schema = StructType([ StructField("BookID", IntegerType(), False), StructField("Title", StringType(), True), StructField("Type", StringType(), True), ]) df = spark.createDataFrame(data, schema) df = df.groupby('BookID').agg(collect_list(struct(col('Title'), col('Type'))).ali...
# 创建SparkSession spark = SparkSession.builder.getOrCreate() # 创建DataFrame data = [("Alice", 25), ("Bob", 30), ("Charlie", 35)] df = spark.createDataFrame(data, ["Name", "Age"]) # 使用array函数创建数组列 df_with_array = df.withColumn("ArrayColumn", array(df["Name"], df...
5. posexplode # Returns a new row for each element with position in the given array or map.frompyspark.sqlimportRowfrompyspark.sql.functionsimportposexplodeeDF=spark.createDataFrame([Row(a=1,intlist=[1,2,3],mapfield={"a":"b"})])eDF.show() +---+---+---+ | a| intlist|mapfield|...
下面是一个示例代码,演示如何向PySpark DataFrame添加一个数组列: frompyspark.sqlimportSparkSessionfrompyspark.sql.functionsimportcol,lit,array# 创建SparkSessionspark=SparkSession.builder.appName("Add Array Column").getOrCreate()# 创建示例DataFramedata=[("Alice",34),("Bob",45),("Cathy",28)]df=spa...
Create ArrayType column Create a DataFrame with an array column. df = spark.createDataFrame( [("abc", [1, 2]), ("cd", [3, 4])], ["id", "numbers"] ) df.show() +---+---+ | id|numbers| +---+---+ |abc| [1,
array_insert 插入数据 都是操作column arr 数组列 pos 插入索引位置 从1开始 value 插入的值 df = spark.createDataFrame( [(['a', 'b', 'c'], 2, 'd'), (['c', 'b', 'a'], -2, 'd')], ['data', 'pos', 'val'])df.show()+---+---+---+| data|pos|val|+---+---+-...
count=random.randint(1,len(labels)-1)returnlabels[:count]# ArrayType代表数组型df=df.withColumn('labels',udf(get_labels,types.ArrayType(types.StringType()))()) df.show()===>> +---+---+---+ |name|age| labels| +---+---+-...
[spark][pyspark]拆分DataFrame中某列Array getItem()语法#pyspark.sql.Column.getItem描述An expression that gets an item at position ordinal out of a list, or gets an item by key out of a dict.示例>>> df = spark.createDataFrame([([
spark = SparkSession.builder.getOrCreate() # 创建示例DataFrame data = spark.createDataFrame([(1, [1, 2, 3]), (2, [4, 5])], ['id', 'array_column']) # 展开阵列列 expanded_data = data.select('id', explode('array_column').alias('expanded_column')) ...
1.array(返回一个新的数组) #将name和age组成一个数组列df1=df.withColumn('arrayColumn',F.array(df.name,df.age))# 单出输出一个dataframedf2=df.select(F.array(df.name,df.age).alias('arrayColumn'))df1.show()df2.show() image.png