Abstract
Soon after Google published MapReduce, their paradigm for processing large amounts of data, the open-source world followed with the Hadoop ecosystem. Later on, Lexis Nexis, the company behind the world's largest database of legal documents, open-sourced its Big Data processing platform, called the High-Performance Computing Cluster (HPCC). This paper makes three contributions. First, we describe our additions and improvements to the Pig Mix benchmark, the set of queries originally written for Apache Pig, and the porting of Pig Mix to HPCC. Second, we compare the performance of queries written in Pig, Java MapReduce, and ECL. Last, we draw conclusions and issue recommendations for future system benchmarks and large-scale data-processing platforms.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015 |
| Editors | Carminati Barbara, Latifur Khan |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 643-648 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781467372787 |
| DOIs | |
| State | Published - 17 Aug 2015 |
| Event | 4th IEEE International Congress on Big Data, BigData Congress 2015 - New York City, United States Duration: 27 Jun 2015 → 2 Jul 2015 |
Publication series
| Name | Proceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015 |
|---|
Conference
| Conference | 4th IEEE International Congress on Big Data, BigData Congress 2015 |
|---|---|
| Country/Territory | United States |
| City | New York City |
| Period | 27/06/15 → 2/07/15 |
Bibliographical note
Publisher Copyright:© 2015 IEEE.
Keywords
- Benchmark
- Big Data
- HPCC Systems
- MapReduce
- Performance
- PigMix
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