Proceedings of the ACM on Management of Data

Welcome to Issue 1 of Volume 2 of the Proceedings of the ACM on Management of Data, which has papers from the third round of submissions to the SIGMOD research track.

Out of 230 submissions in this round, whose submission deadline was July 15, 2023, a ...

Distributed protocols such as 2PC and Paxos lie at the core of many systems in the cloud, but standard implementations do not scale. New scalable distributed protocols are developed through careful analysis and rewrites, but this process is ad hoc and ...

Range filters allow checking whether a query range intersects a given set of keys with a chance of returning a false positive answer, thus generalising the functionality of Bloom filters from point to range queries. Existing practical range filters have ...

Error-bounded lossy compression has been identified as a promising solution for significantly reducing scientific data volumes upon users' requirements on data distortion. For the existing scientific error-bounded lossy compressors, some of them (such as ...

A persistent Regular Path Query (RPQ) on a streaming graph is to continuously find every pair of vertices that are connected by a path in the graph within a sliding window, such that the edge label sequence of this path matches a given regular ...

The prevalence of computer graphics technology boosts the developments of point clouds in recent years, which offer advantages over terrain surfaces (represented by Triangular Irregular Networks, i.e., TINs) in proximity queries, including the shortest ...

k-clique listing is a vital graph mining operator with diverse applications in various networks. The state-of-the-art algorithms all adopt a branch-and-bound (BB) framework with a vertex-oriented branching strategy (called VBBkC), which forms a sub-...

Formal feature explanations strictly maintain perfect conformity but are intractable to compute, while heuristic methods are much faster but can lead to problematic explanations due to lack of conformity guarantees. We propose relative keys that have the ...

Substantial research efforts have been devoted to studying the performance optimality problem for distributed database transactions. However, they focus just on optimizing transactional reads, and thus overlook crucial factors, such as the efficiency of ...

Despite the promising performance of recent learning-based Index Advisors (IAs), they exhibited the robustness issue when poisoning attacks polluted training data. This paper presents the first attempt to study the robustness of updatable learning-based ...

Nearest neighbor search is a fundamental task in various domains, such as federated learning, data mining, information retrieval, and biomedicine. With the increasing need to utilize data from different organizations while respecting privacy regulations, ...

Network telemetry, characterized by its efficient push model and high-performance communication protocol (gRPC), offers a new avenue for collecting fine-grained real-time data. Despite its advantages, existing network telemetry systems lack a theoretical ...

Stream Window Join (SWJ), a vital operation in stream analytics, struggles with achieving a balance between accuracy and latency due to out-of-order data arrivals. Existing methods predominantly rely on adaptive buffering, but often fall short in ...

High-dimensional vector similarity search (HVSS) is gaining prominence as a powerful tool for various data science and AI applications. As vector data scales up, in-memory indexes pose a significant challenge due to the substantial increase in main ...

The modern database has many precise and approximate counting requirements. Nevertheless, a solitary multidimensional index or cardinality estimator is insufficient to cater to the escalating demands across all counting scenarios. Such approaches are ...

Datalog is a declarative programming language that has gained popularity in various domains due to its simplicity, expressiveness, and efficiency. But "pure" Datalog is limited to monotone queries, and cannot be used in most practical applications. For ...

Q-error -- the standard metric for quantifying the error of individual cardinality estimates -- has been widely adopted as a surrogate for query plan optimality in recent work on learning-based cardinality estimation. However, the only result connecting ...

K-Multiple-Means is an extension of K-means for the clustering of multiple means used in many applications, such as image segmentation, load balancing, and blind-source separation. Since K-means uses only one mean to represent each cluster, it fails to ...

Scalable video query optimization has re-emerged as an attractive research topic in recent years. The OTIF system, a video database with cutting-edge efficiency, has introduced a new paradigm of utilizing view materialization to facilitate online query ...

We study the problem of temporal database indexing, i.e., indexing versions of a database table in an evolving database. With the larger and cheaper memory chips nowadays, we can afford to keep track of all versions of an evolving table in memory. This ...

Supporting the interactive exploration of large datasets is a popular and challenging use case for data management systems. Traditionally, the interface and the back-end system are built and optimized separately, and interface design and system ...

The enumeration of hop-constrained simple paths is a building block in many graph-based areas. Due to the enormous search spaces in large-scale graphs, a single machine can hardly satisfy the requirements of both efficiency and memory, which causes an ...

A bipartite graph contains inter-set edges between two disjoint vertex sets, and is widely used to model real-world data, such as user-item purchase records, author-article publications, and biological interactions between drugs and proteins. k-Bipartite ...

Many organizations rely on data from government and third-party sources, and those sources rarely follow the same data formatting. This introduces challenges in integrating data from multiple sources or aligning external sources with internal databases. ...

Quantiles are fundamental statistics in various data science tasks, but costly to compute, e.g., by loading the entire data in memory for ranking. With limited memory space, prevalent in end devices or databases with heavy loads, it needs to scan the ...

Given two sets of elements held by two different parties separately, computing the cardinality (i.e., the number of distinct elements) of their intersection set is a fundamental task in applications such as network monitoring and database systems. To ...

Dynamic graphs have been gaining increasing popularity across various application domains. With the growing size of these graphs, the update performance as well as space occupancy is becoming a crucial aspect of dynamic graph storage. Although existing ...

Controllable tabular data synthesis plays a crucial role in numerous applications by allowing users to generate synthetic data with specific conditions. These conditions can include synthesizing tuples with predefined attribute values or creating tuples ...

As one of the most primitive operators in graph algorithms, such as the triangle counting, maximal clique enumeration, and subgraph listing, a set intersection operator returns common vertices between any two given sets of vertices in data graphs. It is ...

Top-k frequent items detection is a fundamental task in data stream mining. Many promising solutions are proposed to improve memory efficiency while still maintaining high accuracy for detecting the Top-k items. Despite the memory efficiency concern, the ...