Save DataFrame as a Temporary View

Correct Answer: B

Before issuing SQL queries, DataFrame needs to be saved as a table or temporary view.

createOrReplaceTempView function is used to create the temporary view.

Option A is incorrect.

There is no DataFrame method like createTempView.

Option B is correct.

createOrReplaceTempView function is used to create the temporary view.

Option C is incorrect.

There is no such method as ReplaceTempView.

Option D is incorrect.

There is no such method as createTempViewForDataFrame.

Option E is incorrect.

There is no DataFrame method like CreateorReplaceDFTempView.

To know more about DataFrames, please visit the below-given link:

The correct method to create a temporary view from a DataFrame in Apache Spark is B. createOrReplaceTempView.

Explanation:

In Spark, a DataFrame is an immutable distributed collection of data organized into named columns. A temporary view is a virtual table that exists only in the memory of Spark cluster and allows users to run SQL-like queries on DataFrames.

To create a temporary view from a DataFrame, you can use the createOrReplaceTempView method. This method registers the DataFrame as a temporary table or view in Spark's catalog, which can be used in subsequent Spark SQL statements. The createOrReplaceTempView method also overwrites any existing temporary view or table with the same name, or creates a new temporary view if the specified name does not exist.

For example, suppose you have a DataFrame named myDataFrame. You can create a temporary view from this DataFrame using the following code:

pythonCopy code
myDataFrame.createOrReplaceTempView("myTempView") 

This will create a temporary view named myTempView that you can use in Spark SQL queries. For example, you can run the following SQL query to retrieve all rows from the temporary view:

pythonCopy code
spark.sql("SELECT * FROM myTempView") 

Note that temporary views are only accessible within the Spark session that created them and are not persisted across sessions. If you need to reuse a temporary view across multiple Spark sessions, you can save it as a global temporary view using the createOrReplaceGlobalTempView method.