January 11, 2020
Score 8 out of 10
Read Yogesh Mhasde's full review
Pros and Cons
- DataFrames, DataSets, and RDDs.
- Spark has in-built Machine Learning library which scales and integrates with existing tools.
- The data processing done by Spark comes at a price of memory blockages, as in-memory capabilities of processing can lead to large consumption of memory.
- The caching algorithm is not in-built in Spark. We need to manually set up the caching mechanism.