At Aspect Analytics we intend to use Dask, a distributed computation library for Python, to deal with MSI data stored as large tensors. In this talk we explore using Alluxio and Alluxio FUSE as a data consolidation and caching layer for some of our bioinformatics workflows.
Many Spark users may not be aware of the differences in memory utilization between caching data directly in-memory into the Spark JVM versus storing data off-heap via an in-memory storage service like Alluxio. In this office hour, I will highlight the two approaches with a demo and open up for discussions
This talk describes a stack of open-source projects to serve high-concurrent and low-latency SQL queries using Presto with Alluxio on big data in the cloud. Deploying Alluxio as a data orchestration layer to access cloud storage object storage (e.g., AWS S3), this architecture greatly enhances the data locality of Presto with distributed and cross-query caching, thus avoids reading same data repeatedly from the cloud storage.
Presto is widely used for data science, business analytics, and operations. Presto’s SQL is a main driver for this, as it is ANSI-compliant, easy to ramp-up, and has rich functionality. Given the versatility and flexibility of this software, there is also a huge demand to develop interfaces for other critical data domains like real-time dashboards, stream processing, and large-scale batch computations. We will explore some interesting systems and prototypes to bring Presto to these new domains.
This tutorial guides users to set up a stack of Presto, Alluxio and Hive Metastore on your local server, and it demonstrates how to use Alluxio as the caching layer for Presto queries.
This article describes how JD built this interactive OLAP platform combining two open-source technologies: Presto and Alluxio.
Alluxio is an open-source data orchestration system widely used to speed up data-intensive workloads in the cloud. Alluxio v2.0 introduced Replicated Async Write to allow users to complete writes to Alluxio file system and return quickly with high application performance, while still providing users with peace of mind that data will be persisted to the chosen under storage like S3 in the background.
Joint meetup in Hangzhou discusses: An introduction to new features of big data storage system Alluxio and optimization of cache performance, Practice & exploration of Spark & Alluxio, and the Interactive query system Impala.
Welcome to the first event of the Cloud, Data, & Orchestration Austin Meetup! This meetup will feature two talks and an opportunity to engage with other data engineers, developers, and Alluxio users. Thanks to Bazaarvoice for hosting!