Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
Deferred Lightweight Indexing for Log-Structured Key-Value Stores
Proceedings of the 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid’15), May 2015, Shenzhen, Guangdong, China. Best paper award.
Yuzhe Tang†, Arun Iyengar‡, Wei Tan‡, Liana Fong‡, Balaji Palanisamy*, Ling Liu§
§Georgia Institutue of Technology
‡IBM T.J.Watson Research Center
*University of Pittsburgh
The recent shift towards write-intensive workload on big data (e.g., financial trading, social user-generated data streams) has pushed the proliferation of log-structured key-value stores, represented by Google’s BigTable , Apache HBase  and Cassandra . While providing key-based data access with a Put/Get interface, these key-value stores do not support value-based access methods, which significantly limits their applicability in modern web and database applications. In this paper, we present DELI, a DEferred Lightweight Indexing scheme on the log-structured key-value stores. To index intensively updated big data in real time, DELI aims at making the index maintenance as lightweight as possible. The key idea is to apply an append-only design for online index maintenance and to collect index garbage at carefully chosen time. DELI optimizes the performance of index garbage collection through tightly coupling its execution with a native routine process called compaction. The DELI’s system design is fault-tolerant and generic (to most key-value stores); we implemented a prototype of DELI based on HBase without internal code modification. Our experiments show that the DELI offers significant performance advantage for the write-intensive index maintenance.
FULL PAPER: pdf