An Exploratory Case Study of Query Plan Representations

• URL: http://arxiv.org/abs/2408.07857v2
• Date: Fri, 16 Aug 2024 01:10:26 GMT
• Title: An Exploratory Case Study of Query Plan Representations
• Authors: Jinsheng Ba, Manuel Rigger,
• Abstract summary: In database systems, a query plan is a series of concrete internal steps to execute a query. Multiple testing approaches utilize query plans for finding bugs. We envision that a unified query plan representation can facilitate the implementation of these approaches.
• Score: 5.747331236875253
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In database systems, a query plan is a series of concrete internal steps to execute a query. Multiple testing approaches utilize query plans for finding bugs. However, query plans are represented in a database-specific manner, so implementing these testing approaches requires a non-trivial effort, hindering their adoption. We envision that a unified query plan representation can facilitate the implementation of these approaches. In this paper, we present an exploratory case study to investigate query plan representations in nine widely-used database systems. Our study shows that query plan representations consist of three conceptual components: operations, properties, and formats, which enable us to design a unified query plan representation. Based on it, existing testing methods can be efficiently adopted, finding 17 previously unknown and unique bugs. Additionally, the unified query plan representation can facilitate other applications. Existing visualization tools can support multiple database systems based on the unified query plan representation with moderate implementation effort, and comparing unified query plans across database systems provides actionable insights to improve their performance. We expect that the unified query plan representation will enable the exploration of additional application scenarios.

Related papers

• Improving Retrieval-augmented Text-to-SQL with AST-based Ranking and Schema Pruning [10.731045939849125]
  We focus on Text-to- semantic parsing from the perspective of retrieval-augmented generation. Motivated by challenges related to the size of commercial database schemata and the deployability of business intelligence solutions, we propose $textASTReS$ that dynamically retrieves input database information.
  arXiv  Detail & Related papers  (2024-07-03T15:55:14Z)
• Database-Augmented Query Representation for Information Retrieval [59.57065228857247]
  We present a novel retrieval framework called Database-Augmented Query representation (DAQu) DAQu augments the original query with various (query-related) metadata across multiple tables. We validate DAQu in diverse retrieval scenarios that can incorporate metadata from the relational database.
  arXiv  Detail & Related papers  (2024-06-23T05:02:21Z)
• Ask-before-Plan: Proactive Language Agents for Real-World Planning [68.08024918064503]
  Proactive Agent Planning requires language agents to predict clarification needs based on user-agent conversation and agent-environment interaction. We propose a novel multi-agent framework, Clarification-Execution-Planning (textttCEP), which consists of three agents specialized in clarification, execution, and planning.
  arXiv  Detail & Related papers  (2024-06-18T14:07:28Z)
• Testing Database Engines via Query Plan Guidance [6.789710498230718]
  We propose the concept of Query Plan Guidance (QPG) for guiding automated testing towards "interesting" test cases. We apply our method to three mature, widely-used, and diverse database systems-DBite, TiDB, and Cockroach-and found 53 unique, previously unknown bugs.
  arXiv  Detail & Related papers  (2023-12-29T08:09:47Z)
• Conjunctive Query Based Constraint Solving For Feature Model Configuration [79.14348940034351]
  We show how to apply conjunctive queries to solve constraint satisfaction problems. This approach allows the application of a wide-spread database technology to solve configuration tasks.
  arXiv  Detail & Related papers  (2023-04-26T10:08:07Z)
• Searching for Better Database Queries in the Outputs of Semantic Parsers [16.221439565760058]
  In this paper, we consider the case when, at the test time, the system has access to an external criterion that evaluates the generated queries. The criterion can vary from checking that a query executes without errors to verifying the query on a set of tests. We apply our approach to the state-of-the-art semantics and report that it allows us to find many queries passing all the tests on different datasets.
  arXiv  Detail & Related papers  (2022-10-13T17:20:45Z)
• Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing [66.55478402233399]
  We propose a framework to elicit relational structures via a probing procedure based on Poincar'e distance metric. Compared with commonly-used rule-based methods for schema linking, we found that probing relations can robustly capture semantic correspondences. Our framework sets new state-of-the-art performance on three benchmarks.
  arXiv  Detail & Related papers  (2022-06-28T14:05:25Z)
• "What makes my queries slow?": Subgroup Discovery for SQL Workload Analysis [1.3124513975412255]
  We introduce an original approach rooted on Subgroup Discovery. We show how to instantiate and develop this generic data-mining framework. We also provide a visualization tool for interactive knowledge discovery.
  arXiv  Detail & Related papers  (2021-08-09T09:44:13Z)
• Text Summarization with Latent Queries [60.468323530248945]
  We introduce LaQSum, the first unified text summarization system that learns Latent Queries from documents for abstractive summarization with any existing query forms. Under a deep generative framework, our system jointly optimize a latent query model and a conditional language model, allowing users to plug-and-play queries of any type at test time. Our system robustly outperforms strong comparison systems across summarization benchmarks with different query types, document settings, and target domains.
  arXiv  Detail & Related papers  (2021-05-31T21:14:58Z)
• Sequential Gallery for Interactive Visual Design Optimization [51.52002870143971]
  We propose a novel user-in-the-loop optimization method that allows users to efficiently find an appropriate parameter set. We also propose using a gallery-based interface that provides options in the two-dimensional subspace arranged in an adaptive grid view. Our experiment with synthetic functions shows that our sequential plane search can find satisfactory solutions in fewer iterations than baselines.
  arXiv  Detail & Related papers  (2020-05-08T15:24:35Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.