Open source data orchestration for a disaggregated analytics stack

Bangalore Presto Meetup *

The rise of compute intensive workloads and the adoption of the cloud has driven organizations to adopt a decoupled architecture for modern workloads – one in which compute scales independently from storage. While this enables scaling elasticity, it introduces new problems – how do you co-locate data with compute, how do you unify data across multiple remote clouds, how do you keep storage and I/O service costs down and many more.

Ultra-fast SQL Analytics using PAS (Presto on Alluxio Stack)

Presto Meetup *

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.

Simplified Data Preparation for Machine Learning in Hybrid and Multi Clouds

ODSC WEST 2019 Cloud storage brings great flexibility in management and cost-efficiency to data scientists, but also introduces new challenges related to data accessibility and data locality for machine learning applications. For instance, when the input data is stored in a remote cloud storage like AWS S3 or Azure blob storage, direct data access is … Continued

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What can I do to speed up analytics performance on remote data?

Background Today’s advanced analytics applications run on more datasets that ever before. The locations of where data “lands” is becoming more dispersed. And the separation of compute and storage in modern environments lends well to running on these distributed datasets. Data can be stored in a remote location from the compute, such as in a … Continued

Tech Talk: Accelerating Spark with Kubernetes

Kubernetes is widely used across enterprises to orchestrate computation. And while Kubernetes helps improve flexibility and portability for computation in public/hybrid cloud environments across infrastructure providers, running data-intensive workloads can be challenging.

When it comes to efficiently moving data closer to Spark or Presto frameworks, co-locating data with these frameworks and accessing data from multiple or remote clouds is hard to do. That’s where Alluxio, an open source data orchestration platform, can help.

Alluxio enables data locality with your Spark and Presto workloads for faster performance and better data accessibility in Kubernetes. It also provides portability across storage providers.

In this on demand tech talk we’ll give a quick overview of Alluxio and the use cases it powers for Spark/Presto in Kubernetes. We’ll show you how to set up Alluxio and Spark/Presto to run in Kubernetes as well.

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