Self-service BI and exploratory analytics are some of the most common use cases we see our customers running on Cloudera’s analytic database solution. Over the past year, we made significant advancements to provide a more powerful user experience for SQL developers and make them more productive for their everyday self-service BI tasks and workflows. Leveraging Hue as the SQL development workbench, we continue to see usage of the platform increase and the number of analytic use cases grow –
Successful cluster administration can be very difficult without a real-time view of the state of the cluster. Solr itself does not provide aggregated views about its state or any historical usage data, which is necessary to understand how the service is used and how it is performing. Knowing the throughput and capacities not only helps detect errors and troubleshoot issues, but is also useful for capacity planning.
Questions may arise, such as:
- What is the size of my cluster and each collection?
Configuring Apache Solr memory properly is critical for production system stability and performance. It can be hard to find the right balance between competing goals. There are also multiple factors, implicit or explicit, that need to be taken into consideration. This blog talks about some common tasks in memory tuning and guides you through the process to help you understand how to configure Solr memory for a production system.
For simplicity, this blog applies to Solr in Cloudera CDH5.11 running on top of HDFS.
Cloudera Search (that is Apache Solr integrated with the Apache Hadoop eco-system) now supports (as of C5.9) a backup and disaster recovery capability for Solr collections.
In this post we will cover the basics of the backup and disaster recovery capability in Solr and hence in Cloudera Search. In the next post we will cover the design of the Solr snapshots functionality and its integration with the Hadoop ecosystem as well as public cloud platforms (e.g.
Organizations analyze logs for a variety of reasons. Some typical use cases include predicting server failures, analyzing customer behavior, and fighting cybercrime. However, one of the most overlooked use cases is to help companies write better software. In this digital age, most companies write applications, be it for its employees or external users. The cost of faulty software can be severe, ranging from customer churn to a complete firm’s demise, as was the case with Knight Capital in 2012.