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Articles by Ryan Bosshart
Getting Started with Kudu
Where’s the cart? Now you can get everything on Safari . To purchase books, visit Amazon or your favorite retailer. Questions? See our FAQ or contact customer service: Get up to speed with Apache Kudu, the column-oriented data store for Hadoop that not only provides an architectural simplification of several existing use cases, but also allows use cases not possible before.
How do I create a Kudu table via SQL?
Apache Impala is an open source distributed SQL query engine made for the Hadoop ecosystem, that integrates seamlessly with Kudu. In this video, Ryan Bosshart demonstrates how to use Impala’s lightning-fast SQL analytics layer on top of Kudu. All that is needed to follow along is access to the Kudu Quickstart VM. Beginner architects, developers, and data engineers will be able to: Take your Kudu skills to the next level with the full course, Basic Kudu Installation, API Usage, and SQL Integration.
What is hash partitioning in Kudu?
Proper schema and partitioning design is essential for Kudu performance. In this video, Ryan Bosshart explains how hash partitioning paired with range partitioning can be used to improve operational stability. Architects, developers, and data engineers designing new tables in Kudu will learn: Sign up for Safari and get 10 days of free access to the full Introducing Kudu and Kudu Architecture course.
How can I bulk-load data from HDFS to Kudu using Apache Spark?
Apache Spark dominates the big data landscape with its ability to process data on a large scale and handle machine learning workloads. In this video Ryan Bosshart explains how to pair Spark with the Hadoop storage layer for easy, scalable data storage. All you need to follow along is IntelliJ IDEA and access to Kudu Quickstart VM. Data architects and developers will be able to: Continue learning Kudu with our Using Kudu with Apache Spark and Apache Flume course.
Basic Kudu Installation, API Usage, and SQL Integration
Apache Kudu is a required skill in the Big Data world because it addresses problems that are difficult or impossible to implement on current generation Hadoop storage technologies. Big data developers, architects, and engineers looking to add this skill can do so with this easy to understand hands-on exploration of Kudu's basics.
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