#convert to a UDF Function by passing in the function and return type of function udfsomefunc = F.udf(somefunc, StringType()) ratings_with_high_low = ratings.withColumn("high_low", udfsomefunc("rating")) ratings_with_high_low.show() 使用RDD 有时,Spark UDF和SQL函数对于特定用例而言都是...
#convert to a UDF Function by passing in the function and return type of function udfsomefunc = F.udf(somefunc, StringType()) ratings_with_high_low = ratings.withColumn("high_low", udfsomefunc("rating")) ratings_with_high_low.show() 4.使用SQL 对于喜欢SQL的人,甚至可以使用SQL创建列。
Columns in PySpark can be transformed using various functions such aswithColumn,when, andotherwise. These functions allow you to apply conditional logic and transformations to columns. Here is an example of how to add a new column “is_old” based on the age column: df.withColumn("is_old",w...
一、withColumnRenamed()方式修改列名:# 重新命名聚合后结果的列名(需要修改多个列名就跟多个:withColumnRenamed)# 聚合之后不修改列名则会显示:count(member_name)df_res.agg({'member_name':'count','income':'sum','num':'sum'}) .withColumnRenamed("count(member_name)","member_num").show() 二、利用...
def apply1(x): pass # print(x['image_id']) df.foreach(apply1) # 变换 print('===变换===') df = df.withColumn("age", df["age"].cast("Int")) # 修改列的类型 print(df.show(3)) new_df = df.withColumn('userid',df['age'].cast('int')%10) # 新增一列,cast 可用于列类...
# 基于dataframe生成相同行数的随机数frompyspark.sql.functionsimportrand,randn# 均匀分布和正太分布函数test.select(rand(seed=10).alias("uniform"),randn(seed=27).alias("normal"))\.show()# 或者随机生成指定行数的dataframedf=spark.range(0,10).withColumn('rand1',rand(seed=10))\.withColumn('rand...
sql.functions import udf CalculateAge = udf(CalculateAge, IntegerType()) # Apply UDF function Member_df = Member_df.withColumn("AGE", CalculateAge(Member_df['date of birthday'])) 4.1.2 日期 代码语言:javascript 代码运行次数:0 运行 AI代码解释 清洗日期格式字段 from dateutil import parser def...
from datetime import datetime, date import pandas as pd from pyspark.sql import Row df = spark.createDataFrame([ Row(a=1, b=2., c='string1', d=date(2000, 1, 1), e=datetime(2000, 1, 1, 12, 0)), Row(a=2, b=3., c='string2', d=date(2000, 2, 1), e=datetime(2000,...
from pyspark.sql.functions import col df_casted = df_customer.withColumn("c_custkey", col("c_custkey").cast(StringType())) print(type(df_casted)) Remove columnsTo remove columns, you can omit columns during a select or select(*) except or you can use the drop method:Python Копи...
在pyspark中,DataFrame是一种分布式数据集合,它以列的形式组织数据,并且每列都有特定的数据类型。如果我们想要获取DataFrame中每列的最大字符串长度,可以使用pyspark的内置函数length()和agg()来实现。 首先,我们需要导入pyspark的相关模块: 代码语言:txt 复制 from pyspark.sql import SparkSession from pyspark.sql.f...