In the previous tutorial ”Getting Started with Spark Caching using Alluxio in 5 Minutes”, we demonstrated how to get started with Spark and Alluxio. To share more thoughts and experiments on how Alluxio enhances Spark workloads, this article focuses on how Alluxio helps to optimize the memory utilization of Spark applications. For users who are … Continued
Director of Solutions Engineering, Alluxio
As the data ecosystem becomes massively complex and more and more disaggregated, data analysts and end users have trouble adapting and working with hybrid environments. The proliferation of compute applications along with storage mediums leads to a hybrid model that we are just not accustomed to.
With this disaggregated system data engineers now come across a multitude of problems that they must overcome in order to get meaningful insights.
Apache Spark has brought significant innovation to Big Data computing, but its results are even more extraordinary when paired with Alluxio. Alluxio, provides Spark with a reliable data sharing layer, enabling Spark to excel at performing application logic while Alluxio handles storage. Bazaarvoice uses the combination of Spark and Alluxio to provide a real time big data platform that has the ability to not only handle the intake of 1.5 billion page views during peak events like Black Friday, but also provide real time analytics against it (read more). At this scale, the gain in speed is an enabler for new workloads. We’ve established a clean and simple way to integrate Alluxio and Spark.