv))
print "Argument List: {0}".format(str(sys.argv))
spark = SparkSession \
.builder \
.master("yarn") \
.appName('dataproc-python-demo') \
# Defaults to INFO
sc = spark.sparkContext
# Loads CSV file from Google Storage Bucket
df_loans = spark \
.read \
.format("csv") \
.option("header", "true") \
.option("inferSchema", "true") \
.load(storage_bucket + "/" + data_file)
# Creates temporary view using DataFrame
df_loans.withColumnRenamed("Country", "country") \
.withColumnRenamed("Country Code", "country_code") \
.withColumnRenamed("Disbursed Amount", "disbursed") \
.withColumnRenamed("Borrower's Obligation", "obligation") \
.withColumnRenamed("Interest Rate", "interest_rate") \
# Performs basic analysis of dataset
df_disbursement = spark.sql("""
SELECT country, country_code,
format_number(total_disbursement, 0) AS total_disbursement,
format_number(ABS(total_obligation), 0) AS total_obligation,
format_number(avg_interest_rate, 2) AS avg_interest_rate
SELECT country, country_code,
SUM(disbursed) AS total_disbursement,
SUM(obligation) AS total_obligation,
AVG(interest_rate) AS avg_interest_rate
FROM loans
GROUP BY country, country_code
ORDER BY total_disbursement DESC
print "Results:", True)
# Saves results to single CSV file in Google Storage Bucket
df_disbursement.write \
.mode("overwrite") \
.format("parquet") \
.save(storage_bucket + "/" + results_directory)
if __name__ == "__main__":
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