Apache Impala

1. Interactive SQL Queries: Fast and interactive SQL queries on data stored in Hadoop clusters.

2. Massively Parallel Processing (MPP): High-performance processing of large-scale datasets in parallel.

3. Real-Time Analytics: Low-latency query execution for real-time data exploration and analysis.

4. SQL Compatibility: Supports SQL-92 and SQL-2003 standards for a wide range of SQL syntax.

Before learning Apache Impala, it's beneficial to have the following skills:

1. SQL Knowledge: Proficiency in SQL query language for data manipulation and analysis.

2. Hadoop Ecosystem: Understanding of the Hadoop ecosystem components and their roles, including HDFS, Hive, and HBase.

3. Distributed Computing Concepts: Familiarity with distributed computing concepts like parallel processing and fault tolerance.

4. Data Modeling: Knowledge of data modeling techniques and best practices for designing efficient data schemas.

By learning Apache Impala, you gain the following skills:

1. Real-Time SQL Analytics: Ability to perform real-time SQL queries and analytics on large datasets stored in Hadoop clusters.

2. Data Exploration and Analysis: Proficiency in exploring and analyzing big data using interactive SQL queries.

3. Query Optimization: Skill in optimizing SQL queries for performance and efficiency in distributed environments.

4. Integration with Hadoop Ecosystem: Knowledge of integrating Impala with other Hadoop ecosystem components like HDFS, Hive, and HBase.