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.
Before CDH 5.10, every CDH cluster had to have its own Apache Hive Metastore (HMS) backend database. This model is ideal for clusters where each cluster contains the data locally along with the metadata. In the cloud, however, many CDH clusters run directly on a shared object store (like Amazon S3), making it possible for the data to live across multiple clusters and beyond any cluster’s lifespan. In this scenario clusters need to regenerate and coordinate metadata for the underlying shared data individually.
After the GA of Apache Kudu in Cloudera CDH 5.10, we take a look at the Apache Spark on Kudu integration, share code snippets, and explain how to get up and running quickly, as Kudu is already a first-class citizen in Spark’s ecosystem.
As the Apache Kudu development team celebrates the initial 1.0 release launched on September 19, and the most recent 1.2.0 version now GA as part of Cloudera’s CDH 5.10 release,
You may have heard of the recent (and ongoing) hacks targeting open source database solutions like MongoDB and Apache Hadoop. From what we know, an unknown number of hackers scanned for internet-accessible installations that had been set up using the default, non-secure configuration. Finding the exposure, these hackers then accessed the systems and in some cases deleted the files or held them for ransom.
These attacks were not technologically sophisticated,
In Part 1 of the blog, we covered all the prerequisites needed to deploy a CDH cluster on the Microsoft Azure cloud platform. In Part 2, we will cover the resources required on the Azure platform and actually deploy a cluster with Cloudera Director.
Cloudera Director Use Case
Cloudera Director simplifies cluster creation and lessen the time to an operational cluster on the cloud. It’s a great tool for running POCs in your organization.