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Spark SQL and DataFrames Flashcards

6 cards from real Apache Spark practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 6 Spark SQL and DataFrames flashcards as text

  1. What is the entry point for Spark SQL functionality in Spark 2.x and later?

    Answer: SparkSession

    SparkSession is the unified entry point for Spark SQL, DataFrame, and Dataset APIs introduced in Spark 2.0.

  2. Which method is used to run a SQL query on a registered temporary view in Spark SQL?

    Answer: spark.sql()

    spark.sql() executes a SQL query and returns the results as a DataFrame.

  3. What is a DataFrame in Apache Spark?

    Answer: An RDD of Row objects with a named column schema

    A DataFrame is a distributed collection of data organized into named columns, conceptually equivalent to a database table.

  4. How do you register a DataFrame as a temporary SQL view in Spark?

    Answer: df.createOrReplaceTempView("name")

    createOrReplaceTempView() registers a DataFrame as a temporary view scoped to the current SparkSession.

  5. Which DataFrame function is used to select specific columns?

    Answer: select()

    select() returns a new DataFrame with only the specified columns.

  6. What does the printSchema() method do in Spark DataFrames?

    Answer: Prints the schema of the DataFrame in a tree format

    printSchema() prints the schema of the DataFrame as a tree showing column names, types, and nullability.