What is PySpark ? What is Apache Spark | Apache Spark vs PySpark | PySpark Tutorial

Apache Spark vs PySpark

What is Apache Spark?

"Apache Spark is an open-source, distributed computing framework designed for big data processing. It was developed by UC Berkeley in 2009 and is now one of the most powerful tools for handling massive datasets."

🔥 Why is Spark So Popular?

  • ✔️ 100x faster than Hadoop – Uses in-memory computing.
  • ✔️ Supports multiple workloads – Batch, streaming, machine learning, and graph processing.
  • ✔️ Scales easily – Runs on clusters with thousands of nodes.

What is PySpark?

"Now that we understand Apache Spark, let's talk about PySpark. PySpark is simply the Python API for Apache Spark, allowing us to use Spark with Python instead of Scala or Java."

💎 Why Use PySpark?

  • ✔️ Python is easy to learn – Great for data engineers & scientists.
  • ✔️ Leverages Spark’s speed – Handles big data in a scalable way.
  • ✔️ Integrates with Pandas, NumPy, and Machine Learning libraries.

Apache Spark vs PySpark – Key Differences

Feature Apache Spark PySpark
Language Scala, Java Python
Ease of Use More complex Easier for beginners
Performance Faster (native) Slightly slower (Python overhead)
Community Support Strong (since 2009) Growing rapidly
Best For Large-scale data engineering Python-based big data & ML

Watch the Video Explanation!

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