Alluxio meetups, conferences, events and more
The latest Alluxio meetups, webinars, conferences and more

Alluxio Product School | Integrate Alluxio With Your Trino and Spark Workloads, Without Redefining Hive Tables
Past Events:
Ultra Fast Deep Learning in Hybrid Cloud Using Intel Analytics Zoo & Alluxio
Today, many people run deep learning applications with training data from separate storage such as object storage or remote data centers. This presentation will demo the Intel Analytics Zoo + Alluxio stack, an architecture that enables high performance while keeping cost and resource efficiency balanced without network being I/O bottlenecked.
Optimizing Latency-Sensitive Queries for Presto at Facebook: A Collaboration Between Presto & Alluxio
For many latency-sensitive SQL workloads, Presto is often bound by retrieving distant data. In this talk, Rohit Jain, James Sun from Facebook and Bin Fan from Alluxio will introduce their teams’ collaboration on adding a local on-SSD Alluxio cache inside Presto workers at Facebook to improve queries with unsatisfied latency.
Burst Presto & Spark workloads to AWS EMR with no data copies
In this talk, we will show you how to leverage any public cloud (AWS, Google Cloud Platform, or Microsoft Azure) to scale analytics workloads directly on on-prem data without copying and synchronizing the data into the cloud.
Scalable and Highly-available Distributed File System Metadata Service Using gRPC, RocksDB and RAFT
It is critical for Alluxio to be able to store and serve the metadata of all files and directories from all mounted external storage both at scale and at speed. This talk shares our design, implementation, and optimization of Alluxio metadata service (master node) to address the scalability challenges.
Bursting Apache Spark Workloads to the Cloud on Remote Data
Accessing data to run analytic workloads in Spark across data centers and/or clouds can be challenging. Additionally, network I/O can bottleneck Spark jobs that need to read a large amount of data. A common solution is to deploy an HDFS cluster closer to Spark as a caching layer and manually copy the input data to HDFS first, purging it afterward. But this ETL process can be both time-consuming and also error-prone.
Optimizing Query Performance by Decoupling Presto and Hive Data Warehouse
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.
What’s new in Alluxio 2: from seamless operations to structured data management
Alluxio 2.0 expands the system in three major directions including improving the operability of the system, having more advanced data management, as well as re-architecting the system to be able to scale to 1 billion + file. The system is now cloud native on AWS, Google Cloud, and allow users to enable native deployment with K8s. The new advanced data management enables data migration and replication from diff storage systems.
Testing Distributed System at Scale for the Cost of a Large Pizza on AWS
Building distributed systems is no small feat. Software testing is just one of many critical practices that engineers who build these systems need to utilize to ensure the quality and usability of their software. For distributed systems, scaling out testing frameworks to ensure that enterprises who run our in highly distributed environments is a complicated (and expensive task!)
Running Presto with Alluxio on Amazon EMR
Many organizations are leveraging EMR to run big data analytics on public cloud. However, reading and writing data to S3 directly can result in slow and inconsistent performance. Alluxio is a data orchestration layer for the cloud, and in this use case it caches data for S3, ensuring high and predictable performance as well as reduced network traffic.