Query optimization
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Anchor DETR: Query Design for Transformer-Based Detector Open
In this paper, we propose a novel query design for the transformer-based object detection. In previous transformer-based detectors, the object queries are a set of learned embeddings. However, each learned embedding does not have an explic…
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Neo Open
Query optimization is one of the most challenging problems in database systems. Despite the progress made over the past decades, query optimizers remain extremely complex components that require a great deal of hand-tuning for specific wor…
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GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints Open
Multi-query attention (MQA), which only uses a single key-value head, drastically speeds up decoder inference. However, MQA can lead to quality degradation, and moreover it may not be desirable to train a separate model just for faster inf…
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Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases Open
Previous work on answering complex questions from knowledge bases usually separately addresses two types of complexity: questions with constraints and questions with multiple hops of relations. In this paper, we handle both types of comple…
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Learned Cardinalities: Estimating Correlated Joins with Deep Learning Open
We describe a new deep learning approach to cardinality estimation. MSCN is a multi-set convolutional network, tailored to representing relational query plans, that employs set semantics to capture query features and true cardinalities. MS…
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Bao: Making Learned Query Optimization Practical Open
Query optimization remains one of the most challenging problems in data management systems. Recent efforts to apply machine learning techniques to query optimization challenges have been promising, but have shown few practical gains due to…
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Query Rewriting for Horn-SHIQ Plus Rules Open
Query answering over Description Logic (DL) ontologies has become a vibrant field of research. Efficient realizations often exploit database technology and rewrite a given query to an equivalent SQL or Datalog query over a database associa…
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Data Query Mechanism Based on Hash Computing Power of Blockchain in Internet of Things Open
In the IoT (Internet of Things) environment, smart homes, smart grids, and telematics constantly generate data with complex attributes. These data have low heterogeneity and poor interoperability, which brings difficulties to data manageme…
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G-CORE Open
We report on a community effort between industry and academia to
\nshape the future of graph query languages. We argue that existing
\ngraph database management systems should consider supporting
\na query language with two key characteris…
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Apache Calcite Open
Apache Calcite is a foundational software framework that provides query processing, optimization, and query language support to many popular open-source data processing systems such as Apache Hive, Apache Storm, Apache Flink, Druid, and Ma…
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Query Resolution for Conversational Search with Limited Supervision Open
In this work we focus on multi-turn passage retrieval as a crucial component of conversational search. One of the key challenges in multi-turn passage retrieval comes from the fact that the current turn query is often underspecified due to…
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data Open
In the current ongoing crisis, people mostly rely on m obile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for mini…
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Task-Oriented Query Reformulation with Reinforcement Learning Open
Search engines play an important role in our everyday lives by assisting us in finding the information we need. When we input a complex query, however, results are often far from satisfactory. In this work, we introduce a query reformulati…
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On the Complexity of Consistent Query Answering in the Presence of Simple Ontologies Open
Consistent query answering is a standard approach for producing meaningful query answers when data is inconsistent. Recent work on consistent query answering in the presence of ontologies has shown this problem to be intractable in data co…
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Finding bugs in database systems via query partitioning Open
Logic bugs in Database Management Systems (DBMSs) are bugs that cause an incorrect result for a given query, for example, by omitting a row that should be fetched. These bugs are critical, since they are likely to go unnoticed by users. We…
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Learning to Optimize Join Queries With Deep Reinforcement Learning Open
Exhaustive enumeration of all possible join orders is often avoided, and most optimizers leverage heuristics to prune the search space. The design and implementation of heuristics are well-understood when the cost model is roughly linear, …
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Prompting Is Programming: A Query Language for Large Language Models Open
Large language models have demonstrated outstanding performance on a wide range of tasks such as question answering and code generation. On a high level, given an input, a language model can be used to automatically complete the sequence i…
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DialSQL: Dialogue Based Structured Query Generation Open
The recent advance in deep learning and semantic parsing has significantly improved the translation accuracy of natural language questions to structured queries. However, further improvement of the existing approaches turns out to be quite…
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G-OLA Open
Nearly 15 years ago, Hellerstein, Haas and Wang proposed online aggregation (OLA), a technique that allows users to (1) observe the progress of a query by showing iteratively refined approximate answers, and (2) stop the query execution on…
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Coarse-to-Fine Query Focused Multi-Document Summarization Open
We consider the problem of better modeling query-cluster interactions to facilitate query focused multi-document summarization. Due to the lack of training data, existing work relies heavily on retrieval-style methods for assembling query …
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An analytical study of large SPARQL query logs Open
With the adoption of RDF as the data model for Linked Data and the Semantic Web, query specification from end-users has become more and more common in SPARQL endpoints. In this paper, we conduct an in-depth analytical study of the queries …
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BERT-QE: Contextualized Query Expansion for Document Re-ranking Open
Query expansion aims to mitigate the mismatch between the language used in a query and in a document. However, query expansion methods can suffer from introducing non-relevant information when expanding the query. To bridge this gap, inspi…
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Fast queries over heterogeneous data through engine customization Open
Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of heterogeneous datasets to gain insights. The different data models and formats pose a significant challenge o…
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Efficient query processing for scalable web search Open
Search engines are exceptionally important tools for accessing information in today’s world. In satisfying the information needs of millions of users, the effectiveness (the quality of the search results) and the efficiency (the speed at w…
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Two-Level Sampling for Join Size Estimation Open
Join size estimation is a critical step in query optimization, and has been extensively studied in the literature. Among the many techniques, sampling based approaches are particularly appealing, due to their ability to handle arbitrary se…
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SkinnerDB Open
SkinnerDB is designed from the ground up for reliable join ordering. It\nmaintains no data statistics and uses no cost or cardinality models. Instead,\nit uses reinforcement learning to learn optimal join orders on the fly, during\nthe exe…
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Query-Biased Self-Attentive Network for Query-Focused Video Summarization Open
This paper addresses the task of query-focused video summarization, which takes user queries and long videos as inputs and generates query-focused video summaries. Compared to video summarization, which mainly concentrates on finding the m…
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Robust Query Processing in Co-Processor-accelerated Databases Open
Technology limitations are making the use of heterogeneous computing devices much more than an academic curiosity. In fact, the use of such devices is widely acknowledged to be the only promising way to achieve application-speedups that us…
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HoTTSQL: proving query rewrites with univalent SQL semantics Open
Every database system contains a query optimizer that performs query rewrites. Unfortunately, developing query optimizers remains a highly challenging task. Part of the challenges comes from the intricacies and rich features of query langu…
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Balsa: Learning a Query Optimizer Without Expert Demonstrations Open
Query optimizers are a performance-critical component in every database system. Due to their complexity, optimizers take experts months to write and years to refine. In this work, we demonstrate for the first time that learning to optimize…