{"id":11174,"date":"2018-03-22T10:12:24","date_gmt":"2018-03-22T10:12:24","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=11174"},"modified":"2021-05-09T13:11:26","modified_gmt":"2021-05-09T07:41:26","slug":"impala-tutorial","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/impala-tutorial\/","title":{"rendered":"Impala Tutorial for Beginners | Impala Hadoop Tutorial"},"content":{"rendered":"

Basically, to overcome the slowness of Hive Queries, Cloudera offers a separate tool and that tool is what we call Impala. However, there is much more to know about the Impala. <\/span><\/p>\n

So, in this Impala Tutorial for beginners, we will learn the whole concept of Cloudera Impala. It includes Impala’s benefits, working as well as its features. Moreover, we will also learn about Daemons in Impala in this Impala Tutorials.<\/span><\/p>\n

What is Impala? – An Impala Overview
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A tool which we use to overcome the slowness of Hive Queries is what we call Impala. This separate tool was provided by Cloudera distribution. Syntactically Impala queries run very faster than Hive Queries even after they are more or less same as Hive Queries. <\/span><\/p>\n

It offers high-performance, low-latency SQL queries. Impala is the best option while we are dealing with medium sized datasets and we expect the real-time response from our queries. However, make sure Impala is available only in Hadoop<\/strong> distribution. <\/span>
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\n<\/span>Since MapReduce store intermediate results in the file system, Impala is not built on MapReduce<\/strong>. Hence, it is very slow for real-time query processing.<\/p>\n

In addition, Impala has its own execution engine. Basically, that stores the intermediate results in In-memory. Therefore, when compared to other tools which use MapReduce its query execution is very fast.<\/span>
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\nSome Key Points<\/strong><\/p>\n