See results of 10x performance in Spark and Hive jobs that are running on AWS S3. Plus, learn how real world user Bazaarvoice implemented a tiered storage architecture for a boost in performance.
Tags: apache spark, aws s3, case study, meetup, tiered storage
Recently, Qunar deployed Alluxio with Spark in production and found that Alluxio enables Spark streaming jobs to run 15x to 300x faster. In their case study, they described how Alluxio improved their system architecture, and mentioned that some existing Spark jobs would slow down or would never finish because they would run out of memory. After using Alluxio, those jobs were able to finish, because the data could be stored in Alluxio, instead of within Spark.
In this blog, we show by saving RDDs in Alluxio, Alluxio can keep larger data sets in-memory for faster Spark applications, as well as enable sharing of RDDs across separate Spark applications.
TalkingData leverages Alluxio as a single platform to manage all the data across disparate data sources on-premise and in the cloud. Alluxio removes the complexity of our environment by abstracting the different data sources and providing a unified interface. Applications simply interact with Alluxio, and Alluxio manages data access to different storage systems on behalf of the applications. Alluxio effectively democratizes data access, allowing data scientists and analysts in various business units to accomplish their goals without needing to consider where the data is located or having to go to central IT or the engineering team to transfer or prepare the data.
While looking for ways to streamline our data pipeline, we learned about Alluxio, an open source, memory speed, virtual distributed file system. We deployed Alluxio as the shared data layer for all of the intermediate stages in the data pipeline. By reading and writing data in Alluxio, the data can be read concurrently and stay in memory for the next stage of the pipeline. This increased the performance by speeding up the entire pipeline, and increased overall throughput of the pipeline allowing us to provide interactive response to our app users.
Tencent is one of the largest technology companies in the world and a leader in multiple sectors such as social networking, gaming, e-commerce, mobile and web portal. Tencent News, one of Tencent’s many offerings, strives to create a rich, timely news application to provide users with an efficient, high-quality reading experience. To provide the best experience to more than 100 million monthly active users of Tencent News, we leverage Alluxio with Apache Spark to create a scalable, robust, and performant architecture.
Alluxio clusters act as a data access accelerator for remote data in connected storage systems. Temporarily storing data in memory, or other media near compute, accelerates access and provides local performance from remote storage. This capability is even more critical with the movement of compute applications to the cloud and data being located in object stores separate from compute. Caching is transparent to users, using read/write buffering to maintain continuity with persistent storage. Intelligent cache management utilizes configurable policies for efficient data placement and supports tiered storage for both memory and disk (SSD/HDD).
From our friends at MOMO The hadoop ecosystem makes many distributed system/algorithms easier to use and generally lowers the cost of operations. However, enterprises and vendors are never satisfied with that, so higher performance becomes the next issue. We considered several options to address our performance needs and focused our efforts on Alluxio, which improves performance … Continued
Tags: analytics, apache hadoop, apache spark, caching, case study, sql
The primary appeal of a coupled compute-storage architecture, an architecture where the computation is happening on the machines where the data resides, is the performance possible by bringing the compute engine to the data it requires; however, the costs of maintaining such tight-knit architectures are gradually overtaking the performance benefits. Especially with the popularity of cloud resources, being able to independently scale compute and storage results in large cost savings and cheaper maintenance. In addition, data has become the new oil, and all modern organizations are looking to capture as much data as possible.
OLAP (on-line analytical processing) technology has been widely adopted by enterprises since last century; Enterprises rely on OLAP to analyze their huge amount of data, generate reporting and so to help business people making decisions. Today in the era of big data, OLAP becomes more important and challenging than ever before; and cloud computing makes this further true. This article introduces how Kyligence, a cutting-edge big data intelligence company, leverages Alluxio to boost their performance in the cloud.