Apache Spark 3 for Data Engineering and Analytics with Python - Aggregations - Count and Count Distinct

The video tutorial introduces aggregation functions, focusing on count and count distinct functions. It explains how to import these functions using PySpark and demonstrates their application on dataframes, highlighting how count excludes null values. The tutorial also covers using count distinct to identify unique values in datasets. The session concludes with a preview of upcoming lessons on other aggregation functions like min, max, sum, and average.

Describe the process of importing aggregation functions in Pyspark as mentioned in the text.

Evaluate responses using AI:

OFF

What conclusion can be drawn from the counts of records in the dataframe?

Evaluate responses using AI:

OFF

What is the significance of using count distinct for analyzing airport data?

Evaluate responses using AI:

OFF