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pyspark-reducebykey.py
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pyspark-reducebykey.py
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# cevheri
# 2020
# NYC Open Data
# Fire Incident Dispatch Data
# The Fire Incident Dispatch Data file contains data that is generated by the
# Starfire Computer Aided Dispatch System. The data spans from the time
# the incident is created in the system to the time the incident is closed in the system.
# It covers information about the incident as it relates to the assignment
# of resources and the Fire Department’s response to the emergency.
# To protect personal identifying information in accordance with the Health Insurance Portability
# and Accountability Act (HIPAA), specific locations of incidents are not included
# and have been aggregated to a higher level of detail.
from pyspark import SparkConf, SparkContext
import sys
import os
from operator import add
os.environ['SPARK_HOME'] = "/home/cevher/apps/spark-3.0.1-bin-hadoop2.7"
# os.environ['HADOOP_HOME'] = "/home/cevher/app/spark-3.0.1-bin-hadoop2.7/hadoop"
sys.path.append("/home/cevher/apps/spark-3.0.1-bin-hadoop2.7/python")
sys.path.append("/home/cevher/apps/spark-3.0.1-bin-hadoop2.7/python/lib")
if __name__ == '__main__':
conf = SparkConf().setMaster("local").setAppName("reduceByKey")
sc = SparkContext(conf=conf)
def parse_line(line):
fields = line.split(',')
in_class = str(fields[15])
in_date = str(fields[1][:10])
return in_date, in_class
def remove_header(lines):
header = lines.first() # extract header
return lines.filter(lambda row: row != header) # filter out header
lines = sc.textFile("Fire_Incident_Dispatch_Data.csv") # all data
data = remove_header(lines)
rdd = data.map(parse_line)
print(rdd)
rdd1 = rdd.map(lambda x: (x, 1)).reduceByKey(add)
result = rdd1.collect()
for row in result:
print(row)