Introduction to Alluxio (formerly Tachyon)

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Abstract:

On-demand compute clusters are often used to save the cost of running and maintaining a continuous cluster for the sake of ad-hoc analysis. Such clusters also provide significant cost savings in storage, since data can be stored in a much cheaper medium, such as object storage. However, one critical downside which prevents on-demand compute clusters from becoming the norm for sporadic data analytics is the lack of high performance. Without co-locating compute and storage, queries and analysis may take unacceptably long periods of time, greatly reducing the value of gathering such insights.

To address this limitation, Alluxio is used as a lightweight data access layer on the compute nodes to bring performance up to memory speeds without requiring a long running cluster. This talk will summarize why Alluxio’s architecture makes it a perfect fit for completing the on-demand cluster puzzle.

Bio:

Calvin Jia is the top contributor to the Alluxio project and one of the earliest contributors. He started on the project as an undergraduate working in UC Berkeley’s AMPLab. He is currently a software engineer at Alluxio. Calvin has a BS from the University of California, Berkeley.