Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleMay 2024
Wii: Dynamic Budget Reallocation In Index Tuning
Proceedings of the ACM on Management of Data (PACMMOD), Volume 2, Issue 3Article No.: 182, Pages 1–26https://doi.org/10.1145/3654985Index tuning aims to find the optimal index configuration for an input workload. It is often a time-consuming and resource-intensive process, largely attributed to the huge amount of "what-if" calls made to the query optimizer during configuration ...
- research-articleMay 2024
Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks
- Peng Li,
- Yeye He,
- Dror Yashar,
- Weiwei Cui,
- Song Ge,
- Haidong Zhang,
- Danielle Rifinski Fainman,
- Dongmei Zhang,
- Surajit Chaudhuri
Proceedings of the ACM on Management of Data (PACMMOD), Volume 2, Issue 3Article No.: 176, Pages 1–28https://doi.org/10.1145/3654979Language models, such as GPT-3 and ChatGPT, demonstrate remarkable abilities to follow diverse human instructions and perform a wide range of tasks, using instruction fine-tuning. However, when we test language models with a range of basic table-...
- research-articleMay 2024
Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations
Proceedings of the ACM on Management of Data (PACMMOD), Volume 2, Issue 3Article No.: 122, Pages 1–27https://doi.org/10.1145/3654925Spreadsheets are widely recognized as the most popular end-user programming tools, which blend the power of formula-based computation, with an intuitive table-based interface. Today, spreadsheets are used by billions of users to manipulate tables, most ...
- research-articleMarch 2024
Wred: Workload Reduction for Scalable Index Tuning
Proceedings of the ACM on Management of Data (PACMMOD), Volume 2, Issue 1Article No.: 50, Pages 1–26https://doi.org/10.1145/3639305Modern database systems offer index-tuning advisors that automatically identify a set of indexes to improve workload performance. Advisors leverage the optimizer's what-if API to optimize a query for a hypothetical index configuration. Because what-if ...
- research-articleMarch 2024
Cache-Efficient Top-k Aggregation over High Cardinality Large Datasets
Proceedings of the VLDB Endowment (PVLDB), Volume 17, Issue 4Pages 644–656https://doi.org/10.14778/3636218.3636222Top-k aggregation queries are widely used in data analytics for summarizing and identifying important groups from large amounts of data. These queries are usually processed by first computing exact aggregates for all groups and then selecting the groups ...
-
- research-articleSeptember 2023
Flexible Resource Allocation for Relational Database-as-a-Service
- Pankaj Arora,
- Surajit Chaudhuri,
- Sudipto Das,
- Junfeng Dong,
- Cyril George,
- Ajay Kalhan,
- Arnd Christian König,
- Willis Lang,
- Changsong Li,
- Feng Li,
- Jiaqi Liu,
- Lukas M. Maas,
- Akshay Mata,
- Ishai Menache,
- Justin Moeller,
- Vivek Narasayya,
- Matthaios Olma,
- Morgan Oslake,
- Elnaz Rezai,
- Yi Shan,
- Manoj Syamala,
- Shize Xu,
- Vasileios Zois
Proceedings of the VLDB Endowment (PVLDB), Volume 16, Issue 13Pages 4202–4215https://doi.org/10.14778/3625054.3625058Oversubscription is an essential cost management strategy for cloud database providers, and its importance is magnified by the emerging paradigm of serverless databases. In contrast to general purpose techniques used for oversubscription in hypervisors, ...
- research-articleAugust 2023
Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4991–5003https://doi.org/10.1145/3580305.3599776Data pipelines are widely employed in modern enterprises to power a variety of Machine-Learning (ML) and Business-Intelligence (BI) applications. Crucially, these pipelines are recurring (e.g., daily or hourly) in production settings to keep data ...
- research-articleJune 2023
T-Rex: Optimizing Pattern Search on Time Series
Proceedings of the ACM on Management of Data (PACMMOD), Volume 1, Issue 2Article No.: 130, Pages 1–26https://doi.org/10.1145/3589275Pattern search is an important class of queries for time series data. Time series patterns often match variable-length segments with a large search space, thereby posing a significant performance challenge. The existing pattern search systems, for ...
- research-articleJuly 2022
The Seattle report on database research
- Daniel Abadi,
- Anastasia Ailamaki,
- David Andersen,
- Peter Bailis,
- Magdalena Balazinska,
- Philip A. Bernstein,
- Peter Boncz,
- Surajit Chaudhuri,
- Alvin Cheung,
- Anhai Doan,
- Luna Dong,
- Michael J. Franklin,
- Juliana Freire,
- Alon Halevy,
- Joseph M. Hellerstein,
- Stratos Idreos,
- Donald Kossmann,
- Tim Kraska,
- Sailesh Krishnamurthy,
- Volker Markl,
- Sergey Melnik,
- Tova Milo,
- C. Mohan,
- Thomas Neumann,
- Beng Chin Ooi,
- Fatma Ozcan,
- Jignesh Patel,
- Andrew Pavlo,
- Raluca Popa,
- Raghu Ramakrishnan,
- Christopher Re,
- Michael Stonebraker,
- Dan Suciu
Communications of the ACM (CACM), Volume 65, Issue 8August 2022, Pages 72–79https://doi.org/10.1145/3524284Every five years, a group of the leading database researchers meet to reflect on their community's impact on the computing industry as well as examine current research challenges.
- research-articleJune 2022
ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning
SIGMOD '22: Proceedings of the 2022 International Conference on Management of DataJune 2022, Pages 660–673https://doi.org/10.1145/3514221.3526152Today's database systems include index advisors that recommend an appropriate set of indexes for an input workload. Since index tuning on large and complex workloads can be resource-intensive and time-consuming, workload compression techniques have been ...
- research-articleJune 2022
Budget-aware Index Tuning with Reinforcement Learning
- Wentao Wu,
- Chi Wang,
- Tarique Siddiqui,
- Junxiong Wang,
- Vivek Narasayya,
- Surajit Chaudhuri,
- Philip A. Bernstein
SIGMOD '22: Proceedings of the 2022 International Conference on Management of DataJune 2022, Pages 1528–1541https://doi.org/10.1145/3514221.3526128Index tuning aims to find the optimal index configuration for an input workload. It is a resource-intensive task since it requires making multiple expensive "what-if" calls to the query optimizer to estimate the cost of a query given an index ...
- tutorialJune 2022
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities
SIGMOD '22: Proceedings of the 2022 International Conference on Management of DataJune 2022, Pages 2465–2473https://doi.org/10.1145/3514221.3522566Enterprises are moving their business-critical workloads to public clouds at an accelerating pace. Multi-tenancy is a crucial tenet for cloud data service providers allowing them to provide services in cost-effective manner by sharing of resources among ...
- research-articleJune 2022
DISTILL: low-overhead data-driven techniques for filtering and costing indexes for scalable index tuning
Proceedings of the VLDB Endowment (PVLDB), Volume 15, Issue 10Pages 2019–2031https://doi.org/10.14778/3547305.3547309Many database systems offer index tuning tools that help automatically select appropriate indexes for improving the performance of an input workload. Index tuning is a resource-intensive and time-consuming task requiring expensive optimizer calls for ...
- research-articleNovember 2021
Leveraging query logs and machine learning for parametric query optimization
Proceedings of the VLDB Endowment (PVLDB), Volume 15, Issue 3Pages 401–413https://doi.org/10.14778/3494124.3494126Parametric query optimization (PQO) must address two problems: identify a relatively small number of plans to cache for a parameterized query (populateCache), and efficiently select the best cached plan to use for executing any instance of the ...
- research-articleSeptember 2021
DSB: a decision support benchmark for workload-driven and traditional database systems
Proceedings of the VLDB Endowment (PVLDB), Volume 14, Issue 13Pages 3376–3388https://doi.org/10.14778/3484224.3484234We describe a new benchmark, DSB, for evaluating both workload-driven and traditional database systems on modern decision support workloads. DSB is adapted from the widely-used industrial-standard TPC-DS benchmark. It enhances the TPC-DS benchmark with ...
- research-articleJuly 2021
Hyperspace: the indexing subsystem of azure synapse
- Rahul Potharaju,
- Terry Kim,
- Eunjin Song,
- Wentao Wu,
- Lev Novik,
- Apoorve Dave,
- Andrew Fogarty,
- Pouria Pirzadeh,
- Vidip Acharya,
- Gurleen Dhody,
- Jiying Li,
- Sinduja Ramanujam,
- Nicolas Bruno,
- César A. Galindo-Legaria,
- Vivek Narasayya,
- Surajit Chaudhuri,
- Anil K. Nori,
- Tomas Talius,
- Raghu Ramakrishnan
Proceedings of the VLDB Endowment (PVLDB), Volume 14, Issue 12Pages 3043–3055https://doi.org/10.14778/3476311.3476382Microsoft recently introduced Azure Synapse Analytics, which offers an integrated experience across data ingestion, storage, and querying in Apache Spark and T-SQL over data in the lake, including files and warehouse tables. In this paper, we present our ...
- research-articleJuly 2021
Auto-pipeline: synthesizing complex data pipelines by-target using reinforcement learning and search
Proceedings of the VLDB Endowment (PVLDB), Volume 14, Issue 11Pages 2563–2575https://doi.org/10.14778/3476249.3476303Recent work has made significant progress in helping users to automate single data preparation steps, such as string-transformations and table-manipulation operators (e.g., Join, GroupBy, Pivot, etc.). We in this work propose to automate multiple such ...
- research-articleJuly 2021
COMPARE: accelerating groupwise comparison in relational databases for data analytics
Proceedings of the VLDB Endowment (PVLDB), Volume 14, Issue 11Pages 2419–2431https://doi.org/10.14778/3476249.3476291Data analysis often involves comparing subsets of data across many dimensions for finding unusual trends and patterns. While the comparison between subsets of data can be expressed using SQL, they tend to be complex to write, and suffer from poor ...
- research-articleJune 2021
Auto-FuzzyJoin: Auto-Program Fuzzy Similarity Joins Without Labeled Examples
SIGMOD '21: Proceedings of the 2021 International Conference on Management of DataJune 2021, Pages 1064–1076https://doi.org/10.1145/3448016.3452824Fuzzy similarity join is an important database operator widely used in practice. So far the research community has focused exclusively on optimizing fuzzy joinscalability. However, practitioners today also struggle to optimize fuzzy-joinquality, because ...
- review-articleMay 2021
Cloud Data Services: Workloads, Architectures and Multi-Tenancy
Foundations and Trends in Databases (TRDB), Volume 10, Issue 1May 2021, Pages 1–107https://doi.org/10.1561/1900000060Enterprises are moving their business critical workloads to public clouds at an accelerating pace. Cloud data services for Online Transaction Processing (OLTP), Data Analytics and NoSQL are essential building blocks for enterprise applications. Multi-tenancy ...