From limited Hadoop compute capacity to increased data scientist efficiency

Alluxio Tech Talk *

This tech talk will share approaches to burst data to the cloud along with
how Alluxio can enable “zero-copy” bursting of Spark workloads to cloud data services like EMR and Dataproc. Learn how DBS bank uses Alluxio to solve for limited on-prem compute capacity.

Powering Data Science and AI with Apache Spark, Alluxio, and IBM

Alluxio Global Online Meetup *

In this online meetup, we will present the benefits of the fast analytics stack of Spark on Alluxio, and dive into China Unicom’s use case of leveraging Spark and Alluxio to process massive amounts of mobile data.

Effective Analytical Pipelines on AWS Using EMR, Alluxio, and S3

This article describes my lessons from a previous project which moved a data pipeline originally running on a Hadoop cluster managed by my team, to AWS using EMR and S3. The goal was to leverage the elasticity of EMR to offload the operational work, as well as make S3 a data lake where different teams can easily share data across projects.

Four Different Ways to Write to Alluxio

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.

Accelerating Write-intensive Data Workloads on AWS S3

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.