pyspark.sql.DataFrame.createTempView#
- DataFrame.createTempView(name)[source]#
- Creates a local temporary view with this - DataFrame.- The lifetime of this temporary table is tied to the - SparkSessionthat was used to create this- DataFrame. throws- TempTableAlreadyExistsException, if the view name already exists in the catalog.- New in version 2.0.0. - Changed in version 3.4.0: Supports Spark Connect. - Parameters
- namestr
- Name of the view. 
 
 - Examples - Example 1: Creating and querying a local temporary view - >>> df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], schema=["age", "name"]) >>> df.createTempView("people") >>> spark.sql("SELECT * FROM people").show() +---+-----+ |age| name| +---+-----+ | 2|Alice| | 5| Bob| +---+-----+ - Example 2: Attempting to create a temporary view with an existing name - >>> df.createTempView("people") Traceback (most recent call last): ... AnalysisException: "Temporary table 'people' already exists;" - Example 3: Creating and dropping a local temporary view - >>> spark.catalog.dropTempView("people") True >>> df.createTempView("people") - Example 4: Creating temporary views with multiple DataFrames with - SparkSession.table()- >>> df1 = spark.createDataFrame([(1, "John"), (2, "Jane")], schema=["id", "name"]) >>> df2 = spark.createDataFrame([(3, "Jake"), (4, "Jill")], schema=["id", "name"]) >>> df1.createTempView("table1") >>> df2.createTempView("table2") >>> result_df = spark.table("table1").union(spark.table("table2")) >>> result_df.show() +---+----+ | id|name| +---+----+ | 1|John| | 2|Jane| | 3|Jake| | 4|Jill| +---+----+