China Unicom Uses Alluxio and Spark to Build New Computing Platform to Serve Mobile Users

China Unicom is one of the five largest telecom operators in the world. China Unicom’s booming business in 4G and 5G networks has to serve an exploding base of hundreds of millions of smartphone users. This unprecedented growth brought enormous challenges and new requirements to the data processing infrastructure. The previous generation of its data processing system was based on IBM midrange computers, Oracle databases, and EMC storage devices. This architecture could not scale to process the amounts of data generated by the rapidly expanding number of mobile users. Even after deploying Hadoop and Greenplum database, it was still difficult to cover critical business scenarios with their varying massive data processing requirements.

Presto on Alluxio: How Netease Games leveraged Alluxio to boost ad hoc SQL on HDFS

Netease Games is the operator for many popular online games in China like “World of Warcraft” and “Hearthstone”. Netease Games also has developed quite a few popular games on its own such as “Fantasy Westward Journey 2”, “Westward Journey 2”, “World 3”, “League of Immortals”. The strong growth of the business drives the demand to build and maintain a data platform handling a massive amount of data and delivering insights promptly from the data. Given our data scale, it is very challenging to support high-performance ad-hoc queries to the data with results generated in a timely manner.

TalkingData: Leading Data Broker in China Leverages Alluxio to Unify Terabytes of Data Across Disparate Data Sources

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.

Myntra Case Study: Accelerating Analytics in the Cloud for Customized Mobile E-Commerce

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 Case Study: Delivering Customized News to Over 100 Million Users per Month with Alluxio

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.

MOMO: Accelerating Ad Hoc Analysis with Spark SQL and Alluxio

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).

Lenovo Case Study: Analytics on Data from Multiple Locations and Eliminating ETL

Lenovo is an Alluxio customer with a common problem and use case in the world of data analytics. They have petabytes of data in multiple data centers in different geographic locations. Analyzing it requires an ETL process to get all of the data in the right place. This is both slow, because data has to be transferred across the network, and costly because multiple copies of the data need to be stored. Freshness and quality of the data can also suffer as the data is also potentially out of date and incomplete because regulatory issues prevent certain data from being transferred.

Kyligence leverages Alluxio to accelerate OLAP in the cloud

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.