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- Spark SQL Join Types- Syntax examples, Comparision
- Date and Time Functions- Pyspark Dataframes & Pyspark Sql Queries
- Apache Spark RDDs: Comprehensive Tutorial
- Complete crisp PySpark Interview Q&A Cheat Sheet
- Python Lists- how it is created, stored in memory, and how inbuilt methods work — including internal implementation details
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Category: Tutorials
RDD (Resilient Distributed Dataset) is the fundamental data structure in Apache Spark. It is an immutable, distributed collection of objects that can be processed in parallel across a cluster of machines. Purpose of RDD How RDD is Beneficial RDDs are the backbone of Apache Spark’s distributed computing capabilities. They enable scalable, fault-tolerant, and efficient processing…
Big Data Lake: Data Storage HDFS is a scalable storage solution designed to handle massive datasets across clusters of machines. Hive tables provide a structured approach for querying and analyzing data stored in HDFS. Understanding how these components work together is essential for effectively managing data in your BDL ecosystem. HDFS – Hadoop Distributed File…
Big data and big data lakes are complementary concepts. Big data refers to the characteristics of the data itself, while a big data lake provides a storage solution for that data. Organizations often leverage big data lakes to store and manage their big data, enabling further analysis and exploration. Here’s an analogy: Think of big…