Learn how to set up EMR Spark with Alluxio so Spark jobs can seamlessly read from and write to S3. See the performance comparison between Spark on S3 with Spark, and Alluxio on S3.
Slides from our latest talks
Bay Area Meetup which include presentations on the architecture of Presto, its separation of compute and storage, cloud-readiness, recent advancements in the project such as Cost-Based Optimizer and Kubernetes Support. Presto and Alluxio production use cases and more.
Alluxio’s first cloud, data & orchestration Austin meetup featuring talks and demos on efficient data engineering with Apache Spark, Hive and Alluxio on S3.
Kubernetes is widely used across enterprises to orchestrate computation. And while Kubernetes helps improve flexibility and portability for computation in public/hybrid cloud environments across infrastructure providers, running data-intensive workloads can be challenging.
When it comes to efficiently moving data closer to Spark or Presto frameworks, co-locating data with these frameworks and accessing data from multiple or remote clouds is hard to do. That’s where Alluxio, an open source data orchestration platform, can help.
Alluxio enables data locality with your Spark and Presto workloads for faster performance and better data accessibility in Kubernetes. It also provides portability across storage providers.
In this on demand tech talk we’ll give a quick overview of Alluxio and the use cases it powers for Spark/Presto in Kubernetes. We’ll show you how to set up Alluxio and Spark/Presto to run in Kubernetes as well.
Alluxio 2.0 is the most ambitious platform upgrade since the inception of Alluxio with greatly expanded capabilities to empower users to run analytics and AI workloads on private, public or hybrid cloud infrastructures leveraging valuable data wherever it might be stored.
This release, now available for download, includes many advancements that will allow users to push the limits of their data-workloads in the cloud.
In this tech talk, we will introduce the key new features and enhancements such as:
This meetup presents an overview of the motivations and design decisions behind the major changes in the Alluxio 2.0 release, and Real-time Data Processing for Sales Attribution Analysis with Alluxio, Spark and Hive at VIPShop.
Joint hosted Alluxio New York meetup with talks to include: Embracing hybrid cloud for data-intensive analytic workloads and Alluxio on AWS EMR (fast storage access and sharing for Spark).
Alluxio maintainer and founding engineer Calvin Jia presents on Scalable Filesystem Metadata Services with RocksDB at the RocksDB meetup at Twitter.
The ever increasing challenge to process and extract value from exploding data with AI and analytics workloads makes a memory centric architecture with disaggregated storage and compute more attractive. This decoupled architecture enables users to innovate faster and scale on-demand. Enterprises are also increasingly looking towards object stores to power their big data & machine learning workloads in a cost-effective way. However, object stores don’t provide big data compatible APIs as well as the required performance.
In this webinar, the Intel and Alluxio teams will present a proposed reference architecture using Alluxio as the in-memory accelerator for object stores to enable modern analytical workloads such as Spark, Presto, Tensorflow, and Hive. We will also present a technical overview of Alluxio.