Today when we create a Hive table, it is a common technique to partition the table across different values and ranges to improve query performance and reduce maintenance cost. However, Hive can not access a single table directly using a single query with the data of this Hive table across different mediums of storage and … Continued
Tags: alluxio engineering, apache hive, hdfs, performance, sql
Problem Sometimes big data analytics need process input data from two different storage systems at the same time. For instance, a data scientists may need to join two tables one from a HDFS cluster and one from S3. Existing Solutions Certain computation frameworks may be able to connect to storage systems including HDFS and popular cloud … Continued
Tags: aws s3, cloud object storage, compute storage separation, hdfs, unified namespace
Alluxio provides a distributed data access layer for applications like Spark or Presto to access different underlying file system (or UFS) through a single API in a unified file system namespace. If users only interact with the files in the UFS through Alluxio, since Alluxio has knowledge of any changes the client makes to the … Continued
Author: Shuang Li (Shuang is a big data engineer at Netease Games, developing and maintaining OLAP related solutions in the data warehouse. He works closely on Apache Kylin and Presto as well as HBase. Shuang graduated from South China University of Technology.) Background As one of the world’s leading online game company, Netease Games is … Continued
Introduction 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 … Continued
JD.com is China’s largest online retailer and its biggest overall retailer, as well as the country’s biggest internet company by revenue. Currently, JD.com’s BDP platform runs more than 400,000 jobs (15+ PB) daily, on a system with more than 15,000 cluster nodes and a total capacity of 210 PB.
Alluxio has run in JD.com’s production environment on 100 nodes for six months. See how JD.com uses Alluxio to provide support for ad hoc and real-time stream computing, using Alluxio-compatible HDFS URLs and Alluxio as a pluggable optimization component.
Tags: apache hadoop, benchmark, case study, compute storage separation, hdfs, presto
This post is guest authored from our friends at Tencent: Can He Download or print the case study here 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 … Continued
Introduction Alluxio is the world’s first memory-speed virtual distributed storage system that bridges applications and underlying storage systems, providing unified data access orders of magnitudes faster than existing solutions. The Hadoop Distributed File System (HDFS) is a distributed file system for storing large volumes of data. HDFS popularized the paradigm of bringing computation to data … Continued