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Added sys path to guarantee imports | Added SparkConf to all files#7

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Merged
jleetutorial merged 2 commits intomasterfrompedro-changes-path
Feb 4, 2018
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29 changes: 14 additions & 15 deletionsadvanced/accumulator/StackOverFlowSurvey.py
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@@ -1,25 +1,24 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

def filterResponseFromCanada(response, total, missingSalaryMidPoint):
splits = Utils.COMMA_DELIMITER.split(response)
total.add(1)
if not splits[14]:
missingSalaryMidPoint.add(1)
return splits[2] == "Canada"

if __name__ == "__main__":
sc = SparkContext("local", "StackOverFlowSurvey")
sc.setLogLevel("ERROR")

conf = SparkConf().setAppName('StackOverFlowSurvey').setMaster("local[*]")
sc = SparkContext(conf = conf)
total = sc.accumulator(0)
missingSalaryMidPoint = sc.accumulator(0)

responseRDD = sc.textFile("in/2016-stack-overflow-survey-responses.csv")

responseFromCanada = responseRDD.filter(lambda response: \
filterResponseFromCanada(response, total, missingSalaryMidPoint))
def filterResponseFromCanada(response):
splits = Utils.COMMA_DELIMITER.split(response)
total.add(1)
if not splits[14]:
missingSalaryMidPoint.add(1)
return splits[2] == "Canada"

responseFromCanada = responseRDD.filter(filterResponseFromCanada)
print("Count of responses from Canada: {}".format(responseFromCanada.count()))
print("Total count of responses: {}".format(total.value))
print("Count of responses missing salary middle point: {}".format(missingSalaryMidPoint.value))
print("Count of responses missing salary middle point: {}" \
.format(missingSalaryMidPoint.value))
27 changes: 13 additions & 14 deletionsadvanced/accumulator/StackOverFlowSurveyFollowUp.py
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@@ -1,26 +1,25 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

def filterResponseFromCanada(response, total, missingSalaryMidPoint, processedBytes):
processedBytes.add(len(response.encode('utf-8')))
splits = Utils.COMMA_DELIMITER.split(response)
total.add(1)
if not splits[14]:
missingSalaryMidPoint.add(1)
return splits[2] == "Canada"

if __name__ == "__main__":
sc =SparkContext("local", "StackOverFlowSurvey")
sc.setLogLevel("ERROR")
conf =SparkConf().setAppName('StackOverFlowSurvey').setMaster("local[*]")
sc = SparkContext(conf = conf)

total = sc.accumulator(0)
missingSalaryMidPoint = sc.accumulator(0)
processedBytes = sc.accumulator(0)

responseRDD = sc.textFile("in/2016-stack-overflow-survey-responses.csv")

responseFromCanada = responseRDD.filter(lambda response: \
filterResponseFromCanada(response, total, missingSalaryMidPoint, processedBytes))
def filterResponseFromCanada(response):
processedBytes.add(len(response.encode('utf-8')))
splits = Utils.COMMA_DELIMITER.split(response)
total.add(1)
if not splits[14]:
missingSalaryMidPoint.add(1)
return splits[2] == "Canada"
responseFromCanada = responseRDD.filter(filterResponseFromCanada)

print("Count of responses from Canada: {}".format(responseFromCanada.count()))
print("Number of bytes processed: {}".format(processedBytes.value))
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18 changes: 10 additions & 8 deletionsadvanced/broadcast/UkMakerSpaces.py
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@@ -1,19 +1,21 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

def getPostPrefix(line: str):
splits = Utils.COMMA_DELIMITER.split(line)
postcode = splits[4]
return None if not postcode else postcode.split(" ")[0]

def loadPostCodeMap():
lines = open("in/uk-postcode.csv", "r").read().split("\n")
splitsForLines = [Utils.COMMA_DELIMITER.split(line) for line in lines if line != ""]
return {splits[0]: splits[7] for splits in splitsForLines}

def getPostPrefix(line: str):
splits = Utils.COMMA_DELIMITER.split(line)
postcode = splits[4]
return None if not postcode else postcode.split(" ")[0]

if __name__ == "__main__":
sc =SparkContext("local", "UkMakerSpaces")
sc.setLogLevel("ERROR")
conf =SparkConf().setAppName('UkMakerSpaces').setMaster("local[*]")
sc = SparkContext(conf = conf)

postCodeMap = sc.broadcast(loadPostCodeMap())

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22 changes: 12 additions & 10 deletionsadvanced/broadcast/UkMakerSpacesWithoutBroadcast.py
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@@ -1,26 +1,28 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

def getPostPrefixes(line: str):
postcode = Utils.COMMA_DELIMITER.split(line)[4]
cleanedPostCode = postcode.replace("\\s+", "")
return [cleanedPostCode[0:i] for i in range(0,len(cleanedPostCode)+1)]

def loadPostCodeMap():
lines = open("in/uk-postcode.csv", "r").read().split("\n")
splitsForLines = [Utils.COMMA_DELIMITER.split(line) for line in lines if line != ""]
return {splits[0]: splits[7] for splits in splitsForLines}

def getPostPrefix(line: str):
splits = Utils.COMMA_DELIMITER.split(line)
postcode = splits[4]
return None if not postcode else postcode.split(" ")[0]

if __name__ == "__main__":
sc =SparkContext("local", "UkMakerSpaces")
sc.setLogLevel("ERROR")
conf =SparkConf().setAppName('UkMakerSpaces').setMaster("local[*]")
sc = SparkContext(conf = conf)
postCodeMap = loadPostCodeMap()
makerSpaceRdd = sc.textFile("in/uk-makerspaces-identifiable-data.csv")

regions = makerSpaceRdd \
.filter(lambda line: Utils.COMMA_DELIMITER.split(line)[0] != "Timestamp") \
.map(lambda line:next((postCodeMap[prefix] for prefix in getPostPrefixes(line) \
ifprefix in postCodeMap),"Unknow"))
.map(lambda line: postCodeMap[getPostPrefix(line)] \
ifgetPostPrefix(line) in postCodeMap else"Unknow")

for region, count in regions.countByValue().items():
print("{} : {}".format(region, count))
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@@ -1,9 +1,8 @@
from pyspark import SparkContext
from pyspark import SparkContext, SparkConf

if __name__ == "__main__":

sc = SparkContext("local", "AverageHousePrice")
sc.setLogLevel("ERROR")
conf = SparkConf().setAppName("AverageHousePrice").setMaster("local")
sc = SparkContext(conf = conf)

lines = sc.textFile("in/RealEstate.csv")
cleanedLines = lines.filter(lambda line: "Bedrooms" not in line)
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@@ -1,24 +1,26 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from pairRdd.aggregation.reducebykey.housePrice.AvgCount import AvgCount

if __name__ == "__main__":

sc = SparkContext("local", "avgHousePrice")
sc.setLogLevel("ERROR")
conf = SparkConf().setAppName("avgHousePrice").setMaster("local[3]")
sc = SparkContext(conf = conf)

lines = sc.textFile("in/RealEstate.csv")
cleanedLines = lines.filter(lambda line: "Bedrooms" not in line)

housePricePairRdd = cleanedLines.map(lambda line: \
(line.split(",")[3], (1, float(line.split(",")[2]))))
(line.split(",")[3],AvgCount(1, float(line.split(",")[2]))))

housePriceTotal = housePricePairRdd \
.reduceByKey(lambda x, y:(x[0] + y[0], x[1] + y[1]))
.reduceByKey(lambda x, y:AvgCount(x.count + y.count, x.total + y.total))

print("housePriceTotal: ")
for bedroom,total in housePriceTotal.collect():
print("{} :{}".format(bedroom, total))
for bedroom,avgCount in housePriceTotal.collect():
print("{} :({}, {})".format(bedroom,avgCount.count, avgCount.total))

housePriceAvg = housePriceTotal.mapValues(lambda avgCount: avgCount[1] / avgCount[0])
housePriceAvg = housePriceTotal.mapValues(lambda avgCount: avgCount.total / avgCount.count)
print("\nhousePriceAvg: ")
for bedroom, avg in housePriceAvg.collect():
print("{} : {}".format(bedroom, avg))
8 changes: 5 additions & 3 deletionspairRdd/filter/AirportsNotInUsaSolution.py
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@@ -1,10 +1,12 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

if __name__ == "__main__":

sc =SparkContext("local", "airports")
sc.setLogLevel("ERROR")
conf =SparkConf().setAppName("airports").setMaster("local[*]")
sc = SparkContext(conf = conf)

airportsRDD = sc.textFile("in/airports.text")

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10 changes: 6 additions & 4 deletionspairRdd/groupbykey/AirportsByCountrySolution.py
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@@ -1,10 +1,12 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

if __name__ == "__main__":

sc =SparkContext("local", "airports")
sc.setLogLevel("ERROR")
conf =SparkConf().setAppName("airports").setMaster("local[*]")
sc = SparkContext(conf = conf)

lines = sc.textFile("in/airports.text")

Expand All@@ -15,4 +17,4 @@
airportsByCountry = countryAndAirportNameAndPair.groupByKey()

for country, airportName in airportsByCountry.collectAsMap().items():
print("{}: {}".format(country,list(airportName)))
print("{}: {}".format(country,list(airportName)))
9 changes: 5 additions & 4 deletionspairRdd/mapValues/AirportsUppercaseSolution.py
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@@ -1,10 +1,11 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

if __name__ == "__main__":

sc = SparkContext("local", "airports")
sc.setLogLevel("ERROR")
conf = SparkConf().setAppName("airports").setMaster("local[*]")
sc = SparkContext(conf = conf)

airportsRDD = sc.textFile("in/airports.text")

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10 changes: 5 additions & 5 deletionspairRdd/sort/AverageHousePriceSolution.py
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@@ -1,11 +1,11 @@
import sys
sys.path.insert(0, '.')
from pairRdd.aggregation.reducebykey.housePrice.AvgCount import AvgCount
from pyspark import SparkContext

from pyspark import SparkContext, SparkConf

if __name__ == "__main__":

sc = SparkContext("local", "averageHousePriceSolution")
sc.setLogLevel("ERROR")
conf = SparkConf().setAppName("averageHousePriceSolution").setMaster("local[*]")
sc = SparkContext(conf = conf)

lines = sc.textFile("in/RealEstate.csv")
cleanedLines = lines.filter(lambda line: "Bedrooms" not in line)
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7 changes: 5 additions & 2 deletionsrdd/airports/AirportsByLatitudeSolution.py
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@@ -1,12 +1,15 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

def splitComma(line: str):
splits = Utils.COMMA_DELIMITER.split(line)
return "{}, {}".format(splits[1], splits[6])

if __name__ == "__main__":
sc = SparkContext("local", "airports")
conf = SparkConf().setAppName("airports").setMaster("local[*]")
sc = SparkContext(conf = conf)

airports = sc.textFile("in/airports.text")

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7 changes: 5 additions & 2 deletionsrdd/airports/AirportsInUsaSolution.py
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@@ -1,12 +1,15 @@
from pyspark import SparkContext
import sys
sys.path.insert(0, '.')
from pyspark import SparkContext, SparkConf
from commons.Utils import Utils

def splitComma(line: str):
splits = Utils.COMMA_DELIMITER.split(line)
return "{}, {}".format(splits[1], splits[2])

if __name__ == "__main__":
sc = SparkContext("local", "airports")
conf = SparkConf().setAppName("airports").setMaster("local[*]")
sc = SparkContext(conf = conf)

airports = sc.textFile("in/airports.text")
airportsInUSA = airports.filter(lambda line : Utils.COMMA_DELIMITER.split(line)[3] == "\"United States\"")
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3 changes: 3 additions & 0 deletionsrdd/count/CountExample.py
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Expand Up@@ -3,9 +3,12 @@
if __name__ == "__main__":
conf = SparkConf().setAppName("count").setMaster("local[*]")
sc = SparkContext(conf = conf)

inputWords = ["spark", "hadoop", "spark", "hive", "pig", "cassandra", "hadoop"]

wordRdd = sc.parallelize(inputWords)
print("Count: {}".format(wordRdd.count()))

worldCountByValue = wordRdd.countByValue()
print("CountByValue: ")
for word, count in worldCountByValue.items():
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13 changes: 7 additions & 6 deletionssparkSql/HousePriceProblem.py
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Expand Up@@ -4,20 +4,21 @@
Create a Spark program to read the house data from in/RealEstate.csv,
group by location, aggregate the average price per SQ Ft and sort by average price per SQ Ft.

The houses dataset contains a collection of recent real estate listings in San Luis Obispo county and
around it. 
The houses dataset contains a collection of recent real estate listings in 
San Luis Obispo county andaround it. 

The dataset contains the following fields:
1. MLS: Multiple listing service number for the house (unique ID).
2. Location: city/town where the house is located. Most locations are in San Luis Obispo county and
northern Santa Barbara county (Santa Maria­Orcutt, Lompoc, Guadelupe, Los Alamos), but there
some out of area locations as well.
2. Location: city/town where the house is located. Most locations are in 
San Luis Obispo county andnorthern Santa Barbara county (Santa Maria­Orcutt, Lompoc, 
Guadelupe, Los Alamos), but theresome out of area locations as well.
3. Price: the most recent listing price of the house (in dollars).
4. Bedrooms: number of bedrooms.
5. Bathrooms: number of bathrooms.
6. Size: size of the house in square feet.
7. Price/SQ.ft: price of the house per square foot.
8. Status: type of sale. Thee types are represented in the dataset: Short Sale, Foreclosure and Regular.
8. Status: type of sale. Thee types are represented in the dataset: Short Sale, 
Foreclosure and Regular.

Each field is comma separated.

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4 changes: 2 additions & 2 deletionssparkSql/HousePriceSolution.py
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Expand Up@@ -4,8 +4,8 @@

if __name__ == "__main__":

session = SparkSession.builder.appName("HousePriceSolution").master("local").getOrCreate()
session.sparkContext.setLogLevel("ERROR")
session = SparkSession.builder.appName("HousePriceSolution").master("local[*]").getOrCreate()

realEstate = session.read \
.option("header","true") \
.option("inferSchema", value=True) \
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