ALLUXIO BAY AREA MEETUP
This talk describes a stack to combine Presto, Alluxio, and Cloud object storage systems (e.g.,AWS S3) for high-concurrent and low-latency SQL queries on big data on the cloud. 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. Alluxio is an open-source data orchestration that brings data closer to compute and provides a unified data access layer at in-memory speeds. Presto can use Alluxio as a distributed caching tier on top of S3 for the hot data to query, avoiding reading data repeatedly from the cloud.
This talk covers:
- The architecture of Presto, its separation of compute and storage, cloud-readiness, recent advancements in the project such as Cost-Based Optimizer and Kubernetes Support.
- An overview of Alluxio’s key concepts, architecture and data flow,
- Presto and Alluxio production use cases running hundreds of nodes, including ING Bank, JD.com, and NetEase Games.
Complete the form below to access the full overview:
.png)
Presentations
Use Alluxio to Unify Storage Systems in Suning
Suning is one of the leading commercial enterprises in China with two public companies in China and Japan respectively. It uses Alluxio to unify storage systems and manage multiple HDFS clusters.
STRATA DATA CONFERENCE LONDON 2018
JD.com is China’s largest online retailer and its biggest overall retailer, as well as the country’s biggest internet company by revenue. Currently, JD.com’s BDP platform runs more than 400,000 jobs (15+ PB) daily, on a system with more than 15,000 cluster nodes and a total capacity of 210 PB.
Alluxio, formerly Tachyon, is the world’s first system that unifies disparate storage systems at memory speed. In the big data ecosystem, Alluxio lies between computation frameworks or jobs and various kinds of storage systems. Additionally, Alluxio’s memory-centric architecture enables data access orders of magnitude faster than existing solutions.
Alluxio has run in JD.com’s production environment on 100 nodes for six months. Mao Baolong, Yiran Wu, and Yupeng Fu explain how JD.com uses Alluxio to provide support for ad hoc and real-time stream computing, using Alluxio-compatible HDFSURLs and Alluxio as a pluggable optimization component. To give just one example, one framework, JDPresto, has seen a 10x performance improvement on average. This work has also extended Alluxio and enhanced the syncing between Alluxio and HDFS for consistency.
Alluxio in MOMO: Accelerating Ad Hoc Analysis
From our friends at MOMO
MOMO, a leading pan-entertainment social platform in China, has deployed Alluxio to accelerate ad-hoc query analytics. In the course of evaluating the best fit for Alluxio in their infrastructure they conducted several performance tests to understand how ad-hoc query analytics behaved in several scenarios. These tests give real-world insight to the performance benefits Alluxio provides. The MOMO findings include:
- With Alluxio, performance was improved 3-5x over the current mode
- Even when initially reading ‘cold’ data Alluxio delivered superior performance in most cases
- Alluxio can effectively scale-out to improve performance as requirements grow