TFiR – Open Source & Emerging Technologies In this interview we spoke to Haoyuan (H.Y.) Li, Founder, Chairman and CTO of Open Source Alluxio, a company that is democratizing data in the cloud.
Alluxio video presentations
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.
Haoyuan Li’s keynote at O’Reilly Beijing discusses open source data orchestration and the value of leveraging Alluxio with rising trends driving the need for a new architecture. Four big trends driving this need: Separation of compute & storage, hybrid-multi cloud environments, rise of object store and self-service data across the enterprise.
While running analytics workloads using EMR Spark on S3 is a common deployment today, many organizations face issues in performance and consistency. EMR can be bottlenecked when reading large amounts of data from S3, and sharing data across multiple stages of a pipeline can be difficult as S3 is eventually consistent for read-your-own-write scenarios.
A simple solution is to run Spark on Alluxio as a distributed cache for S3. Alluxio stores data in memory close to Spark, providing high performance, in addition to providing data accessibility and abstraction for deployments in both public and hybrid clouds.
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 preview release, now available for download, includes many advancements that will allow users to push the limits of their data-workloads in the cloud.
As data analytic needs have increased with the explosion of data, the importance of the speed of analytics and the interactivity of queries has increased dramatically.
In this tech talk, we will introduce the Starburst Presto, Alluxio, and cloud object store stack for building a highly-concurrent and low-latency analytics platform. This stack provides a strong solution to run fast SQL across multiple storage systems including HDFS, S3, and others in public cloud, hybrid cloud, and multi-cloud environments.
Enterprises are increasingly looking towards object stores to power their big data & machine learning workloads in a cost-effective way. The combination of SwiftStack and Alluxio together, enables users to seamlessly move towards a disaggregated architecture. Swiftstack provides a massively parallel cloud object storage and multi-cloud data management system. Alluxio is a data orchestration layer, which sits between compute frameworks and storage systems and enables big data workloads to be deployed directly on SwiftStack. Alluxio provides data locality, accessibility and elasticity via its core innovations. With the Alluxio and Swiftstack solution, Spark, Presto, Tensorflow and Hive and other compute workloads can benefit from 10X performance improvement and dramatically lower costs. In this tech talk, we will provide a brief overview of the Alluxio and SwiftStack solution as well as the key use cases it enables.
The rise of compute intensive workloads and the adoption of the cloud has driven organizations to adopt a decoupled architecture for modern workloads – one in which compute scales independently from storage. While this enables scaling elasticity, it introduces new problems – how do you co-locate data with compute, how do you unify data across multiple remote clouds, how do you keep storage and I/O service costs down and many more.
Enter Alluxio, a virtual unified file system, which sits between compute and storage that allows you to realize the benefits of a hybrid cloud architecture with the same performance and lower costs.
We briefly introduce Alluxio and present different ways Alluxio can help Spark jobs, along with best practices. We also discuss how Alluxio can be deployed and used with a Spark data processing pipeline in the cloud.