Problem If you have hundreds of external tables defined in Hive, what is the easist way to change those references to point to new locations? That is a fairly normal challenge for those that want to integrate Alluxio into their stack. A typical setup that we will see is that users will have Spark-SQL or … Continued
How do we access AWS S3 data when running Presto in an on-premise environment, how can we do it efficiently to reduce both egress cost and performance runtimes? Alluxio as a local cache for Presto queries against remote AWS S3 data sources As we move toward more and more decoupled environments one of the things … Continued
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.
In this talk, we will focus on Alluxio design, its architecture, data flow and metadata flow. We will dive into the choices in its design space and share the experiences when implementing features like data tiering, storage options and cache eviction policies. We will also share our lessons in design, implementation and operation when working to build an open source distributed storage systems with 900 contributors for 5+ years.
Wenbo Zhao (Two Sigma) and Bin Fan (Alluxio) will be presenting on how Two Sigma uses Alluxio to make data-intensive compute independent of the storage beneath.
This presentation focuses on how Alluxio helps the big data analytics stack to be cloud-native. The trending Cloud object storage systems provide more cost-effective and scalable storage solutions but also different semantics and performance implications compared to HDFS. Applications like Spark or Presto will not benefit from the node-level locality or cross-job caching when retrieving data from the cloud object storage. Deploying Alluxio to access cloud solves these problems because data will be retrieved and cached in Alluxio instead of the underlying cloud or object storage repeatedly.
Cloud object storage systems provide different semantics and performance implications compared to HDFS. Applications like Presto cannot benefit from the node-level locality or cross-job caching when reading from the cloud. Deploying Alluxio with Presto to access cloud solves these problems because data will be retrieved and cached in Alluxio instead of the underlying cloud or object storage repeatedly. Bin will present the architecture to combine Presto with Alluxio with use cases from major internet companies like JD.com and NetEase.com, and their lessons learned to operate this architecture at scale.
This webinar reviews: The observation and analysis of trends of separation of Storage and Compute in Big Data ecosystem; Why and how to build a new data access layer between compute and storage in this data stack; Alluxio open source: history, overview, design, and architecture; Production Use case with Spark, Presto, Tensorflow and etc; A demo of running Presto on Alluxio on S3
Over the past two decades, the Big Data stack has reshaped and evolved quickly with numerous innovations driven by the rise of many different open source projects and communities. In this meetup, speakers from Uber, Alibaba, and Alluxio will share best practices for addressing the challenges and opportunities in the developing data architectures using new and emerging open source building blocks. Topics include data format (ORC) optimization, storage security (HDFS), data format (Parquet) layers, and unified data access (Alluxio) layers.