Database Paper Browser

Back to papers

Runtime Optimization of Join Location in Parallel Data Management Systems

Summary: Per-key runtime choice between map-side and reduce-side joins in parallel storage, accounting for UDFs and transfer costs. Extends ski-rental with multi-resource load balancing (CPU, network, I/O) and worst-case guarantees; implemented on Hadoop, Spark, and Muppet; yields throughput gains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11434
Venue
VLDB
Year
2017
Pagerank
4.1905499e-05
Overall Rank
11,805 | 17.96%
DOI
-

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
168 Approximate Frequency Counts over Data Streams 2002 VLDB 0.0003915627
287 Storm @Twitter 2014 SIGMOD 0.00028917909
330 An Architecture for Parallel Topic Models 2010 VLDB 0.00027271063
548 Practical Skew Handling in Parallel Joins 1992 VLDB 0.00020369531
831 Finding Frequent Items in Data Streams 2008 VLDB 0.00016094846
2,612 Muppet: MapReduce-Style Processing of Fast Data 2012 VLDB 8.4566845e-05
3,312 Automatic Partitioning of Database Applications 2012 VLDB 7.2356116e-05
4,945 Lifting the Burden of History from Adaptive Query Processing 2004 VLDB 5.8115261e-05
Previous Page 1 / 1 Next

Semantically Similar Papers