Hadoop in Action

By Chuck P. Lam. 2010

396 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics (2010, methodology): “Hadoop [6-9] is a software framework that can be installed on a commodity Linux cluster to permit large scale distributed data analysis.”
Assessing the impact of big data on firm innovation performance: Big data is not always better data (2020, background): “For example, Ha-doop, a popular open source framework, enables parallel processing, allowing for rapid access to and analysis of huge volumes of data (Lam, 2010).”
Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph (2015, methodology): “Hadoop can parallel process the data to increase speed, and it has high scalability because it can handle PB level data (Lam, 2010).”
Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce (2018, methodology): “In this section we present and analyze three well-known alternatives for distributed processing belonging to the “Apache Hadoop ecosystem.””