What is Apache Spark?
Apache Spark is a distributed data-processing engine for analysing large datasets across a cluster. It supports batch processing, SQL, streaming, and machine learning workloads.
Where is Apache Spark used?
- Large-scale data transformation
- ETL pipelines and analytics
- Streaming data processing
- Distributed machine learning
Prerequisites to learn Apache Spark
- Programming fundamentals
- Basic SQL and data-processing knowledge
- Python, Scala, or Java familiarity
Advantages of Apache Spark
- Scales beyond one machine
- Supports several workload types
- Rich APIs and ecosystem
- Fault-tolerant distributed execution
Limitations of Apache Spark
- Cluster tuning can be complex
- Overkill for small datasets
- Distributed debugging requires additional skills
Start learning Apache Spark
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