from pyspark.sql import SparkSession from pyspark.sql.functions import col, when # 创建 SparkSession spark = SparkSession.builder.appName("example").getOrCreate() # 示例 DataFrame data = [("Alice", 34), ("Bob", 28), ("Catherine", 31)] columns = ["name", "age"] df = spark.creat...
在PySpark中,为DataFrame新增一列是一个常见的操作。以下是完成此任务的详细步骤,包括代码示例: 导入PySpark库并初始化SparkSession: 首先,需要导入PySpark库并创建一个SparkSession对象。SparkSession是PySpark的入口点,用于与Spark进行交互。 python from pyspark.sql import SparkSession # 初始化SparkSession spark = Sp...
df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], schema=["age", "name"])df.withColumnRenamed('age', 'age2').show()+---+---+|age2| name|+---+---+| 2|Alice|| 5| Bob|+---+---+ withColumnsRenamed 多列重命名 字典,列名的映射 df.withColumnsRenamed({'age'...
25),("Bob",30),("Cathy",29)]columns=["Name","Age"]df=spark.createDataFrame(data,columns)# 使用 withColumn 添加新列df_with_new_column=df.withColumn("Age after 5 years",col("
6.1 distinct:返回一个不包含重复记录的DataFrame 6.2 dropDuplicates:根据指定字段去重 --- 7、 格式转换 --- pandas-spark.dataframe互转 转化为RDD --- 8、SQL操作 --- --- 9、读写csv --- 延伸一:去除两个表重复的内容 参考文献 1、--
我有一个 Spark DataFrame(使用 PySpark 1.5.1)并且想添加一个新列。 我尝试了以下方法但没有成功: type(randomed_hours) # => list # Create in Python and transform to RDD new_col = pd.DataFrame(randomed_hours, columns=['new_col'])
\.getOrCreate()# 创建 DataFramedata=[("1",10),("2",20),("3",None)]columns=["id","value"]df=spark.createDataFrame(data,schema=columns)# 显示原始 DataFramedf.show()# 添加新列并提供默认值df_with_default=df.withColumn("default_col",lit(100))# 显示添加新列后的 DataFramedf_with_...
Pyspark dataframe列值取决于另一行的值 我有这样一个数据帧: columns = ['manufacturer', 'product_id'] data = [("Factory", "AE222"), ("Sub-Factory-1", "0"), ("Sub-Factory-2", "0"),("Factory", "AE333"), ("Sub-Factory-1", "0"), ("Sub-Factory-2", "0")]...
import pandas as pd from pyspark.sql import SparkSession colors = ['white','green','yellow','red','brown','pink'] color_df=pd.DataFrame(colors,columns=['color']) color_df['length']=color_df['color'].apply(len) color_df=spark.createDataFrame(color_df) color_df.show() 7.RDD与Data...
withExtensions(scala.Function1<SparkSessionExtensions,scala.runtime.BoxedUnit> f) 这允许用户添加Analyzer rules, Optimizer rules, Planning Strategies 或者customized parser.这一函数我们是不常见的。 DF创建 (1)直接创建 # 直接创建Dataframedf = spark.createDataFrame([ ...