In this meetup, Dipti and HY will present a new approach to hybrid analytical workloads using Alluxio, an open source data orchestration layer, which sits between compute and storage layer. Applications like Apache Spark or TensorFlow can then seamlessly access multiple disparate data sources with consistent performance using data locality and abstraction that the data orchestration tier brings.
Alluxio is a proud sponsor and exhibitor at the Presto Summit in San Francisco.
What’s Presto Summit? It’s the leading Presto conference co-organized by our partner Starburst Data and the Presto Software Foundation.
This whitepaper details how to leverage any public cloud (AWS, Google Cloud Platform, or Microsoft Azure) to scale analytics workloads directly on on-prem data without copying and synchronizing the data into the cloud. We will show an example of what it might look like to run on-demand Starburst Presto, Spark, and Hive with Alluxio in the public cloud using on-prem HDFS.
The paper also includes a real world case study on Two Sigma, a leading hedge fund based in New York City, who deployed large clusters of Google Compute Engine VMs with Spark and Alluxio using on-prem HDFS as the underlying storage tier.
Tags: apache hive, apache spark, aws, case study, hybrid cloud, presto
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.
Tags: big data, cloud, cloud object storage, cloud storage, compute storage separation, data, data orchestration, hybrid cloud, multi cloud, on-prem object storage, storage
This webinar highlights 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.
Tags: aws, cloud, compute storage separation, data, data orchestration, emr, hybrid cloud, on-prem object storage, spark, webinar
While adding a higher-bandwidth dedicated circuit will help, Alluxio data orchestration addresses the hybrid problem by making the data local to the compute nodes.
The data orchestration layer bridging the gap between data locality with improved performance and data accessibility for analytics workloads in Kubernetes, and enables portability across storage providers.
An overview of Alluxio and the cloud use case with Spark in Kubernetes. Learn how to set up Alluxio and Spark to run in Kubernetes.
Tags: analytics, apache spark, compute, compute storage separation, data, data orchestration, hybrid cloud, kubernetes, locality, multi cloud, office hour, spark, storage
Haoyuan Li presents at Beijing Meetup on 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.
Tags: big data, cloud, cloud storage, compute storage separation, data, data orchestration, hybrid cloud, meetup, multi cloud, storage
As the data ecosystem becomes massively complex and more and more disaggregated, data analysts and end users have trouble adapting and working with hybrid environments. The proliferation of compute applications along with storage mediums leads to a hybrid model that we are just not accustomed to.
With this disaggregated system data engineers now come across a multitude of problems that they must overcome in order to get meaningful insights.