In this talk, we will describe how we have solved an issue with large S3 API costs incurred by Presto under several usage concurrency levels by implementing Alluxio as a data orchestration layer between S3 and Presto. Also, we will show the results of an experiment with estimating the per-query S3 API costs using the TPC-DS dataset.
Tag: data orchestration
This blog explores an innovative platform with Presto as the computing engine and Alluxio as a data orchestration layer between Presto and S3 storage, to support online services with instantaneous response within the gaming industry. The preliminary results show that Presto with Alluxio outperforms S3 significantly in all cases.Alluxio with metadata caching shows up to 5.9x performance gain when handling large numbers of small files.
Join us for this webinar where Alex Ma of Alluxio, an open source data orchestration platform, will discuss how a data orchestration approach offers a solution for connecting traditional on-prem data centers with the cloud, data centers with other data centers, and clouds with other clouds. With Alluxio’s “zero-copy” burst solution, companies can bridge remote data centers with computing frameworks in other locations, enabling them to offload compute and leverage the flexibility, scalability, and power of the cloud for their remote data.
Adit Madan and Parviz Peiravi offer an overview of the Alluxio data orchestration layer that provides a unified data access layer for hybrid and multi cloud deployments, leveraging Intel® Optane™ Persistent Memory for higher performance caching at reduced cost. The data access layer enables distributed compute engines like Presto, TensorFlow, and PyTorch to transparently access data from various storage systems (including S3, HDFS, and Azure) while actively leveraging a multi-tier cache to accelerate data access.
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.
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.
This talk will overview two projects at Electronic Arts (EA) that address the mismatch by data orchestration: One project automatically generates configurations for all components in a large monitoring system, which reduces the daily average number of alerts from ~1000 to ~20. The other project introduces Alluxio for caching and unifying address space across ETL and analytics workloads, which substantially simplifies architecture, improves performance, and reduces ops overheads.
For data-driven workloads in disaggregated stacks, there’s no native data access layer within a Kubernetescluster. For query engines and machine learning frameworks that are deployed within a Kubernetes cluster, any critical data sitting outside the cluster breaks locality. Alluxio can help.
The rise of compute intensive workloads and the adoption of the cloud has driven organizations to adopt a decoupled architecture for modern workloads – one in which compute scales independently from storage. While this enables scaling elasticity, it introduces new problems – how do you co-locate data with compute, how do you unify data across multiple remote clouds, how do you keep storage and I/O service costs down and many more.