By Edward Capriolo, Dean Wampler
Need to maneuver a relational database software to Hadoop? This complete advisor introduces you to Apache Hive, Hadoop’s information warehouse infrastructure. You’ll fast tips on how to use Hive’s SQL dialect—HiveQL—to summarize, question, and examine huge datasets saved in Hadoop’s dispensed filesystem.
This example-driven consultant indicates you the way to establish and configure Hive on your setting, offers a close evaluate of Hadoop and MapReduce, and demonstrates how Hive works in the Hadoop atmosphere. You’ll additionally locate real-world case stories that describe how businesses have used Hive to resolve designated difficulties concerning petabytes of data.
- Use Hive to create, regulate, and drop databases, tables, perspectives, capabilities, and indexes
- Customize facts codecs and garage suggestions, from documents to exterior databases
- Load and extract information from tables—and use queries, grouping, filtering, becoming a member of, and different traditional question methods
- Gain top practices for growing consumer outlined services (UDFs)
- Learn Hive styles you can use and anti-patterns you want to avoid
- Integrate Hive with different facts processing programs
- Use garage handlers for NoSQL databases and different datastores
- Learn the professionals and cons of working Hive on Amazon’s Elastic MapReduce
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Extra resources for Programming Hive
On your Maven venture, create a pom. xml and comprise hive_test as a dependency, as proven right here: