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What is Differences Between Hadoop and Spark about?
Hadoop and Spark are distributed data processing frameworks. Hadoop uses HDFS for dedicated storage while Spark does not. Hadoop has average processing speed while Spark is excellent. Hadoop uses separate tools for libraries while Spark has integrated libraries. Some common uses of Hadoop include managing traffic data, streaming processing, content management, fraud detection, and analyzing customer data in real-time. Hadoop is different from other systems in that it uses a distributed file system to store
- Author
- dasari ramya
- Language
- EN