Starting in Cloudera Enterprise 5.5, Cloudera Navigator offers interactive visual analytics that help answer important questions about the data that’s in your CDH clusters.
The new analytics system in Cloudera Navigator shows the distribution of data along various metadata dimensions and supports interactive filtering and grouping with a simple point-and-click interface. This new functionality a great complement to Cloudera Navigator’s search capabilities and is integrated with Navigator’s policy engine,
Bet you didn’t know this: In some cases, Solr offers lightning-fast response times for business-style queries.
If you were to ask well informed technical people about use cases for Solr, the most likely response would be that Solr (in combination with Apache Lucene) is an open source text search engine: one can use Solr to index documents, and after indexing, these same documents can be easily searched using free-form queries in much the same way as you would query Google.
Learn how to build an Impala table around data that comes from non-Impala, or even non-SQL, sources.
As data pipelines start to include more aspects such as NoSQL or loosely specified schemas, you might encounter situations where you have data files (particularly in Apache Parquet format) where you do not know the precise table definition. This tutorial shows how you can build an Impala table around data that comes from non-Impala or even non-SQL sources,
The super-active Apache Spark community is exerting a strong gravitational pull within the Apache Hadoop ecosystem. I recently had that opportunity to ask Cloudera’s Apache Spark committers (Sean Owen, Imran Rashid [PMC], Sandy Ryza, and Marcelo Vanzin) for their perspectives about how the Spark community has worked and is working together, and the work to be done via the One Platform initiative to make the Spark stack enterprise-ready.
YCSB, the open standard for comparative performance evaluation of data stores, is now available to CDH users for their Apache HBase deployments via new packages from Cloudera Labs.
Many factors go into deciding which data store should be used for production applications, including basic features, data model, and the performance characteristics for a given type of workload. It’s critical to have the ability to compare multiple data stores intelligently and objectively so that you can make sound architectural decisions.