Hadoop vs Spark: Which is Better for Big Data?
An example of an AI chatbot conversation about Hadoop and Spark for big data processing.
What's the difference between Hadoop and Spark?
Hadoop is a distributed storage and processing framework, while Spark is a fast data processing engine that can run on top of Hadoop.
Which one is faster for data processing?
Spark is generally faster than Hadoop because it processes data in-memory, reducing the time spent on disk I/O.
Can I use Spark without Hadoop?
Yes, Spark can run independently without Hadoop, but it can also leverage Hadoop's storage capabilities.
What are the use cases for each?
Hadoop is great for batch processing large datasets, while Spark excels in real-time data processing and analytics.
Which one should I choose for my project?
It depends on your specific needs. If you need real-time processing, go with Spark; for large batch jobs, Hadoop might be better.
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