PySpark Column 类还提供了一些函数来处理 StructType 列。...在下面的示例中,列hobbies定义为 ArrayType(StringType) ,列properties定义为 MapType(StringType, StringType),表示键和值都为字符串。...,以及如何在运行时更改 Pyspark DataFrame 的结构,将案例类转换为
importrandomdefadd_salt(key):return(key,random.randint(1,10))df=df.withColumn("salted_key",F.udf(add_salt)("key_column"))df=df.groupBy("salted_key").agg(F.collect_list("value_column"))df=df.withColumn("key_column",F.col("salted_key").getItem(0)).drop("salted_key") 5.采样(Sa...
In PySpark, we can drop one or more columns from a DataFrame using the .drop("column_name") method for a single column or .drop(["column1", "column2", ...]) for multiple columns.
from pyspark.sql import Window from pyspark.sql.functions import row_number, monotonically_increasing_id window_spec = Window.orderBy(monotonically_increasing_id()) df = df.withColumn("index", row_number().over(window_spec) - 1) ''' +---+---+---+ | cfrnid| 0830|index| +---+---...
df4.drop("CopiedColumn") \ .show(truncate=False) 1. 2. 4、where() & filter() where和filter函数是相同的操作,对DataFrame的列元素进行筛选。 import pyspark from pyspark.sql import SparkSession from pyspark.sql.types import StructType,StructField, StringType, IntegerType, ArrayType from pyspark....
withColumn(colName:String,col:Column):添加列或者替换具有相同名字的列,返回新的DataFrame。 1.3 XGBoost4J-Spark 随着Spark在工业界的广泛应用,积累了大量的用户,越来越多的企业以Spark为核心构建自己的数据平台来支持挖掘分析类计算、交互式实时查询计算,于是XGBoost4J-Spark应运而生。本节将介绍如何通过Spark实现机器...
DataFrame可以对Column进行操作和更改。 #删除指定的column,通常join后删除on的column df.drop('age').show() df.drop(df.age).show() df.join(df2, df.name == df2.name, 'inner').drop('name').sort('age').show() #创建新的column或更新重名column,指定column不存在不操作 ...
mysql://192.168.174.101:3306/crime --username root --password 123456 --table log --columns "dates,category,descript,dayofweek,pddistrict,resolution,address,x,y,id" --column-family "info" --hbase-create-table --hbase-table "log" --hbase-row-key "id" --num-mappers 1 --split-by id...
1#除去一些不要的列,并展示前五行2drop_list = ['Dates','DayOfWeek','PdDistrict','Resolution','Address','X','Y']3data = data.select([columnforcolumnindata.columnsifcolumnnotindrop_list])4data.show(5) 1.2 显示数据结构 1#利用printSchema()方法显示数据的结构2data.printSchema() ...
The index column instant is also not useful as a predictor. You can also delete the column dteday, as this information is already included in the other date-related columns yr, mnth, and weekday. df = df.drop("instant").drop("dteday").drop("casual").drop("registered") display(df...