Proceedings of the VLDB Endowment

We study the set similarity join problem, which retrieves all pairs of similar sets from two collections of sets for a given distance function. Existing exact solutions employ a signature-based filter-verification framework: If two sets are similar, ...

Data trees, typically encoded in JSON, are ubiquitous in data-driven applications. This ubiquity makes urgent the development of novel techniques for querying heterogeneous JSON data in a flexible manner. We propose a rule language for JSON, called ...

We introduce EQUI-VOCAL: a new system that automatically synthesizes queries over videos from limited user interactions. The user only provides a handful of positive and negative examples of what they are looking for. EQUI-VOCAL utilizes these initial ...

Recent advances in Graph Neural Networks (GNNs) have changed the landscape of modern graph analytics. The complexity of GNN training and the scalability challenges have also sparked interest from the systems community, with efforts to build systems that ...

Developers are increasingly building applications that incorporate multiple data stores, for example to manage heterogeneous data. Often, these require transactional safety for operations across stores, but few systems support such guarantees. To solve ...

Data processing systems often leverage vector instructions to achieve higher performance. When applying vector instructions, an often overlooked data structure is the hash table, even though it is fundamental in data processing systems for operations ...

Elasticity of compute and storage is crucial for analytical cloud database systems. All cloud vendors provide disaggregated object stores, which can be used as storage backend for analytical query engines. Until recently, local storage was unavoidable ...

A huge amount of data, in terms of streams, are collected nowadays via a variety of sources, such as sensors, mobile devices, or even raw log files. The unprecedented rate at which these data are generated and collected calls for novel record linkage ...

In this paper, we present the REmatch system for information extraction. REmatch is based on a recently proposed enumeration algorithm for evaluating regular expressions with capture variables supporting the all-match semantics. It tells a story of what ...

The performance of worst-case optimal join algorithms depends on the order in which the join attributes are processed. Selecting good orders before query execution is hard, due to the large space of possible orders and unreliable execution cost ...

In many real-world applications such as social network analysis and online advertising/marketing, one of the most important and popular problems is called influence maximization (IM), which finds a set of k seed users that maximize the expected number ...

Median absolute deviation (MAD), the median of the absolute deviations from the median, has been found useful in various applications such as outlier detection. Together with median, MAD is more robust to abnormal data than mean and standard deviation (...

The vast amounts of data collected in various domains pose great challenges to modern data exploration and analysis. To find "interesting" objects in large databases, users typically define a query using positive and negative example objects and train a ...

The chase procedure is a fundamental algorithmic tool in databases that allows us to reason with constraints, such as existential rules, with a plethora of applications. It takes as input a database and a set of constraints, and iteratively completes ...

Cardinality estimation is widely believed to be one of the most important causes of poor query plans. Prior studies evaluate the impact of cardinality estimation on plan quality on a set of Select-Project-Join queries on PostgreSQL DBMS. Our empirical ...

We propose WALTZ, an LSM tree-based key-value store on the emerging Zoned Namespace (ZNS) SSD. The key contribution of WALTZ is to leverage the zone append command, which is a recent addition to ZNS SSD specifications, to provide tight tail latency. The ...

Analysts and scientists are interested in querying streams of video, audio, and text to extract quantitative insights. For example, an urban planner may wish to measure congestion by querying the live feed from a traffic camera. Prior work has used deep ...

SQL query performance is critical in database applications, and query rewriting is a technique that transforms an original query into an equivalent query with a better performance. In a wide range of database-supported systems, there is a unique problem ...

This paper proposes a novel framework for certifying the fairness of predictive models trained on biased data. It draws from query answering for incomplete and inconsistent databases to formulate the problem of consistent range approximation (CRA) of ...

Subgraph-based graph representation learning (SGRL) has recently emerged as a powerful tool in many prediction tasks on graphs due to its advantages in model expressiveness and generalization ability. Most previous SGRL models face computational issues ...

PageRank is a famous measure of graph centrality that has numerous applications in practice. The problem of computing a single node's PageRank has been the subject of extensive research over a decade. However, existing methods still incur large time ...

There have been many decades of work on optimizing query processing in database management systems. Recently, modern machine learning (ML), and specifically reinforcement learning (RL), has gained increased attention as a means to develop a query ...

B-trees are the go-to data structure for in-memory indexes in databases and storage systems. B-trees support both point operations (i.e., inserts and finds) and range operations (i.e., iterators and maps). However, there is an inherent tradeoff between ...

Deep graph networks (DGNs) have demonstrated their outstanding effectiveness on both heterogeneous and homogeneous graphs. However their black-box nature does not allow human users to understand their working mechanisms. Recently, extensive efforts have ...

Extracting roads from multi-source data, such as aerial images and vehicle trajectories, is an important way to maintain road networks in the filed of urban computing. In this paper, we revisit the problem of road extraction and aim to boost its ...

Query optimization is essential for the efficient execution of queries. The necessary analysis, if we can and should apply optimizations and transform the query plan, is already challenging. Traditional techniques focus on the availability of columns at ...

Normalization aims at minimizing sources of potential data inconsistency and costs of update maintenance incurred by data redundancy. For relational databases, different classes of dependencies cause data redundancy and have resulted in proposals such ...

This paper evaluates the suitability of Apache Arrow, Parquet, and ORC as formats for subsumption in an analytical DBMS. We systematically identify and explore the high-level features that are important to support efficient querying in modern OLAP DBMSs ...

Recent data search platforms use ML task-based utility measures rather than metadata-based keywords, to search large dataset corpora. Requesters submit a training dataset, and these platforms search for augmentations---join or union-compatible datasets--...

Although dominant for tabular data, ML libraries that train tree models over normalized databases (e.g., LightGBM, XGBoost) require the data to be denormalized as a single table, materialized, and exported. This process is not scalable, slow, and poses ...