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

The video tutorial explains how to perform data aggregations in big data analytics using Spark. It covers the importance of aggregation functions like sum and max, and demonstrates their application through examples involving car price data. The tutorial concludes with a brief overview of the concepts and encourages viewers to apply these techniques using Spark.

What is the purpose of aggregation in big data analytics?

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Explain the significance of grouping data in the context of aggregation.

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What aggregation functions does Spark provide for summarizing data?

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Describe the steps involved in calculating the sum of car prices by year.

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How can the maximum price recorded in a specific year be determined using Spark?

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