Spark
Definition
Open-source data processing engine that runs computations in memory rather than reading and writing to disk at each step.
Use Cases
- Netflix: Recommendation engine — Netflix uses Spark to process large volumes of viewing data in real-time, enabling the recommendation system to update quickly based on user interactions. (Improved user engagement and satisfaction by providing timely and relevant content recommendations.)
Provider Equivalents
- AWS: Amazon EMR
- Azure: Azure Synapse Analytics
- GCP: Google Cloud Dataproc
- OCI: Oracle Cloud Infrastructure Data Flow
Frequently Asked Questions
- What's the difference between Spark and Hadoop?
- Spark processes data in memory, making it faster for iterative tasks, while Hadoop writes intermediate results to disk, which can be slower but more reliable for batch processing.
- When should I use Spark?
- Use Spark for tasks requiring fast data processing, like real-time analytics, machine learning, and interactive querying, especially when working with large datasets.
- How much does Spark cost?
- Costs vary based on the cloud provider and resource usage. Managed services like AWS EMR, Azure Synapse, and GCP Dataproc charge based on compute and storage resources consumed.
Category: data
Difficulty: advanced
Related Terms
See Also