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- Parallel processing in Python—especially in data engineering and PySpark pipelines
- All major PySpark data structures and types Discussed
- PySpark Control Statements Vs Python Control Statements- Conditional, Loop, Exception Handling, UDFs
- Pyspark Memory Management, Partition & Join Strategy – Scenario Based Questions
- Data Engineer Interview Questions Set5
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Category: Tutorials
PySpark is a powerful Python API for Apache Spark, a distributed computing framework that enables large-scale data processing. Spark History Spark was initially started by Matei Zaharia at UC Berkeley’s AMPLab in 2009, and open sourced in 2010 under a BSD license. In 2013, the project was donated to the Apache Software Foundation and switched…
In Apache Spark, data types are essential for defining the schema of your data and ensuring that data operations are performed correctly. Spark has its own set of data types that you use to specify the structure of DataFrames and RDDs. Understanding and using Spark’s data types effectively ensures that your data processing tasks are…