Alluxio 2.3.0 focuses on streamlining the user experience in hybrid cloud deployments where Alluxio is deployed with compute in the cloud to access data on-prem. Features such as environment validation tools and concurrent metadata synchronization greatly improve Alluxio’s functionality. Integrations with AWS EMR, Google Dataproc, K8s, and AWS Glue make Alluxio easy to use in a variety of cloud environments. In this article, we will share some of the highlights of the release. For more, please visit our release notes page.
Software Engineer, Alluxio
With this release comes the General Availability (GA) of Alluxio Structured Data Services (SDS), the subsystem of Alluxio responsible for managing and transforming structured data, such as databases, tables, and partitions.
Alluxio is a new layer on top of under storage systems that can not only improve raw I/O performance but also enables applications flexible options to read, write and manage files. This article focuses on describing different ways to write files to Alluxio, realizing the tradeoffs in performance, consistency, and also the level of fault tolerance compared to HDFS.
Alluxio is an open-source data orchestration system widely used to speed up data-intensive workloads in the cloud. Alluxio v2.0 introduced Replicated Async Write to allow users to complete writes to Alluxio file system and return quickly with high application performance, while still providing users with peace of mind that data will be persisted to the chosen under storage like S3 in the background.
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.
Testing distributed systems at scale is typically a costly yet necessary process. At Alluxio we take testing very seriously as organizations across the world rely on our technology, therefore, a problem we want to solve is how to test at scale without breaking the bank. In this blog we are going to show how the maintainers of the Alluxio open source project build and test our system at scale cost-effectively using public cloud infrastructure. We test with the most popular frameworks, such as Spark and Hive, and pervasive storage systems, such as HDFS and S3. Using Amazon AWS EC2, we are able to test 1000+ worker clusters, at a cost of about $16 per hour.