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

Tags: , , , , , ,

Presto on Alluxio: How Netease Games leveraged Alluxio to boost ad hoc SQL on HDFS

Netease Games is the operator for many popular online games in China like “World of Warcraft” and “Hearthstone”. Netease Games also has developed quite a few popular games on its own such as “Fantasy Westward Journey 2”, “Westward Journey 2”, “World 3”, “League of Immortals”. The strong growth of the business drives the demand to build and maintain a data platform handling a massive amount of data and delivering insights promptly from the data. Given our data scale, it is very challenging to support high-performance ad-hoc queries to the data with results generated in a timely manner.

Providing a Unified Data Layer at Memory Speed for Cloud Environments with Huawei and Alluxio

The cloud is rapidly becoming ubiquitous, with continued adoption focused on the flexibility and cost benefits of a utility infrastructure model. Enterprises are increasingly taking a “data first” view of infra- structure, which demands a new way of thinking in a world in which data is stored and accessed from multiple locations and providers. Performance and interoperability challenges, however, can present obstacles to cloud adoption and complicate data management. Techniques such as the use of data silos, ETL processes and multiple data copies, which are commonly employed to accommodate cloud limitations, often tend to offset the expected benefits of cloud infrastructure. Alluxio offers a new way to enhance the benefits of cloud infra- structure without the performance limitations or interoperability challenges resulting from accessing disparate data sources in multiple, often remote, locations.

Tags: , , , ,

TalkingData Case Study: Leading Data Broker in China Leverages Alluxio to Unify Terabytes of Data Across Disparate Data Sources

TalkingData’s largest data broker, provides data intelligence solutions and processes over 20 terabytes of data and more than one billion session requests per day. TalkingData deployed Alluxio to unify disparate cloud, on-premise, and hybrid data sources for a range of analytics applications. The architecture provides self-service data access for data scientists and engineers, eliminating the need for ETL or manual IT assistance.

Tags: , , , ,

TalkingData: Leading Data Broker in China Leverages Alluxio to Unify Terabytes of Data Across Disparate Data Sources

TalkingData leverages Alluxio as a single platform to manage all the data across disparate data sources on-premise and in the cloud. Alluxio removes the complexity of our environment by abstracting the different data sources and providing a unified interface. Applications simply interact with Alluxio, and Alluxio manages data access to different storage systems on behalf of the applications. Alluxio effectively democratizes data access, allowing data scientists and analysts in various business units to accomplish their goals without needing to consider where the data is located or having to go to central IT or the engineering team to transfer or prepare the data.