Apache Spark 3 for Data Engineering and Analytics with Python - Get the Most Products Sold Together

The video tutorial guides viewers through the process of identifying products frequently sold together in New York using SQL. It covers data preparation, grouping order IDs, combining products into lists, and creating temporary tables. The tutorial concludes with analyzing product combinations and visualizing the results using a pie chart.

What is the first step in determining if an order ID can have multiple products?

• Check the sales table for duplicate entries

• Count the number of products per order ID

• Filter the data by product name

• Sort the data by order ID

What is the purpose of the 'having' clause in SQL?

• To filter data based on aggregation results

• To sort data in ascending order

• To join multiple tables

• To update existing records

Which SQL function is used to create a list of products for each order ID?

• GROUP_CONCAT

• COLLECT_LIST

• ARRAY_AGG

• LISTAGG

Why is it important to sort the product list by product name?

• To ensure the list is in alphabetical order

• To make it easier to group products consistently

• To improve database performance

• To reduce the size of the data

What is the purpose of creating a temporary table in this context?

• To permanently store the sorted product list

• To store intermediate results for further processing

• To delete unnecessary data

• To backup the original sales data

How is the most common combination of products identified?

• By sorting the product list in descending order

• By counting the frequency of each product combination

• By filtering the product list by state

• By using a pie chart to visualize the data

What type of chart is used to visualize the top product combinations?

• Pie chart

• Line chart

• Bar chart

• Scatter plot