Abstract Multi-core scalability presents a major implementation challenge for data system designers today. Traditional methods such as latching no longer scale in today’s highly parallel architectures. While the designer can make use of techniques such as latch-free programming to painstakingly design specialized, highly-performant solutions, such solutions are often intricate to build and difficult to reason about. Of particular interest to data system designers is a class of data structures we call almost-latch-free; such data structures can be made scalable in the common case, but have rare complications (e.g., dynamic resizing) that prevent full latch-free implementations. In this work, we present a new programming framework called Epoch-Protected Version Scheme (EPVS) to make it easy to build such data structures. EPVS makes use of epoch protection to preserve performance in the common case of latch-free operations, while allowing users to specify critical sections that execute under mutual exclusion for the rare, non-latch-free operations. We showcase the use of EPVS-based concurrency primitives in a few practical systems to demonstrate its competitive performance and intuitive guarantees. EPVS is available in open source as part of Microsoft’s FASTER project (Epoch Protected Version Scheme (source code) 2022; Microsoft FASTER 2022).

To provide applications with the ability to analyze fresh data and eliminate the time-consuming ETL workflow, hybrid transactional and analytical (HTAP) systems have been developed to serve online transaction processing and online analytical processing workloads in a single system. In recent years, HTAP systems have attracted considerable interest from both academia and industry. Several new architectures and technologies have been proposed. This paper provides a comprehensive overview of these HTAP systems. We review recently published papers and technical reports in this field and broadly classify existing HTAP systems into two categories based on their data formats: monolithic and hybrid HTAP. We further classify hybrid HTAP into four sub-categories based on their storage architecture: row-oriented, column-oriented, separated, and hybrid. Based on such a taxonomy, we outline each stream’s design challenges and performance issues (e.g., the contradictory format demand for monolithic HTAP). We then discuss potential solutions and their trade-offs by reviewing noteworthy research findings. Finally, we summarize emerging HTAP applications, benchmarks, future trends, and open problems.

Abstract Uncertain butterflies are one of, if not the, most important graphlet structures on uncertain bipartite networks. In this paper, we examine the uncertain butterfly structure (in which the existential probability of the graphlet is greater than or equal to a threshold parameter), as well as the global Uncertain Butterfly Counting Problem (to count the total number of these instances over an entire network). To solve this task, we propose a non-trivial exact baseline (UBFC), as well as an improved algorithm (IUBFC) which we show to be faster both theoretically and practically. We also design two sampling frameworks (UBS and PES) which can sample either a vertex, edge or wedge from the network uniformly and estimate the global count quickly. Furthermore, a notable butterfly-based community structure which has been examined in the past is the k-bitruss. We adapt this community structure onto the uncertain bipartite graph setting and introduce the Uncertain Bitruss Decomposition Problem (which can be used to directly answer any k-bitruss search query for any k). We then propose an exact algorithm (UBitD) to solve our problem with three variations in deriving the initial uncertain support. Using a range of networks with different edge existential probability distributions, we validate the efficiency and effectiveness of our solutions.