Hue users can learn a lot about new features by following a steady stream of new demos.
Hue, the open source Web UI that makes Apache Hadoop easier to use, is now a standard across the ecosystem — shipping within multiple software distributions and sandboxes. One of the reasons for its success is an agile developer community behind it that is constantly rolling out new features to its users.
Integrating Hue with LDAP can help make your secure Hadoop apps as widely consumed as possible.
Hue, the open source Web UI that makes Apache Hadoop easier to use, easily integrates with your corporation’s existing identity management systems and provides authentication mechanisms for SSO providers. So, by changing a few configuration parameters, your employees can start analyzing Big Data in their own browsers under an existing security policy.
In this installment of “Meet the Engineer” we speak with Romain Rigaux, a Software Engineer on the Hue team.
What do you do at Cloudera, and in which project are you involved?
Currently I work on Hue, the open source Web interface that lets users do Big Data analysis directly from their browser. Its goal is to make that process easier,
The team behind Hue, the open source Web UI that makes Apache Hadoop easier to use, strikes again with a new Spark app.
Editor’s note: This post was recently published on the Hue blog. We republish it here for your convenience.
Hi Spark Makers!
A Hue application for Apache Spark (incubating) was recently created. It lets users execute and monitor Spark jobs directly from their browser and be more productive.
You can use Hue and Cloudera Search to build your own integrated Big Data search app.
In a previous post, you learned how to analyze data using Apache Hive via Hue’s Beeswax and Catalog apps. This time, you’ll see how to make Yelp Dataset Challenge data searchable by indexing it and building a customizable UI with the Hue Search app.
Indexing Data in Cloudera Search
Indexing data in Cloudera Search involves :
- Setting up SolrCloud to partition your dataset into multiple indexes and processes
- Configuring SolrCloud collections to hold indexes
- Specifying the schema by which indexes will be created
- Feeding relevant data into the SolrCloud