Interprocedural query extraction for transparent persistence

Wiedermann, Ben; Ibrahim, Ali; Cook, William R.

doi:10.1145/1449955.1449767

Cited by 14 publications

(17 citation statements)

References 26 publications

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“…The third line of work on query synthesis generates more efficient SQL queries from code written in conventional programming languages [Cheung et al 2013;Wiedermann et al 2008]. For instance, QBS [Cheung et al 2013] transforms parts of the application logic into SQL queries by automatically inferring loop invariants.…”

Section: Evaluation Of Different Confidence Thresholdsmentioning

confidence: 99%

SQLizer: query synthesis from natural language

Yaghmazadeh

Wang

Dillig

et al. 2017

Proc. ACM Program. Lang.

237

163

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This paper presents a new technique for automatically synthesizing SQL queries from natural language (NL). At the core of our technique is a new NL-based program synthesis methodology that combines semantic parsing techniques from the NLP community with type-directed program synthesis and automated program repair. Starting with a program sketch obtained using standard parsing techniques, our approach involves an iterative refinement loop that alternates between quantitative type inhabitation and automated sketch repair. We use the proposed idea to build an end-to-end system called Sqlizer that can synthesize SQL queries from natural language. Our method is fully automated, works for any database without requiring additional customization, and does not require users to know the underlying database schema. We evaluate our approach on over 450 natural language queries concerning three different databases, namely MAS, IMDB, and YELP. Our experiments show that the desired query is ranked within the top 5 candidates in close to 90% of the cases and that Sqlizer outperforms Nalir, a state-of-the-art tool that won a best paper award at VLDB'14. CCS Concepts: • Human-centered computing → Natural language interfaces; • Software and its engineering → Domain specific languages; • Information systems → Relational database query languages; Database utilities and tools; Extraction, transformation and loading;

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Section: Evaluation Of Different Confidence Thresholdsmentioning

confidence: 99%

SQLizer: query synthesis from natural language

Yaghmazadeh

Wang

Dillig

et al. 2017

Proc. ACM Program. Lang.

237

163

View full text Add to dashboard Cite

show abstract

“…In the database research community, there has been work in inferring invariants and postconditions in transforming imperative code into database queries [15,32,60]. We follow QBS [15] in using constraint-based program synthesis to come up with invariants and postconditions.…”

Section: Related Workmentioning

confidence: 99%

Verified lifting of stencil computations

et al. 2016

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This paper demonstrates a novel combination of program synthesis and verification to lift stencil computations from low-level Fortran code to a high-level summary expressed using a predicate language. The technique is sound and mostly automated, and leverages counterexample guided inductive synthesis (CEGIS) to find provably correct translations. Lifting existing code to a high-performance description language has a number of benefits, including maintainability and performance portability. Our experiments show that the lifted summaries allow domain specific compilers to do a better job of parallelization as compared to an off-the-shelf compiler working on the original code, and can even support fully automatic migration to hardware accelerators such as GPUs. We have implemented verified lifting in a system called STNG and have evaluated it using microbenchmarks, mini-apps, and real-world applications. We demonstrate the benefits of verified lifting by first automatically summarizing Fortran source code into a high-level predicate language, and subsequently translating the lifted summaries into Halide, with the translated code achieving median performance speedups of 4.1× and up to 24× as compared to the original implementation.

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“…Data persistence languages. Several projects explore integrated query languages [32,11,21,10,19] that improve expressiveness and performance of database applications. Pyxis partitions database applications that use the standard JDBC API.…”

Section: Related Workmentioning

confidence: 99%

Automatic partitioning of database applications

Cheung¹,

Madden²,

Arden

et al. 2012

Proc. VLDB Endow.

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Database-backed applications are nearly ubiquitous in our daily lives. Applications that make many small accesses to the database create two challenges for developers: increased latency and wasted resources from numerous network round trips. A well-known technique to improve transactional database application performance is to convert part of the application into stored procedures that are executed on the database server. Unfortunately, this conversion is often difficult. In this paper we describe Pyxis, a system that takes database-backed applications and automatically partitions their code into two pieces, one of which is executed on the application server and the other on the database server. Pyxis profiles the application and server loads, statically analyzes the code's dependencies, and produces a partitioning that minimizes the number of control transfers as well as the amount of data sent during each transfer. Our experiments using TPC-C and TPC-W show that Pyxis is able to generate partitions with up to 3× reduction in latency and 1.7× improvement in throughput when compared to a traditional non-partitioned implementation and has comparable performance to that of a custom stored procedure implementation.

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Interprocedural query extraction for transparent persistence

Cited by 14 publications

References 26 publications

SQLizer: query synthesis from natural language

SQLizer: query synthesis from natural language

Verified lifting of stencil computations

Automatic partitioning of database applications

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