可扩展的低延迟分析

Mass Scalla Project Mass Scalla (SCAlable Low-Latency Analytics at Massachusetts) is an ongoing research project by the University of Massachusetts Amherst database group. We design, develop, and evaluate a scalable, low-latency analytics platform that fundamentally transforms the existing cluster computing paradigm into an incremental parallel processing paradigm, and further extends to near real-time analytics. For more information, please visit http://scalla.cs.umass.edu/. Code Release SCALLA 0.1 is integrated with Hadoop 0.20.1. SCALLA 0.1 can work in three modes. In Hadoop mode, it works as stock Hadoop without the need of any change. In Turn Off Sort-Merge mode, you can run your Hadoop job with a purely hash-based approach without the need to change the code of your Hadoop job. In Incremental Processing mode, you need to modify your Hadoop reducer with our simple incremental API

scalla-0.1
ivy.xml
.classpath
.project
conf
hadoop-0.20.2-dev-core.jar
scalla-docs
NOTICE.txt
hadoop-0.20.1+169.56-test.jar
scalla-examples
src
build.xml
hadoop-0.20.1+169.56-tools.jar
c++
contrib
ivy
hadoop-0.20.1+169.56-ant.jar
lib
bin
hadoop-0.20.1+169.56-examples.jar
example-confs
LICENSE.txt
cloudera
docs
webapps
README.txt