Spark Pipelines in the Cloud with Alluxio

Big Data Day LA *

In this talk, we discuss how Alluxio can be deployed and used with a Spark data processing pipeline in the cloud. We show how pipeline stages can share data with Alluxio memory for improved performance benefits, and how Alluxio can improves completion times and reduces performance variability for Spark pipelines in the cloud.

Using Alluxio (formerly Tachyon) to Speed Up Big Data Analytics [Chinese]

Strata Data Conference Beijing *

An overview of Alluxio basics, demonstrating how Alluxio works and how to use this system to enable distributed computation engines (like Spark or MapReduce) to share data at memory speed. Using hands-on exercises, Yupeng and Rong walk you through deploying and running Alluxio, mounting external storage systems (like S3) into Alluxio’s namespace, interacting Alluxio with built-in commands and WebUI, and building simple big data applications using common computation frameworks (e.g., Apache Spark and Hadoop MapReduce) to read from and write to Alluxio.

Best Practices for Using Alluxio with Spark

Strata Data Conference New York 2017 *

Haoyuan Li and Cheng Chang explain how Alluxio makes Spark more effective in both on-premises and public cloud deployments and share production deployments of Alluxio and Spark working together. Along the way, they discuss best practices for using Alluxio with Spark, including with RDDs and DataFrames.

Accelerating Spark Workloads in an Apache Mesos Environment with Alluxio

MesosCon North America 2017 *

Using Alluxio, an open-source memory speed virtual distributed storage system, deployed on Mesos enables connecting any compute framework, such as Apache Spark, to storage systems via a unified namespace. Alluxio enables applications to interact with any data at memory speed. Alluxio can eliminate the pains of ETL and data duplication, and enable new workloads across all data. Adit will discuss the architecture of Mesos, Spark and Alluxio to achieve an optimal architecture for enterprises.

Accelerating Spark Workloads in a Mesos Environment with Alluxio

MesosCon Europe 2017 *

Using Alluxio, a memory speed virtual distributed storage system, deployed on Mesos enables connecting any compute framework, such as Apache Spark, to storage systems via a unified namespace. Alluxio enables applications to interact with any data at memory speed. Alluxio can eliminate the pains of ETL and data duplication, and enable new workloads across all data. Gene will discuss the architecture of Mesos, Spark and Alluxio to achieve an optimal architecture for enterprises.

Best Practices For Using Apache Spark With Alluxio

Spark Summit Europe 2017 *

Many organizations and deployments use Alluxio with Apache Spark, and some of them scale out to over PB’s of data. Alluxio can enable Spark to be even more effective, in both on-premise deployments and public cloud deployments. Alluxio bridges Spark applications with various storage systems and further accelerates data intensive applications. In this talk, we briefly introduce Alluxio, and present different ways how Alluxio can help Spark jobs. We discuss best practices of using Alluxio with Spark, including RDDs and DataFrames, as well as on-premise deployments and public cloud deployments.

Apache Spark Pipelines in the Cloud with Alluxio

Spark Summit Europe 2017 *

In this talk, we discuss how Alluxio can be deployed and used with a Spark data processing pipeline in the cloud. We show how pipeline stages can share data with Alluxio memory for improved performance benefits, and how Alluxio can improves completion times and reduces performance variability for Spark pipelines in the cloud.

Two Sigma Open Source Meetup

New York Meetup *

TSOS meetups focus on the open source projects that Two Sigma cares most about, from projects we generated in-house then open sourced to large external open source projects that we depend on to do our work. This time, Wenbo Zhao (Two Sigma) and Bin Fan (Alluxio) will be presenting on how Two Sigma uses Alluxio to make data-intensive compute independent of the storage beneath.