With the advent of the Big Data era, it is usually computationally expensive to calculate the resource usages of a SQL query. Can we estimate the resource usages of SQL queries more efficiently without any computation in a SQL engine kernel? In this session, Chunxu and Beinan would like to introduce how Twitter’s data platform leverages a machine learning-based approach in Presto and BigQuery to estimate query utilization with 90%+ accuracy.
Tag: machine learning
This talk introduces the three game level progressions to use Alluxio to speed up your cloud training with production use cases from Microsoft, Alibaba, and BossZhipin.
As more and more companies turn to AI / ML / DL to unlock insight, AI has become this mythical word that adds unnecessary barriers to new adaptors. Oftentimes it was regarded as luxury for those big tech companies only – this should not be the case.
With machine learning (ML) and artificial intelligence (AI) applications becoming more business-critical, organizations are in the race to advance their AI/ML capabilities. To realize the full potential of AI/ML, having the right underlying machine learning platform is a prerequisite.
This article will discuss a new solution to orchestrating data for end-to-end machine learning pipelines that addresses the above questions. I will outline common challenges and pitfalls, followed by proposing a new technique, data orchestration, to optimize the data pipeline for machine learning.
2021 marked accelerated growth for the Alluxio Open Source Project. We could not be more grateful for what the community has achieved together in this past year. This blog provides a glimpse of the year long summary of our community growth.
This blog is the last one in the machine learning series. Our first blog introduced the what and why of our solution, and the second blog compared traditional and Alluxio solutions. This blog will demonstrate how to set up and benchmark the end-to-end performance of the training process.
This blog is the second in the machine learning series following the previous one, which discussed Alluxio’s solution to improve training performance and simplify data management. With the help of Alluxio, loading data from cloud storage, training and caching data can be done in a transparent and distributed way as a part of the training process, thus improving training performance and simplifying data management. In this blog 2 of the series, we focus on comparing traditional solutions with Alluxio’s.
In this blog, we provide an overview of Alluxio’s AI/ML model training solution. For more details about the reference architecture and benchmarking results, please refer to the full length whitepaper.