In Detail
If you have always wanted to crunch billions of rows of raw data on Hadoop in a couple of seconds, then Cloudera Impala is the number one choice for you. Cloudera Impala provides fast, interactive SQL queries directly on your Apache Hadoop data stored in HDFS or HBase. In addition to using the same unified storage platform, Impala also uses the same metadata, SQL syntax (Hive SQL), ODBC driver, and user interface (Hue Beeswax) as Apache Hive. This provides a familiar and unified platform for batch-oriented or real-time queries.
In this practical, example-oriented book, you will learn everything you need to know about Cloudera Impala so that you can get started on your very own project. The book covers everything about Cloudera Impala from installation, administration, and query processing, all the way to connectivity with other third party applications. With this book in your hand, you will find yourself empowered to play with your data in Hadoop.
As a reader of this book, you will learn about the origin of Impala and the technology behind it that allows it to run on thousands of machines. You will learn how to install, run, manage, and troubleshoot Impala in your own Hadoop cluster using the step-by-step guidance provided in the book. The book covers tenets of data processing such as loading data stored in Hadoop into Impala tables and querying data using Impala SQL statements, all with various code illustrations and a real-world example.
The book is written to get you started with Impala by providing rich information so you can understand what Impala is, what it can do for you, and finally how you can use it to achieve your objective.
Approach
This book is an easy-to-follow, step-by-step tutorial where each chapter takes your knowledge to the next level. The book covers practical knowledge with tips to implement this knowledge in real-world scenarios. A chapter with a real-life example is included to help you understand the concepts in full.
Who this book is for
Using Cloudera Impala is for those who really want to take advantage of their Hadoop cluster by processing extremely large amounts of raw data in Hadoop at real-time speed. Prior knowledge of Hadoop and some exposure to HIVE and MapReduce is expected.
