Abstract In recent years, many approaches to indexing XML data have appeared. These approaches attempt to process XML queries efficiently and sufficient query plans are built for t...
As access times to main memory and disks continue to diverge, faster non-volatile storage technologies become more attractive for speeding up data analysis applications. NAND flas...
Mehul A. Shah, Stavros Harizopoulos, Janet L. Wien...
Many parallel join algorithms have been proposed so far but most of which are developed focused on minimizing the disk It0 and CPU costs. The communication cost, however, is also ...
Hwan-Ik Choi, Byoung Mo Im, Myoung-Ho Kim, Yoon-Jo...
The most costly spatial operation in spatial databases is a spatial join with combines objects from two data sets based on spatial predicates. Even if the execution time of sequen...
Three join algorithms are evaluated in an environment with distributed main-memory based mediators and data sources. A streamed ship-out join ships bulks of tuples to a mediator ne...
The MapReduce framework is increasingly being used to analyze large volumes of data. One important type of data analysis done with MapReduce is log processing, in which a click-st...
Spyros Blanas, Jignesh M. Patel, Vuk Ercegovac, Ju...
This demonstration presents a recently proposed join algorithm called DigestJoin. Optimized for solid-state drives (SSDs), DigestJoin aims at reducing intermediate join results and...
When integrating geo-spatial datasets, a join algorithm is used for finding sets of corresponding objects (i.e., objects that represent the same real-world entity). Algorithms for...