8. SparkSQL综合作业
综合练习:学生课程分数
网盘下载sc.txt文件,创建RDD,并转换得到DataFrame。
>>> lines = spark.sparkContext.textFile('file:///home/hadoop/wc/sc.txt') >>> parts = lines.map(lambda x:x.split(',')) >>> people = parts.map(lambda p : Row(p[0],p[1],int(p[2].strip()) )) >>> from pyspark.sql.types import IntegerType,StringType >>> from pyspark.sql.types import StructField,StructType >>> from pyspark.sql import Row >>> fields = [StructField('name',StringType(),True),StructField('course',StringType(),True), StructField('age',IntegerType(),True)] >>> schema = StructType(fields) >>> lines = spark.sparkContext.textFile('file:///home/hadoop/wc/sc.txt') >>> parts = lines.map(lambda x:x.split(',')) >>> people = parts.map(lambda p : Row(p[0],p[1],int(p[2].strip()) )) >>> schemaPeople = spark.createDataFrame(people,schema) >>> schemaPeople.printSchema() >>> schemaPeople.show(10)
分别用DataFrame操作和spark.sql执行SQL语句实现以下数据分析:
1.总共有多少学生?
>>> schemaPeople.select(schemaPeople['name']).distinct().count()
2.开设了多少门课程?
>>> schemaPeople.select(schemaPeople['course']).distinct().count()
3.每个学生选修了多少门课?
>>> schemaPeople.groupBy('name').count().show()
4.每门课程有多少个学生选?
>>> schemaPeople.groupBy('course').count().show()
5.有多少个100分?
ilter(schemaPeople['age']==100).show()
6.Tom选修了几门课?每门课多少分?
>>> schemaPeople.filter(schemaPeople['name']=='Tom').show()
7.Tom的成绩按分数大小排序。
>>> schemaPeople.filter(schemaPeople['name']=='Tom').orderBy(schemaPeople.age).show()
8.Tom选修了哪几门课?
>>> schemaPeople.filter(schemaPeople['name']=='Tom').select(schemaPeople['name'],schemaPeople['course']).show()
9.Tom的平均分。
>>> schemaPeople.registerTempTable('people') >>> spark.sql('select avg(age) from people where name = "Tom" ').show()
10.'OperatingSystem'不及格人数
>>> spark.sql('select count(name) from people where course = "OperatingSystem" and age < 60').show()
11.'OperatingSystem'平均分
>>> spark.sql('select avg(age) from people where course = "OperatingSystem" ').show()
12.'OperatingSystem'90分以上人数
>>> spark.sql('select * from people where course = "OperatingSystem" and age > 90 ').show()
13.每个分数按比例+20平时分。
>>> schemaPeople.select(schemaPeople['name'],schemaPeople['course'],schemaPeople['age']+20).show(5)
14.求每门课的平均分
>>> spark.sql('select course, AVG(age) from people where GROUP BY course').show()
15.求每门课的最高分最低分
>>> spark.sql('select course, MAX(age) from people where GROUP BY course').show()