This talk describes the design of shadow cache, a lightweight component to track the working set size of Alluxio cache. Shadow cache can keep track of the working set size over the past window dynamically, and is implemented by a series of bloom filters. We’ve deployed the shadow cache in Facebook Presto and leverage the result to understand the system bottleneck and help with routing design decisions.
Nowadays it is not straightforward to integrate Alluxio with popular query engines like Presto on existing Hive data. Solutions proposed by the community like Alluxio Catalog Service or Transparent URI brings unnecessary pressure on Alluxio masters when querying files should not be cached.
RaptorX is an internal project name aiming to boost query latency significantly beyond what vanilla Presto is capable of. For this session, we introduce the hierarchical cache work including Alluxio data cache, fragment result cache, etc. Cache is the key building block for RaptorX.
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.
JD.com is one of the largest e-commerce corporations. In big data platform of JD.com, there are tens of thousands of nodes and tens of petabytes off-line data which require millions of spark and MapReduce jobs to process everyday. As the main query engine, thousands of machines work as Presto nodes and Presto plays an import role in the field of In-place analysis and BI tools. Meanwhile, Alluxio is deployed to improve the performance of Presto. The practice of Presto & Alluxio in JD.com benefits a lot of engineers and analysts.
Presto & Alluxio on AWS: How we build a Up-To-Date Data-Platform at Ryte.
Presto, an open source distributed SQL engine, is widely recognized for its low-latency queries, high concurrency, and native ability to query multiple data sources. Proven at scale in a variety of use cases at Comcast, GrubHub, FINRA, LinkedIn, Lyft, Netflix, Slack, Zalando, in the last few years Presto experienced an unprecedented growth in popularity in both on-premises and cloud deployments over Object Stores, HDFS, NoSQL and RDBMS data stores.
For many latency-sensitive SQL workloads, Presto is often bound by retrieving distant data. In this talk, Rohit Jain from Facebook will introduce their teams’ collaboration with Alluxio on adding a local on-SSD Alluxio cache inside Presto workers at Facebook to improve queries with unsatisfied latency.
This is an open source community conference focused on the key data engineering challenges and solutions around building cloud-native data and AI platforms using latest technologies such as Alluxio, Apache Spark, Apache Airflow, Presto, Tensorflow, and Kubernetes.