Conjunctive selection conditions in main memory
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Block Oriented Processing of Relational Database Operations in Modern Computer Architectures
Proceedings of the 17th International Conference on Data Engineering
Managing Intra-operator Parallelism in Parallel Database Systems
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
The Volcano Optimizer Generator: Extensibility and Efficient Search
Proceedings of the Ninth International Conference on Data Engineering
Optimizing database architecture for the new bottleneck: memory access
The VLDB Journal — The International Journal on Very Large Data Bases
LLVM: A Compilation Framework for Lifelong Program Analysis & Transformation
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
Compiled Query Execution Engine using JVM
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Adaptive aggregation on chip multiprocessors
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Constant-Time Query Processing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Database architecture evolution: mammals flourished long before dinosaurs became extinct
Proceedings of the VLDB Endowment
SIMD-scan: ultra fast in-memory table scan using on-chip vector processing units
Proceedings of the VLDB Endowment
HyPer: A hybrid OLTP&OLAP main memory database system based on virtual memory snapshots
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
How to efficiently snapshot transactional data: hardware or software controlled?
Proceedings of the Seventh International Workshop on Data Management on New Hardware
Proceedings of the 15th International Conference on Extending Database Technology
Micro-specialization: dynamic code specialization of database management systems
Proceedings of the Tenth International Symposium on Code Generation and Optimization
Massively parallel sort-merge joins in main memory multi-core database systems
Proceedings of the VLDB Endowment
Compacting transactional data in hybrid OLTP&OLAP databases
Proceedings of the VLDB Endowment
Query processing on prefix trees live
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Hekaton: SQL server's memory-optimized OLTP engine
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Simulation of database-valued markov chains using SimSQL
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Optimizing select conditions on GPUs
Proceedings of the Ninth International Workshop on Data Management on New Hardware
High throughput heavy hitter aggregation for modern SIMD processors
Proceedings of the Ninth International Workshop on Data Management on New Hardware
Energy-efficient in-memory database computing
Proceedings of the Conference on Design, Automation and Test in Europe
Memory footprint matters: efficient equi-join algorithms for main memory data processing
Proceedings of the 4th annual Symposium on Cloud Computing
Just-in-time compilation for SQL query processing
Proceedings of the VLDB Endowment
Instant loading for main memory databases
Proceedings of the VLDB Endowment
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As main memory grows, query performance is more and more determined by the raw CPU costs of query processing itself. The classical iterator style query processing technique is very simple and exible, but shows poor performance on modern CPUs due to lack of locality and frequent instruction mispredictions. Several techniques like batch oriented processing or vectorized tuple processing have been proposed in the past to improve this situation, but even these techniques are frequently out-performed by hand-written execution plans. In this work we present a novel compilation strategy that translates a query into compact and efficient machine code using the LLVM compiler framework. By aiming at good code and data locality and predictable branch layout the resulting code frequently rivals the performance of hand-written C++ code. We integrated these techniques into the HyPer main memory database system and show that this results in excellent query performance while requiring only modest compilation time.