November 2013
Intermediate to advanced
34 pages
33m
English
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Conclusion
In this article, you have learned how Impala fits into the Hadoop software stack:
- Querying data files stored in HDFS.
- Enabling interactive queries for data originally managed by Hive. Using Hive where convenient for some ETL tasks, then querying the data in Impala.
- Providing a SQL frontend for data managed by HBase.
- Using data files produced by MapReduce, Pig, and other Hadoop components.
- Utilizing data formats from simple (text), to compact and efficient (Avro, RCFile, SequenceFile), to optimized for data warehouse queries (Parquet).
You have seen the interesting benefits Impala brings to users coming from different backgrounds:
- For Hadoop users, how Impala brings the familiarity and flexibility of fast, interactive SQL to the Hadoop world.
- For database users, how the combination of Hadoop and Impala makes it simple to set up a distributed database for data warehouse-style queries.
You have gotten a taste of what is involved in setting up Impala, loading data, and running queries.
The rest is in your hands!
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.