PySpark and AWS: Master Big Data with PySpark and AWS - Spark DF Filter Rows

The video tutorial covers various techniques for filtering data in Spark DataFrames. It begins with basic filtering methods, progresses to using multiple conditions, and introduces the 'isin' function for filtering based on multiple values. The tutorial also explores string functions like 'startsWith', 'endsWith', 'contains', and 'like' for more advanced filtering. These techniques help in efficiently manipulating and querying data within DataFrames.

What is the primary focus of the video tutorial?

• Creating new DataFrames

• Filtering rows and columns in DataFrames

• Visualizing data with charts

• Performing data aggregation

Which method is used to filter rows based on a single condition?

• DF.select

• DF.groupBy

• DF.aggregate

• DF.filter

What logical operator is used to combine multiple conditions in a DataFrame filter?

• AND

• XOR

• NOT

• OR

How can you filter DataFrame rows that match any value from a list?

• Using 'contains' function

• Using 'is in' function

• Using 'starts with' function

• Using 'ends with' function

What is the benefit of using 'is in' over multiple OR conditions?

• It is more readable

• It allows for more conditions

• It is more secure

• It is faster

Which function is used to filter rows where a column value starts with a specific string?

• isIn

• endsWith

• contains

• startsWith

What is the alternative to 'contains' for checking if a column value includes a specific string?

• startsWith

• like

• isIn

• endsWith

Which function would you use to filter rows where a column value ends with a specific string?

• endsWith

• startsWith

• contains

• isIn

Which notation is similar to SQL's 'LIKE' for pattern matching in DataFrames?

• like

• startsWith

• isIn

• contains

What should you ensure when using 'starts with' in Databricks?

• Use numbers

• Use small letters

• Use capital letters

• Use special characters