How does Impala achieve faster query performance compared to Hive?
- Caching Intermediate Results
- Data Partitioning
- In-memory Processing
- Query Compilation
Impala achieves faster query performance compared to Hive by utilizing in-memory processing. Unlike Hive, which relies on MapReduce and disk-based processing, Impala keeps frequently accessed data in memory, reducing query latency and improving overall performance.
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