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 to improve unsatisfied Presto latency.
Tags: local cache, meetup, performance, presto, sql workloads
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.
Tags: analytic workloads, cloud, hdfs, hybrid cloud, office hour, presto, public cloud, spark
This whitepaper details how to leverage a public cloud, such as Amazon AWS, Google GCP, or Microsoft Azure to scale analytic workloads directly on data on-premises without copying and synchronizing the data into the cloud. We will show an example of what it might look like to run on-demand Presto and Hive with Alluxio in the public cloud using on-prem HDFS. We will also show how to set up and execute performance benchmarks in two geographically dispersed Amazon EMR clusters along with a summary of our findings.
Tags: aws, azure, data analytics, emr, gcp, hdfs, hive, hybrid cloud, presto, public cloud, zero copy
This is a casual online video chat where all attendees are welcome to bring your own questions. Our host Bin will have suggested topics, such as the top challenges around leveraging popular compute frameworks including Presto and Spark to access remote data, and the latest developments in Alluxio open source such as Alluxio Catalog Services.
Are you using SQL engines, such as Presto, to query existing Hive data warehouse and experiencing challenges including overloaded Hive Metastore with slow and unpredictable access, unoptimized data formats and layouts such as too many small files, or lack of influence over the existing Hive system and other Hive applications?
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.
Ideally, Presto would access data independently from how the data was originally stored or managed. 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.
Tags: alluxio engineering, catalog service, data orchestration, hive, office hour, performance, presto, structured data services
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.
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.
Tags: aws s3, big data, cloud, compute storage separation, emr, office hour, presto, storage