Ultra Fast Deep Learning in Hybrid Cloud Using Intel Analytics Zoo & Alluxio

Alluxio Global Online Meetup *

Today, many people run deep learning applications with training data from separate storage such as object storage or remote data centers. This presentation will demo the Intel Analytics Zoo + Alluxio stack, an architecture that enables high performance while keeping cost and resource efficiency balanced without network being I/O bottlenecked.

Optimizing Query Performance by Decoupling Presto and Hive Data Warehouse

Ideally, Presto would access data independently from how the data was originally stored or managed. Alluxio, as a data orchestration layer provides the physical data independence, for Presto to interact with the data more efficiently. In addition to caching for IO acceleration, Alluxio also provides a catalog service to abstract the metadata in the Hive Metastore, and transformations to expose the data in compute-optimized way. In this talk, we describe some of the challenges of using Presto with Hive, and introduce Alluxio data orchestration for solving those challenges.

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Serving Structured Data in Alluxio: Concept

This article introduces Structured Data Management available in the latest Alluxio 2.2.0 release, a new effort to provide further benefits to SQL and structured data workloads using Alluxio.

Enabling Ultra-fast Presto in the Cloud with Alluxio

This talk describes a stack of open-source projects to serve high-concurrent and low-latency SQL queries using Presto with Alluxio on big data in the cloud. Deploying Alluxio as a data orchestration layer to access cloud storage object storage (e.g., AWS S3), this architecture greatly enhances the data locality of Presto with distributed and cross-query caching, thus avoids reading the same data repeatedly from the cloud storage.

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