FPGA '99 Proceedings of the 1999 ACM/SIGDA seventh international symposium on Field programmable gate arrays
An adaptive query execution system for data integration
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Dataflow query execution in a parallel main-memory environment
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Systolic (VLSI) arrays for relational database operations
SIGMOD '80 Proceedings of the 1980 ACM SIGMOD international conference on Management of data
Control Versus Data Flow in Parallel Database Machines
IEEE Transactions on Parallel and Distributed Systems
Diag-Join: An Opportunistic Join Algorithm for 1:N Relationships
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Selection conditions in main memory
ACM Transactions on Database Systems (TODS)
Semantics and evaluation techniques for window aggregates in data streams
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Measuring the gap between FPGAs and ASICs
Proceedings of the 2006 ACM/SIGDA 14th international symposium on Field programmable gate arrays
Incremental Evaluation of Sliding-Window Queries over Data Streams
IEEE Transactions on Knowledge and Data Engineering
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Towards a streaming SQL standard
Proceedings of the VLDB Endowment
CellJoin: a parallel stream join operator for the cell processor
The VLDB Journal — The International Journal on Very Large Data Bases
The multikernel: a new OS architecture for scalable multicore systems
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Continuous analytics over discontinuous streams
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
A Spinning Join That Does Not Get Dizzy
ICDCS '10 Proceedings of the 2010 IEEE 30th International Conference on Distributed Computing Systems
SECRET: a model for analysis of the execution semantics of stream processing systems
Proceedings of the VLDB Endowment
Querying sliding windows over online data streams
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Efficiently correlating complex events over live and archived data streams
Proceedings of the 5th ACM international conference on Distributed event-based system
Massively parallel sort-merge joins in main memory multi-core database systems
Proceedings of the VLDB Endowment
Efficient frequent item counting in multi-core hardware
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
An embedded co-processor for accelerating window joins over uncertain data streams
Microprocessors & Microsystems
Photon: fault-tolerant and scalable joining of continuous data streams
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
A fast handshake join implementation on FPGA with adaptive merging network
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
The HELLS-join: a heterogeneous stream join for extremely large windows
Proceedings of the Ninth International Workshop on Data Management on New Hardware
Efficient co-processor utilization in database query processing
Information Systems
Revisiting co-processing for hash joins on the coupled CPU-GPU architecture
Proceedings of the VLDB Endowment
Flexible query processor on FPGAs
Proceedings of the VLDB Endowment
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In spite of the omnipresence of parallel (multi-core) systems, the predominant strategy to evaluate window-based stream joins is still strictly sequential, mostly just straightforward along the definition of the operation semantics. In this work we present handshake join, a way of describing and executing window-based stream joins that is highly amenable to parallelized execution. Handshake join naturally leverages available hardware parallelism, which we demonstrate with an implementation on a modern multi-core system and on top of field-programmable gate arrays (FPGAs), an emerging technology that has shown distinctive advantages for high-throughput data processing. On the practical side, we provide a join implementation that substantially outperforms CellJoin (the fastest published result) and that will directly turn any degree of parallelism into higher throughput or larger supported window sizes. On the semantic side, our work gives a new intuition of window semantics, which we believe could inspire other stream processing algorithms or ongoing standardization efforts for stream query languages.