PigOut: Making multiple Hadoop clusters work together

PigOut: Making multiple Hadoop clusters work together

                                  PigOut: Making multiple Hadoop clusters work together.This paper presents PigOut, a system that enables federated data processing over multiple Hadoop clusters. Using PigOut, a user (such as a data analyst) can write a single script in a high-level language to efficiently use multiple Hadoop clusters. There is no need to manually write multiple scripts and coordinate the execution for different clusters. PigOut accomplishes this by automatically partitioning a single, user-supplied script into multiple scripts that run on different clusters. Additionally, PigOut generates workflow descriptions to coordinate execution across clusters.

Hadoop-Projects

Hadoop-Projects

In doing so, PigOut leverages existing tools built around Hadoop, avoiding extra effort required from users or administrators. For example, PigOut uses Pig Latin, a popular query language for Hadoop MapReduce, in a (virtually) unmodified form. Through our evaluation with PigMix, the standard benchmark for Pig, we demonstrate that PigOut’s automatically-generated scripts and workflow definitions have comparable performance to manual, hand-tuned ones. We also report our experience with manually writing multiple scripts for a set of federated clusters, and compare the process with PigOut’s automated approach.

Similar IEEE  Project Titles


Work Progress

PHD - 24

M.TECH - 125

B.TECH -95

BIG DATA -110.

HADOOP -90.

ON-GOING Hadoop Projects

HADOOP MAP -90.

HADOOP YARN -27.

HADOOP HEBROS - 25.

HADOOP ZOOKEEPER -18.

Achievements – Hadoop Solutions

Hadoop-Projects-Achievement-Awards

Twitter Feed

Customer Review

Hadoop Solutions 5 Star Rating: Recommended 4.9 - 5 based on 1000+ ratings. 1000+ user reviews.