{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T22:53:17Z","timestamp":1757631197703,"version":"3.44.0"},"reference-count":17,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p>Query rewriting is an important technique to optimize SQL performance in databases. With the prevalent use of business intelligence systems and object-relational mapping frameworks, existing rewriting capabilities inside databases are insufficient to optimize machine-generated queries. In this paper, we propose a novel system called \"QueryBooster,\" to support SQL query rewriting as a cloud service. It provides a powerful and easy-to-use Web interface for users to formulate rewriting rules via a language or express rewriting intentions by providing example query pairs. It allows multiple users to share rewriting knowledge and automatically suggests shared rewriting rules for users. It requires no modifications or plugin installations to applications or databases. In this demonstration, we use real-world applications and datasets to show the user experience of QueryBooster to rewrite their application queries and share rewriting knowledge.<\/jats:p>","DOI":"10.14778\/3611540.3611615","type":"journal-article","created":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T11:32:37Z","timestamp":1694777557000},"page":"4038-4041","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Demo of QueryBooster: Supporting Middleware-Based SQL Query Rewriting as a Service"],"prefix":"10.14778","volume":"16","author":[{"given":"Qiushi","family":"Bai","sequence":"first","affiliation":[{"name":"University of California, Irvine"}]},{"given":"Sadeem","family":"Alsudais","sequence":"additional","affiliation":[{"name":"University of California, Irvine"}]},{"given":"Chen","family":"Li","sequence":"additional","affiliation":[{"name":"University of California, Irvine"}]}],"member":"320","published-online":{"date-parts":[[2023,8]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"ApexSQL: SQL execution plan viewing and analysis [n.d.]. https:\/\/www.apexsql.com\/sql-tools-plan.aspx. last accessed: 2023-01-07."},{"key":"e_1_2_1_2_1","volume-title":"BigVis Workshop of EDBT","volume":"3135","author":"Bai Qiushi","year":"2022","unstructured":"Qiushi Bai, Sadeem Alsudais, and Chen Li. 2022. 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