The Alluxio-Presto sandbox is a docker application featuring installations of MySQL, Hadoop, Hive, Presto, and Alluxio. The sandbox lets you easily dive into an interactive environment where you can explore Alluxio, run queries with Presto, and see the performance benefits of using Alluxio in a big data software stack.
Alluxio Resources
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The data orchestration layer bridging the gap between data locality with improved performance and data accessibility for analytics workloads in Kubernetes, and enables portability … Continued
Announcing the OEM partnership with Alluxio and Starburst Data, the company behind Presto, the fastest growing SQL query engine in a disaggregated world.
This webinar will describe the concept and internal mechanism using the stack of Spark+Alluxio in Kubernetes to enhance data locality even when the storage … Continued
Join us for this tech talk where we’ll introduce the Starburst Presto, Alluxio, and cloud object store stack for building a highly-concurrent and low-latency … Continued
This talk will guide the audience on how Alluxio can greatly simplify the data preparation phase in with remote and possibly multiple data sources. … Continued
Users deploy Alluxio in a wide range of use cases from analytics to AI platforms, for Alluxio's unified access to data and transparent caching … Continued
This office hour describes the concept and dataflow with respect to using the stack of Spark/Alluxio in Kubernetes with enhanced data locality even the … Continued
This talk describes a stack of open-source projects to serve high-concurrent and low-latency SQL queries using Presto with Alluxio on big data in the … Continued
Google Cloud Dataproc is a widely used fully managed Spark and Hadoop service to run big data analytics and compute workloads in the cloud. … Continued
If you’re a MapR user, you might have concerns with your existing data stack. Whether it’s the complexity of Hadoop, financial instability and no … Continued
Many Spark users may not be aware of the differences in memory utilization between caching data directly in-memory into the Spark JVM versus storing … Continued