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Integrating query processing with parallel languages
2015
2015 31st IEEE International Conference on Data Engineering Workshops
Preserved Fulltext
and
compilation of for-loop
code
• compiler optimization
across operators
• generative
programming
techniques
• domain-specific
processor
• per-query accelerator
• block-oriented
processing ...
compilation
Logical
query plan
Physical
query plan
machine
code
libraries
source or
bytecode
program
SQL
query
parse
lower
generate
code
compile
link or
inline
query
optimization ...
Background: PL+query int[] numbers = { 5, 4, 1, 3, 9, 8, 6, 7 , 2, 0 }; var numberGroups = from n in numbers group n by n % 5 into g select new { Remainder = g.Key, Numbers = g }; foreach (var g in numberGroups ...
doi:10.1109/icdew.2015.7129583
dblp:conf/icde/Myers15
fatcat:nulnfma5ofeula4pm27iy75f7a
Dynamic speculative optimizations for SQL compilation in Apache Spark
2020
Proceedings of the VLDB Endowment
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Our new SQL compiler for Spark produces highly-efficient machine code, leading to speedups of up to 4.4x on the TPC-H benchmark with textual-form data formats such as CSV or JSON. ...
In this paper we present a new approach to query compilation that overcomes these limitations by relying on runtime profiling and dynamic code generation. ...
behavior of the query execution (for example, by re-compiling the machine code responsible for certain SQL predicate evaluations to a more efficient version). ...
doi:10.14778/3377369.3377382
fatcat:5jm4mgvxpjhapi46kjcjjshsfq
Tidy Tuples and Flying Start: fast compilation and fast execution of relational queries in Umbra
2021
The VLDB journal
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AbstractAlthough compiling queries to efficient machine code has become a common approach for query execution, a number of newly created database system projects still refrain from using compilation. ...
It is sometimes claimed that the intricacies of code generation make compilation-based engines too complex. ...
Such a query engine can compile very quickly and produces machine code that makes efficient use of the processors. ...
doi:10.1007/s00778-020-00643-4
fatcat:iuqrjwb5tzcpri7jlxft4rfidm
Just-in-time compilation for SQL query processing
2014
2014 IEEE 30th International Conference on Data Engineering
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Just-in-time compilation of SQL queries into native code has recently emerged as a viable alternative to interpretation-based query processing. ...
Throughout the discussion we draw analogies to the general code generation techniques used in contemporary compiler technology. At the same time we describe the open research problems of the area. ...
Just-in-time native code generation for SQL Just-in-time compilation of SQL has been revived recently. Krikellas et al. ...
doi:10.1109/icde.2014.6816765
dblp:conf/icde/Viglas14
fatcat:riydka5efzesbapeoy6omvrj64
Just-in-time compilation for SQL query processing
2013
Proceedings of the VLDB Endowment
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Just-in-time compilation of SQL queries into native code has recently emerged as a viable alternative to interpretation-based query processing. ...
Throughout the discussion we draw analogies to the general code generation techniques used in contemporary compiler technology. At the same time we describe the open research problems of the area. ...
Just-in-time native code generation for SQL Just-in-time compilation of SQL has been revived recently. Krikellas et al. ...
doi:10.14778/2536222.2536254
fatcat:4xbo5pcwrzgpvhhklphpxg6r4e
AMa χ oS—Abstract Machine for Xcerpt: Architecture and Principles
[chapter]
2006
Lecture Notes in Computer Science
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It strictly separates compilation and execution of queries: Queries are compiled once to abstract machine code that consists in (1) a code segment with instructions for evaluating each rule and (2) a hint ...
AMaχoS is an abstract machine implementation for Xcerpt that aims at efficiency and ease of deployment. ...
Acknowledgments This research has been funded by the European Commission and by the Swiss Federal Office for Education and Science within the 6th Framework Programme project REWERSE number 506779 (cf. ...
doi:10.1007/11853107_8
fatcat:ncci6fg2crdn7k3xwj5uile3zm
Flare: Native Compilation for Heterogeneous Workloads in Apache Spark
[article]
2017
arXiv
pre-print
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Flare achieves these results through (1) compilation to native code, (2) replacing parts of the Spark runtime system, and (3) extending the scope of optimization and code generation to large classes of ...
We demonstrate order of magnitude speedups both for relational workloads such as TPC-H, as well as for a range of machine learning kernels that combine relational and iterative functional processing. ...
[34] generates efficient code for LINQ queries. Weld is similar to DMLL in supporting nested parallel structures. ...
arXiv:1703.08219v1
fatcat:3euaew55sbe5le72a6rxatxt7a
Processing Declarative Queries through Generating Imperative Code in Managed Runtimes
2017
2017 IEEE 33rd International Conference on Data Engineering (ICDE)
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Our proposal is to apply code generation techniques that have recently been developed for general query processing. ...
The idea is that instead of compiling quereies to query plans, which are then interpreted, the system generates customized native code that is then compiled and executed by the query engine. ...
This work was supported by a Microsoft Research PhD Scholarship and the Intel University Research Office through the Software for Persistent Memories program. ...
doi:10.1109/icde.2017.234
dblp:conf/icde/Viglas17
fatcat:nlal5sjbzzc2royk3qxnvlkuka
Flare & lantern
2019
Proceedings of the VLDB Endowment
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In this demo, we will show how bottlenecks between existing systems can be eliminated when their engines are designed around runtime compilation and native code generation, which is the case for many state-of-the-art ...
We demonstrate an integration of Flare (an accelerator for Spark SQL), and Lantern (an accelerator for TensorFlow and PyTorch) that results in a highly optimized end-to-end compiled data path, switching ...
Figure 3 : 3 System overview: (a) architecture of Spark [2] (b)-(c) the integration of Flare (a Spark accelerator and query compiler) with Lantern (a machine learning framework) on the code generation ...
doi:10.14778/3352063.3352097
fatcat:oqx6mho5dbdfhcsu53an64ig6u
Steno
2011
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation - PLDI '11
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To address this problem, we have developed Steno, which uses a combination of novel and well-known techniques to generate code for declarative queries that is almost as efficient as handoptimized code. ...
To address these overheads, we have implemented Steno: an optimizer for LINQ queries that generates the equivalent loopbased imperative code. ...
We would also like to thank Steve Hand and the anonymous reviewers, whose comments on earlier drafts of this paper have been invaluable for improving the presentation of this work. ...
doi:10.1145/1993498.1993513
dblp:conf/pldi/MurrayIY11
fatcat:t4a2zw6j3rfwljjrxmmsp2tkxa
Steno
2012
SIGPLAN notices
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To address this problem, we have developed Steno, which uses a combination of novel and well-known techniques to generate code for declarative queries that is almost as efficient as handoptimized code. ...
To address these overheads, we have implemented Steno: an optimizer for LINQ queries that generates the equivalent loopbased imperative code. ...
We would also like to thank Steve Hand and the anonymous reviewers, whose comments on earlier drafts of this paper have been invaluable for improving the presentation of this work. ...
doi:10.1145/2345156.1993513
fatcat:lzoqp4hlhnbkjkqw4vft7llw2m
Steno
2011
SIGPLAN notices
Preserved Fulltext
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To address this problem, we have developed Steno, which uses a combination of novel and well-known techniques to generate code for declarative queries that is almost as efficient as handoptimized code. ...
To address these overheads, we have implemented Steno: an optimizer for LINQ queries that generates the equivalent loopbased imperative code. ...
We would also like to thank Steve Hand and the anonymous reviewers, whose comments on earlier drafts of this paper have been invaluable for improving the presentation of this work. ...
doi:10.1145/1993316.1993513
fatcat:p6ngyj2lavduhe5gpgm2qv5evi
Efficiently compiling efficient query plans for modern hardware
2011
Proceedings of the VLDB Endowment
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In this work we present a novel compilation strategy that translates a query into compact and efficient machine code using the LLVM compiler framework. ...
As main memory grows, query performance is more and more determined by the raw CPU costs of query processing itself. ...
CODE GENERATION 4.1 Generating Machine Code So far we have only discussed the translation of algebraic expressions into pseudo-code, but in practice we want to compile the query into machine code. ...
doi:10.14778/2002938.2002940
fatcat:e6dysbyztjakped622vnd6prqu
File-based sharing for dynamically compiled code on Dalvik virtual machine
2010
2010 International Computer Symposium (ICS2010)
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To improve the security, we implement a daemon process, named Query Agent, to control all accesses to the native code and maintain all the information of traces, which are the units of the compilation ...
Memory footprint is considered as an important design issue for embedded systems. Sharing dynamically compiled code among virtual machines can reduce memory footprint and recompilation overhead. ...
When a Dalvik VM compiles a piece of code, it asks the Query Agent to allocate a starting address for the generated native code. ...
doi:10.1109/compsym.2010.5685462
fatcat:smg6d4va55epfgtra3k4ggv5l4
Generating Custom Code for Efficient Query Execution on Heterogeneous Processors
[article]
2017
arXiv
pre-print
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Our core idea is to create variants of generated code and to learn a fast variant for each processor. ...
Our experimental results show that the performance of variants may diverge up to two orders of magnitude. Therefore, we need to generate custom code for each processor to achieve peak performance. ...
Acknowledgment We thank Manuel Renz, Tobias Fuchs, Martin Kiefer, and Viktor Rosenfeld from Technische Universität Berlin for helpful feedback and discussions. ...
arXiv:1709.00700v1
fatcat:2wptsn3cmnew3pefun635vc5q4
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