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Related papers: MTBase: Optimizing Cross-Tenant Database Queries

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Conventional text-to-SQL parsers are not good at synthesizing complex SQL queries that involve multiple tables or columns, due to the challenges inherent in identifying the correct schema items and performing accurate alignment between…

Computation and Language · Computer Science 2024-03-18 Yangjun Wu , Han Wang

A new emerging class of parallel database management systems (DBMS) is designed to take advantage of the partitionable workloads of on-line transaction processing (OLTP) applications. Transactions in these systems are optimized to execute…

Databases · Computer Science 2011-11-01 Andrew Pavlo , Evan P. C. Jones , Stanley Zdonik

Recently, the database management system (DBMS) community has witnessed the power of machine learning (ML) solutions for DBMS tasks. Despite their promising performance, these existing solutions can hardly be considered satisfactory. First,…

Databases · Computer Science 2021-11-29 Ziniu Wu , Pei Yu , Peilun Yang , Rong Zhu , Yuxing Han , Yaliang Li , Defu Lian , Kai Zeng , Jingren Zhou

In this paper, we propose Multi-Modal Databases (MMDBs), which is a new class of database systems that can seamlessly query text and tables using SQL. To enable seamless querying of textual data using SQL in an MMDB, we propose to extend…

Databases · Computer Science 2023-05-01 Matthias Urban , Carsten Binnig

HRDBMS is a novel distributed relational database that uses a hybrid model combining the best of traditional distributed relational databases and Big Data analytics platforms such as Hive. This allows HRDBMS to leverage years worth of…

Databases · Computer Science 2019-01-28 Jason Arnold , Boris Glavic , Ioan Raicu

Multi-cloud computing systems face significant challenges in ensuring acceptable performance while adhering to tenant budget requirements. This paper proposes a tenant budget-aware (tenant-centric) data replication framework for Multi-Cloud…

A large number of cloud middleware platforms and tools are deployed to support a variety of Internet of Things (IoT) data analytics tasks. It is a common practice that such cloud platforms are only used by its owners to achieve their…

Networking and Internet Architecture · Computer Science 2016-06-28 Prem Prakash Jayaraman , Charith Perera , Dimitrios Georgakopoulos , Schahram Dustdar , Dhavalkumar Thakker , Rajiv Ranjan

In today's Web and social network environments, query workloads include ad hoc and OLAP queries, as well as iterative algorithms that analyze data relationships (e.g., link analysis, clustering, learning). Modern DBMSs support ad hoc and…

Databases · Computer Science 2012-08-02 Svilen R. Mihaylov , Zachary G. Ives , Sudipto Guha

Metadata hotspots remain one of the key obstacles to scalable Input/Output (I/O) in both High-Performance Computing (HPC) and cloud-scale storage environments. Situations such as job start-ups, checkpoint storms, or heavily skewed namespace…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-25 Sangam Ghimire , Nigam Niraula , Nirjal Bhurtel , Paribartan Timalsina , Bishal Neupane , James Bhattarai , Sudan Jha

In binary classification systems, decision thresholds translate model scores into actions. Choosing suitable thresholds relies on the specific distribution of the underlying model scores but also on the specific business decisions of each…

With the rise of machine learning, inference on deep neural networks (DNNs) has become a core building block on the critical path for many cloud applications. Applications today rely on isolated ad-hoc deployments that force users to…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-24 Amit Samanta , Suhas Shrinivasan , Antoine Kaufmann , Jonathan Mace

In this paper, we describe a multidatabase system as 4tiered Client-Server DBMS architectures. We discuss their functional components and provide an overview of their performance characteristics. The first component of this proposed system…

Databases · Computer Science 2009-12-04 Mohammad Ghulam Ali

Enterprises increasingly adopt multi cloud architectures to take advantage of diverse database engines, regional availability, and cost models. In these environments, ETL pipelines must process large, distributed datasets while minimizing…

Treasure Data is processing millions of distributed SQL queries every day on the cloud. Upgrading the query engine service at this scale is challenging because we need to migrate all of the production queries of the customers to a new…

The ranked retrieval model has rapidly become the de facto way for search query processing in client-server databases, especially those on the web. Despite of the extensive efforts in the database community on designing better ranking…

Databases · Computer Science 2016-11-09 Abolfazl Asudeh , Nan Zhang , Gautam Das

With the rapid rise of intelligent data services, modern enterprises increasingly require efficient, multimodal, and cost-effective data analytics infrastructures. However, in ByteDance's production environments, existing systems fall short…

When multiple tenants compete for resources, database performance tends to suffer. Yet there are scenarios where guaranteed sub-millisecond latencies are crucial, such as in real-time data processing, IoT devices, or when operating in…

Databases · Computer Science 2024-09-04 Wolfgang Mauerer , Ralf Ramsauer , Edson R. F. Lucas , Stefanie Scherzinger

Message-oriented-middleware (MOM) has become an small industry. MOM offers queued transaction processing as an advance over pure client-server transaction processing. This note makes four points: Queued transaction processing is less…

Databases · Computer Science 2007-05-23 Jim Gray

Addressing the mismatch between natural language descriptions and the corresponding SQL queries is a key challenge for text-to-SQL translation. To bridge this gap, we propose an SQL intermediate representation (IR) called Natural SQL…

Computation and Language · Computer Science 2021-09-14 Yujian Gan , Xinyun Chen , Jinxia Xie , Matthew Purver , John R. Woodward , John Drake , Qiaofu Zhang

The broadening adoption of machine learning in the enterprise is increasing the pressure for strict governance and cost-effective performance, in particular for the common and consequential steps of model storage and inference. The RDBMS…