Building a high-performance data lake analytics engine at Alibaba Cloud with Presto+Alluxio

Data Lake Analytics(DLA) is a large scale serverless data federation service on Alibaba Cloud. One of its serverless analytics engine is based on Presto. The DLA Presto engine supports a variety of data sources and is widely used in different application scenarios in the cloud. In this session, we will talk about the system architecture of DLA Presto engine, as well as the challenges and solutions. In particular, we will introduce the use of alluxio local cache to solve performance issues on OSS data sources caused by access delay and OSS bandwidth limitation. We will discuss the principle of alluxio local cache and some improvements we have made.

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Using Alluxio to Optimize and Improve Performance of Kubernetes-Based Deep Learning in the Cloud

This article presents the collaborative work of Alibaba, Alluxio, and Nanjing University in tackling the problem of Artificial Intelligence and Deep Learning model training in the cloud. We adopted a hybrid solution with a data orchestration layer that connects private data centers to cloud platforms in a containerized environment. Various performance bottlenecks are analyzed with detailed optimizations of each component in the architecture.

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