In this chapter, you have learned how to use various SQL statements in Impala. The example covers various aspects of data transformation and data processing. I hope by using the preceding examples, you could learn the SQL statements and functions described in detail in Chapter 3, The Impala Query Language and Built-in Functions. You can continue working on this autos database and the automobiles and motorcycles table to learn other SQL clauses and built-in functions as well. The main reason you should use Impala instead of Hive is the great increase in query-processing speed. The execution time for the first query in both Apache Hive and Impala will be nearly the same. However, for the subsequent queries, you will see a tremendous increase in the speed of query execution. This results in new real-time performance to justify your use of Impala.

In Chapter 5, Impala Administration and Performance Improvements, we are going to learn how to administer and manage Impala to improve performance and keep it running in the high-availability mode.