DataFrame.createGlobalTempView 是 PySpark 中 DataFrame 对象的方法之一。它用于创建一个全局临时视图。具体来说,createGlobalTempView 方法将当前 DataFrame 对象注册为一个全局临时视图。全局临时视图是一个在整个 Spark 应用程序中可见的、命名的逻辑表,可以基于该视图执行 SQL 查询。这个方法的作用是将 DataFrame 转换...
spark.sql('''SELECT m1.a, m2.bFROM {table1} m1 INNER JOIN {table2} m2ON m1.key = m2.keyORDER BY m1.a, m2.b''',table1=spark.createDataFrame([(1, "a"), (2, "b")], ["a", "key"]),table2=spark.createDataFrame([(3, "a"), (4, "b"), (5, "b")], ["b", ...
1.3 从Hive表创建DataFrame PySpark还支持从Hive表创建DataFrame。以下是一个示例: frompyspark.sqlimportSparkSession# 创建SparkSessionspark=SparkSession.builder.appName("Hive table to DataFrame").enableHiveSupport().getOrCreate()# 从Hive表创建DataFramedf=spark.sql("SELECT * FROM my_table") 1. 2. 3....
from pyspark.sql import SparkSession from pyspark.sql.functions import udf from pyspark.sql.types import StringType # 创建SparkSession spark = SparkSession.builder.appName("DataFrameReorganization").getOrCreate() # 创建示例DataFrame data = [("Alice", 25), ("Bob", 30), ("Charlie", 35...
itertuples(): 按行遍历，将DataFrame的每一行迭代为元祖，可以通过row[name]对元素进行访问，比iterrows...
PySpark Dataframe 添加新列 为spark dataframe 添加新的列的几种实现 frompyspark.sqlimportSparkSessionfrompyspark.sqlimportRow spark= SparkSession.builder.getOrCreate() 测试数据准备 test_data =[ Row(name='China', Population=1439323776, area=960.1),...
spark.sql("insert overwrite table dev.dev_result_temp select user_log_acct,probability from tmp") spark.stop() 创建和保存spark dataframe: spark.createDataFrame(data, schema=None, samplingRatio=None),直接创建 其中data是行或元组或列表或字典的RDD、list、pandas.DataFrame。
创建不输入schema格式的DataFramefrom 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,...
from pyspark.sql import SparkSession spark=SparkSession \ .builder \ .appName('my_first_app_name') \ .getOrCreate() 2. 创建dataframe 2.1. 从变量创建 # 生成以逗号分隔的数据 stringCSVRDD = spark.sparkContext.parallelize([ (123, "Katie", 19, "brown"), (234, "Michael", 22, "green"...
spark.sql("insert overwrite table dev.dev_result_temp select user_log_acct,probability from tmp") spark.stop() 创建和保存spark dataframe: spark.createDataFrame(data, schema=None, samplingRatio=None),直接创建 其中data是行或元组或列表或字典的RDD、list、pandas.DataFrame。