This is a guest blog by Chengzhi Zhao with an original blog source. Traditionally, if you want to run a single Spark job on EMR, you might follow the steps: launching a cluster, running the job which reads data from storage layer like S3, performing transformations within RDD/Dataframe/Dataset, finally, sending the result back to S3. … Continued
As the data ecosystem within enterprises grow larger and larger, not only do we see an increase in total data volumes but also an increase in the disparate storage systems in which they are housed. The challenge then becomes how do different applications and teams have an efficient way of being able to access data … Continued
The latest advances in container orchestration by Kubernetes bring cost savings and flexibility to compute workloads in public or hybrid cloud environments. On the other hand, it introduces new challenges such as how to move data to compute efficiently, how to unify data across multiple or remote clouds, how to co-locate data with compute and many more. Alluxio approaches these problems in a new way. It helps elastic compute workloads realize the true benefits of the cloud, while bringing data locality and data accessibility to workloads orchestrated by Kubernetes
Hear how DBS Bank is taking a new approach to making data-intensive compute independent of the storage. They will share the challenges as well as the new technology stack that includes technologies like Spark, Alluxio and object stores.
Enterprises are increasingly looking towards object stores to power their big data & machine learning workloads in a cost-effective way. The combination of SwiftStack and Alluxio together, enables users to seamlessly move towards a disaggregated architecture. Swiftstack provides a massively parallel cloud object storage and multi-cloud data management system. Alluxio is a data orchestration layer, which sits between compute frameworks and storage systems and enables big data workloads to be deployed directly on SwiftStack. Alluxio provides data locality, accessibility and elasticity via its core innovations. With the Alluxio and Swiftstack solution, Spark, Presto, Tensorflow and Hive and other compute workloads can benefit from 10X performance improvement and dramatically lower costs.
Alluxio can help data scientists and data engineers interact with different storage systems in a hybrid cloud environment. Using Alluxio as a data access layer for Big Data and Machine Learning applications, data processing pipelines can improve efficiency without explicit data ETL steps and the resulting data duplication across storage systems.
This technical salon will focus on big data, storage, database and Alluxio application practice, and invite Tencent technical experts and industry technical experts to share the basic principles of Alluxio system, big data system architecture, database application operation and maintenance, AI computer. Themes such as visual technology and landing practice bring rich practical content and experience exchange.
Open source software always plays critical role in software development. From Linux kernel to TensorFlow, it drives a lot of awesome projects which created trend and led direction of technology.
We are pleased to have several experts, Reynold Xin, Dongxu Huang, Qing Han, Bin Fan, Amelia Wong, etc. who will share the technology and stories on their successful open source project.
Tachyon is a memory-centric fault-tolerant distributed storage system, which enables reliable file sharing at memory-speed. It originated from AMPLab, UC Berkeley in 2012, the same lab produced Apache Mesos and Apache Spark. Soon later, it became an open source project and is deployed at many companies. Since then, Tachyon has attracted more than 200 contributors from over 50 institutions. In 2015, company Tachyon Nexus was founded to further accelerate the development of Tachyon. In this talk, we will review Tachyon’s new features, deployments, and developments in 2015, and look into 2016.