Spark Programming in Python for Beginners with Apache Spark 3 - Reading CSV, JSON and Parquet files

The video tutorial introduces the Reader API in Spark, demonstrating how to use the DataFrame reader to handle different data file formats: CSV, JSON, and Parquet. It explains the process of reading these files, the importance of schema inference, and the limitations of relying solely on inferred schemas. The tutorial emphasizes the advantages of using Parquet files, which include built-in schema information, making them the preferred format for data processing in Spark. The video concludes with recommendations to use Parquet files whenever possible for efficient data handling.

What are the three types of data files included in the Spark Schema Demo project?

• CSV, JSON, and XML

• CSV, XML, and Parquet

• CSV, JSON, and Parquet

• JSON, XML, and Parquet

Which option is necessary when reading a CSV file with a header using Dataframe reader?

• Set header to false

• Set header to true

• Set inferSchema to true

• Set delimiter to comma

What is a limitation of using the inferSchema option with CSV files?

• It requires a header row

• It cannot infer any data types

• It only infers string data types

• It may not correctly infer date fields

When reading JSON files, what is a notable behavior of the Dataframe reader?

• It requires a header row

• It requires explicit schema definition

• It automatically infers the schema

• It does not sort columns alphabetically

What is a common issue when inferring schemas for JSON files?

• No schema is inferred

• All fields are inferred as integers

• Integer fields are inferred as strings

• Date fields are inferred as strings

What is a key advantage of using Parquet files in Spark?

• They include schema information within the file

• They do not require a schema

• They are the only format supported by Spark

• They are text-based and easy to read

Why is the Parquet file format recommended for use in Spark?

• It is faster than all other formats

• It does not require any setup

• It is the only format that supports JSON

• It is the default file format for Apache Spark