基于pandas DataFrame创建pyspark DataFrame df.toPandas()可以把pyspark DataFrame转换为pandas DataFrame。 df= spark.createDataFrame(rdd, ['name','age'])print(df)# DataFrame[name: string, age: bigint]print(type(df.toPandas()))# <class 'pandas.core.frame.DataFrame'># 传入pandas DataFrameoutput =...
data = [("Alice", 25, "New York"), ("Bob", 30, "San Francisco")] df = spark.createDataFrame(data, ["name", "age", "city"]) 使用struct函数创建嵌套列: 代码语言:txt 复制 df_with_nested_column = df.withColumn("address", struct(df["city"])) ...
在PySpark中,可以通过以下步骤从文本文件创建DataFrame: 导入必要的模块和函数: 代码语言:txt 复制 from pyspark.sql import SparkSession from pyspark.sql.types import StructType, StructField, StringType 创建SparkSession对象: 代码语言:txt 复制 spark = SparkSession.builder.appName("Create DataFrame from Text...
schema = StructType([ StructField("id", LongType(), True), StructField("name", StringType(), True), StructField("age", LongType(), True), StructField("eyeColor", StringType(), True) ]) df = spark.createDataFrame(csvRDD, schema) 5.读文件创建DataFrame testDF = spark.read.csv(File...
from pyspark.sql.types import StructField, StringTypedf = spark.createDataFrame([("a", 1)], ["i", "j"])df.show()+---+---+| i| j|+---+---+| a| 1|+---+---+df.schemaStructType([StructField('i', StringType(), True), StructField('j', LongType(), True)])# 设置新...
df = spark.createDataFrame([{'name':'Alice','age':1}, {'name':'Polo','age':1}]) (3)指定schema创建 schema = StructType([ StructField("id", LongType(),True), StructField("name", StringType(),True), StructField("age", LongType(),True), ...
from pyspark.sql.types import StructType, StructField, LongType, StringType data_schema = StructType([ StructField('id', LongType()), StructField('type', StringType()), ]) df = spark.createDataFrame(spark.sparkContext.emptyRDD(), schema=data_schema) df.show() ...
StructField("gender",StringType(),True),\ StructField("salary",IntegerType(),True)\])df=spark.createDataFrame(data=data,schema=schema)df.printSchema()df.show(truncate=False) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. ...
PySpark - DataFrame的基本操作 连接spark 1、添加数据 1.1、createDataFrame(): 创建空dataframe 1.2、createDataFrame() : 创建一个spark数据框 1.3、toDF() : 创建一个spark数据框 1.4、withColumn(): 新增数据列 2、修改数据 2.1、withColumn(): 修改原有数据框中某一列的值(统一修改) ...
File "/software/spark-3.1.2-bin-hadoop2.7/python/pyspark/sql/session.py", line 517, in _createFromLocal struct.fields[i].name = nameIndexError: list index out of range>>> deptColumns2 = ["dept_name","dept_id", "new_field"]>>> write_df2 = spark.createDataFrame(data=dept2, schema...