Cloudera’s new “Designing and Building Big Data Applications” is a great springboard for writing apps for an enterprise data hub.
Cloudera’s vision of an enterprise data hub as a central, scalable repository for all your data is changing the notion of data warehousing. The best way to gain value from all of your data is by bringing more workloads to where the data lives. That place is Apache Hadoop.
The conclusion to this series covers how to use scans, and considerations for choosing the Thrift or REST APIs.
In this series of how-tos, you have learned how to use Apache HBase’s Thrift interface. Part 1 covered the basics of the API, working with Thrift, and some boilerplate code for connecting to Thrift. Part 2 showed how to insert and to get multiple rows at a time.
The second how-to in a series about using the Apache HBase Thrift API
Last time, we covered the fundamentals about connecting to Thrift via Python. This time, you’ll learn how to insert and get multiple rows at a time.
Working with Tables
Using the Thrift interface, you can create or delete tables. Let’s take a look at the Python code that creates a table:
We at Cloudera University have been busy lately, building and expanding our courses to help data professionals succeed. We’ve expanded the Hadoop Administrator course and created a new Data Analyst course. Now we’ve updated and relaunched our course on Apache HBase to help more organizations adopt Hadoop’s real-time Big Data store as a competitive advantage.
The course is designed to make sure developers and administrators with an HBase use case can start realizing value from day one.
There are various way to access and interact with Apache HBase. Most notably, the Java API provides the most functionality. But some people want to use HBase without Java.
Those people have two main options: One is the Thrift interface (the more lightweight and hence faster of the two options), and the other is the REST interface (aka Stargate). A REST interface uses HTTP verbs to perform an action.