In the previous tutorial ”Getting Started with Spark Caching using Alluxio in 5 Minutes”, we demonstrated how to get started with Spark and Alluxio. To share more thoughts and experiments on how Alluxio enhances Spark workloads, this article focuses on how Alluxio helps to optimize the memory utilization of Spark applications. For users who are … Continued
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 tutorial describes steps to set up an EMR cluster with Alluxio as a distributed caching layer for Hive, and run sample queries to access data in S3 through 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.
This article aims to provide a different approach to help connect and make distributed files systems like HDFS or cloud storage systems look like a local file system to data processing frameworks: the Alluxio POSIX API. To explain the approach better, we used the TensorFlow + Alluxio + AWS S3 stack as an example.
Over the years of working in the big data and machine learning space, we frequently hear from data engineers that the biggest obstacle to extracting value from data is being able to access the data efficiently. Data silos, isolated islands of data, are often viewed by data engineers as the key culprit or public enemy №1. There have been many attempts to do away with data silos, but those attempts themselves have resulted in yet another data silo, with data lakes being one such example. Rather than attempting to eliminate data silos, we believe the right approach is to embrace them.
Notice anything new about our websites? That’s right – we are super excited to launch our new website – Alluxio.io!
As we continue our focus on our open source community, one important item on our mind was to rebuild our website to provide better user experience for our community. To that end, you’ll see lots of changes in the Alluxio web experience.
The Apache Spark + Alluxio stack is getting quite popular particularly for the unification of data access across S3 and HDFS. In addition, compute and storage are increasingly being separated causing larger latencies for queries. Alluxio is leveraged as compute-side virtual storage to improve performance. But to get the best performance, like any technology stack, you need to follow the best practices. This article provides the top 10 tips for performance tuning for real-world workloads when running Spark on Alluxio with data locality giving the most bang for the buck.
As the amount of data being collected and analyzed by Enterprises continues to grow unabated, more attention is being placed on managing the cost of storing the data relative to performance. Hadoop provides a scalable and fast way of storing and analyzing data, however, the cost of storing data in Hadoop is typically higher compared to alternative technologies like Object Stores.