【机器学习之二】python开发spark案例

环境
　　spark-1.6
　　python3.5

一、wordcount

# -*- coding:utf-8 -*-
'''
Created on 2019年5月13日

@author: Administrator
'''

#从pyspark中导入相应的包
from pyspark import SparkConf
from pyspark import SparkContext

def show(x):
    print(x)

if __name__ == '__main__':
    #创建SparkConf
    conf = SparkConf().setAppName("wordcount").setMaster("local")
    #创建SparkContext  注意参数要传递conf=conf
    sc = SparkContext(conf=conf)
    #设置日志级别
    sc.setLogLevel("WARN")
    #使用2个分区读取数据 一行行的数据
    lines = sc.textFile("../../data/words", 2)
    print("lines rdd partition length = %d"%(lines.getNumPartitions()))
    #每一行数据按照空格拆分  得到一个个单词
    words = lines.flatMap(lambda line:line.split(" "), True)
    #将每个单词 组装成一个tuple 计数1
    pairWords = words.map(lambda word : (word,1),True)
    #使用3个分区 reduceByKey进行汇总
    result = pairWords.reduceByKey(lambda v1,v2:v1+v2, 3)
    print("result rdd partition length = %d"%(result.getNumPartitions()))
    #打印结果
    result.foreach(lambda t :show(t))
    #将结果保存到文件
    result.saveAsTextFile("../../data/wc-result")
    #关闭
    sc.stop()

二、PVUV

# -*- coding:utf-8 -*-
'''
Created on 2019年5月16日

@author: Administrator
'''
# import sys
from pyspark.conf import SparkConf
from pyspark.context import SparkContext
from builtins import sorted

# print(sys.getdefaultencoding())
# reload(sys)
# sys.setdefaultencoding('utf-8')
# print(sys.getdefaultencoding())

#打印结果
def showresult(em):
    print(em)

#数据样例
#7.213.213.208    吉林    2018-03-29    1522294977303    1920936170939152672    www.dangdang.com    Login

#页面访问量
def pv(lines):
    sitepair = lines.map(lambda line:(line.split("\t")[5],1))
    result1 = sitepair.reduceByKey(lambda v1,v2:v1+v2)
    #排序 降序
    result2 = result1.sortBy(lambda one:one[1],ascending=False)
    result2.foreach(lambda em :showresult(em))
# ('www.baidu.com', 18791)
# ('www.dangdang.com', 18751)
# ('www.suning.com', 18699)
# ('www.mi.com', 18678)
# ('www.taobao.com', 18613)
# ('www.jd.com', 18519)
# ('www.gome.com.cn', 18493)

#用户访问量
def uv(lines):
    #同一个IP访问某个网站量要排重
    sitepair = lines.map(lambda line:line.split("\t")[0]+"_"+line.split("\t")[5]).distinct()
    result = sitepair.map(lambda one:(one.split("_")[1],1)).reduceByKey(lambda v1,v2:v1+v2).sortBy(lambda one:one[1],ascending=False)
    result.foreach(lambda one:showresult(one))
# ('www.baidu.com', 15830)
# ('www.suning.com', 15764)
# ('www.mi.com', 15740)
# ('www.jd.com', 15682)
# ('www.dangdang.com', 15641)
# ('www.taobao.com', 15593)
# ('www.gome.com.cn', 15590)

def uvExceptBJ(lines):
    usiteviews = lines.filter(lambda line:line.split("\t")[1] != "北京").map(lambda line:line.split("\t")[0]+"_"+line.split("\t")[5]).distinct()
    result1 = usiteviews.map(lambda one:(one.split("_")[1],1)).reduceByKey(lambda v1,v2:v1+v2)
    result2 = result1.sortBy(lambda one:one[1],ascending=False)
    result2.foreach(lambda em : showresult(em))
# ('www.baidu.com', 15399)
# ('www.mi.com', 15341)
# ('www.suning.com', 15294)
# ('www.jd.com', 15255)
# ('www.dangdang.com', 15181)
# ('www.gome.com.cn', 15154)
# ('www.taobao.com', 15131)   

def getTop2Location(lines):
    #按照网站分组
    site_locations = lines.map(lambda line:(line.split("\t")[5],line.split("\t")[1])).groupByKey()
    result = site_locations.map(lambda one:getCurrSiteTop2Location(one)).collect()
    for em in result:
        print(em)
# ('www.suning.com', [('山西', 1102), ('广西', 606)])
# ('www.jd.com', [('山西', 1069), ('湖北', 614)])
# ('www.taobao.com', [('山西', 1065), ('安徽', 601)])
# ('www.gome.com.cn', [('山西', 1029), ('内蒙', 590)])
# ('www.dangdang.com', [('山西', 1083), ('香港', 591)])
# ('www.mi.com', [('山西', 1085), ('广东', 617)])
# ('www.baidu.com', [('山西', 1028), ('台湾', 641)])

def getCurrSiteTop2Location(one):
    site = one[0]
    locations = one[1]

    locationdict = {}
    #汇总每个网站中location的数量
    for location in locations:
        if location in locationdict:
            locationdict[location] += 1
        else:
            locationdict[location] = 1
    resultlist = []
    #使用内置函数排序
    sortedList = sorted(locationdict.items(),key = lambda kv:kv[1],reverse = True)
    #取前两个地区
    if len(sortedList) < 2:
       resultlist = sortedList
    else:
        for i in range(2):
            resultlist.append(sortedList[i])
    return site,resultlist

def getTopOperation(lines):
    site_operations = lines.map(lambda line:(line.split("\t")[5],line.split("\t")[6])).groupByKey()
    result = site_operations.map(lambda one:getCurrSiteTopOperation(one)).collect()
    for em in result:
        print(em)
# ('www.suning.com', [('View', 3168)])
# ('www.jd.com', [('Login', 3132)])
# ('www.taobao.com', [('Regist', 3196)])
# ('www.gome.com.cn', [('Click', 3170)])
# ('www.dangdang.com', [('Buy', 3179)])
# ('www.mi.com', [('Buy', 3231)])
# ('www.baidu.com', [('Comment', 3207)])

def getCurrSiteTopOperation(one):
    site = one[0]
    operations = one[1]
    operationDict = {}
    for operation in operations:
        if operation in operationDict:
            operationDict[operation] += 1
        else:
            operationDict[operation] = 1

    resultList=[]
    sortedList = sorted(operationDict.items(), key=lambda kv:kv[1], reverse=True)
    if len(sortedList) < 1:
       resultList=[]
    else:
        resultList.append(sortedList[0])
    return site,resultList

def getTop3User(lines):
    #另外一种思路 按照用户分组 统计每个用户访问不同网站数量
    site_uid_count = lines.map(lambda line:(line.split("\t")[3],line.split("\t")[5])).groupByKey().flatMap(lambda one:getSiteInfo(one))
    #按照网站分组之后再取前三
    result = site_uid_count.groupByKey().map(lambda one:getCurSiteTop3User(one)).collect()
    for em in result:
        print(em)
# ('www.suning.com', [('1522294989941', 5), ('1522294980028', 5), ('1522294986337', 5)])
# ('www.jd.com', [('1522295002636', 5), ('1522294988631', 5), ('1522294990824', 4)])
# ('www.taobao.com', [('1522294992394', 5), ('1522294982477', 5), ('1522294999369', 5)])
# ('www.gome.com.cn', [('1522294994219', 5), ('1522294988497', 5), ('1522294991142', 5)])
# ('www.dangdang.com', [('1522294994360', 5), ('1522294988712', 5), ('1522294992239', 4)])
# ('www.mi.com', [('1522294987189', 5), ('1522294989540', 5), ('1522294980962', 5)])
# ('www.baidu.com', [('1522294991559', 6), ('1522294989188', 5), ('1522294996021', 5)])

#统计每个用户访问网站数量 然后返回每个网站对应用户访问量
def getSiteInfo(one):
    uid = one[0]
    sites = one[1]
    siteDict = {}
    for site in sites:
        if site in siteDict:
            siteDict[site] += 1
        else:
            siteDict[site] = 1
    resultList=[]
    for site,count in siteDict.items():
        resultList.append((site,(uid,count)))
    return resultList

def getCurSiteTop3User(one):
    site = one[0]
    uid_counts = one[1]
    top3List = ["","",""]
    for uid_count in uid_counts:
        for i in range(0,len(top3List)):
            if top3List[i] == "":
                top3List[i] = uid_count
                break
            else:
                if uid_count[1] > top3List[i][1]:
                    for j in range(2,i,-1):
                        top3List[j] = top3List[j-1]
                    top3List[i] = uid_count
                    break
    return site,top3List           

if __name__ == '__main__':
    conf = SparkConf().setMaster("local").setAppName("pvuv")
    sc = SparkContext(conf=conf)
    sc.setLogLevel("WARN")
    lines = sc.textFile('../../data/pvuvdata')
    # 1).统计PV,UV
    pv(lines)
    uv(lines)
    # 2).统计除了北京地区外的UV
    uvExceptBJ(lines)
    # 3).统计每个网站最活跃的top2地区
    getTop2Location(lines)
    # 4).统计每个网站最热门的操作
    getTopOperation(lines)
    # 5).统计每个网站下最活跃的top3用户
    getTop3User(lines)
    #停止
    sc.stop()