利用python将两张表链接



from pyspark.sql import SparkSession
from pyspark.sql.types import *
import os


def getUser(spark,path):
struct1 = StructType([
StructField("user", StringType(), True),
StructField("vedios", StringType(), True),
StructField("id", IntegerType(), True)
])
df = spark.read.csv(path, schema=struct1, sep="\t", header=True)
df.createOrReplaceTempView("users1")
df = spark.sql("select * from users1")
return df


def getMovies(spark,path):
df = spark.read.csv(path, header=True)
df.createOrReplaceTempView("movies")
df = spark.sql("select * from movies ")
return df


if __name__ == '__main__':
os.environ['JAVA_HOME'] = 'C:\Program Files\Java\jdk1.8.0_211'
print(os.path)
spark = SparkSession \
.builder \
.appName("Python Spark SQL basic example") \
.config("spark.some.config.option", "some-value") \
.getOrCreate()
path_user = "C:/Users/Administrator/Desktop/guiliVideo/user/2008/0903/user.txt"
path_movies="C:/Users/Administrator/Desktop/vedios.txt"
df1=getUser(spark,path_user)
df2=getMovies(spark,path_movies)
df3=df1.join(df2,df1.user==df2.uploader,how='inner')
df3.createOrReplaceTempView('table1')
df4=spark.sql('select * from table1 limit 10')
df4.show(http://www.amjmh.com)
 
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posted on 2019-08-15 13:36  激流勇进1  阅读(1097)  评论(0编辑  收藏  举报