How do you run Spark on On-Premise S3?

Introducing S3 and Spark S3 has become the de-facto standard API for digital business applications to store unstructured data chunks. To this end, several vendors have S3-API compatible offerings that allow app developers to standardize on the S3 API’s on-premise, and port these apps to run on other platforms when ready. So, what is S3 and … Continued

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Two Sigma Case Study – Cloud bursting with Spark for on-premise Hadoop

Two Sigma, a leading hedge fund with more than $50 billion under management, turned to Alluxio for help with bursting Spark workloads in a public cloud to enable hybrid workloads for on-premise HDFS. With Alluxio, Two Sigma sees better performance, increased flexibility and dramatically lower costs with the number of model runs per day increased by 4x and the cost of compute reduced by 95%.

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China Unicom Uses Alluxio and Spark to Build New Computing Platform to Serve Mobile Users

Abstract China Unicom is one of the five largest telecom operators in the world. China Unicom’s booming business in 4G and 5G networks has to serve an exploding base of hundreds of millions of smartphone users. This unprecedented growth brought enormous challenges and new requirements to the data processing infrastructure. The previous generation of its … Continued

Getting Started with Alluxio and Spark in 5 Minutes

Introduction Apache Spark has brought significant innovation to Big Data computing, but its results are even more extraordinary when paired with Alluxio. Alluxio, provides Spark with a reliable data sharing layer, enabling Spark to excel at performing application logic while Alluxio handles storage. Bazaarvoice uses the combination of Spark and Alluxio to provide a real time … Continued

Achieving 10x acceleration of Spark and Hive Jobs on AWS S3 with Alluxio Tiered Storage

The data engineering team at Bazaarvoice, a software-as-a-service digital marketing company based in Austin, Texas, must handle data at massive Internet-scale to serve its customers. Facing challenges with scaling their storage capacity up and provisioning hardware, they turned to Alluxio’s tiered storage system and saw 10x acceleration of their Spark and Hive jobs running on AWS S3.

In this whitepaper you’ll learn:

  • How to build a big data analytics platform on AWS that includes technologies like Hive, Spark, Kafka, Storm, Cassandra, and more
  • How to setup a Hive metastore using a storage tier for hot tables
  • How to leverage tiered storage for maximized read performance

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Accelerate Spark and Hive Jobs on AWS S3 by 10x with Alluxio Tiered Storage

In this article, Thai Bui from Bazaarvoice describes how Bazaarvoice leverages Alluxio to build a tiered storage architecture with AWS S3 to maximize performance and minimize operating costs on running Big Data analytics on AWS EC2. This blog is an abbreviated version of the full-length technical whitepaper (coming soon) which aims to provide the following takeaways: Common … Continued

One Click to Benchmark Spark + Alluxio + S3 Stack with TPC-DS queries on AWS

The Alluxio sandbox is the easiest way to test drive the popular data analytics stack of Spark, Alluxio, and S3 deployed in a multi-node cluster in a public cloud environment. The sandbox cluster is fully configured and ready for users to run applications ranging from the hello-world example to the TPC-DS benchmark suite. Don’t take our word … Continued

Top 10 Tips for Making the Spark + Alluxio Stack Blazing Fast

The Apache Spark + Alluxio stack is getting quite popular particularly for the unification of data access across S3 and HDFS. In addition, compute and storage are increasingly being separated causing larger latencies for queries. Alluxio is leveraged as compute-side virtual storage to improve performance. But to get the best performance, like any technology stack, you need to follow the … Continued