Shows
Disseminate: The Computer Science Research PodcastXiangyao Yu | Disaggregation: A New Architecture for Cloud Databases | #68In this episode of Disseminate: The Computer Science Research Podcast, host Jack Waudby sits down with Xiangyao Yu (UW–Madison), one of the leading voices shaping the next generation of cloud-native databases.We dive deep into disaggregation — the architectural shift transforming how modern data systems are built. Xiangyao breaks down:Why traditional shared-nothing databases struggle in cloud environmentsHow separating compute and storage unlocks elasticity, scalability, and cost efficiencyThe evolution of disaggregated systems, from Aurora and Snowflake through to advanced pushdown processing and new modular servicesHis team's research on reinventing core protocols like 2-phase commit for clou...
2025-11-2742 min
Disseminate: The Computer Science Research PodcastNavid Eslami | Diva: Dynamic Range Filter for Var-Length Keys and Queries | #67In this episode of Disseminate: The Computer Science Research Podcast, Jack sits down with Navid Eslami, PhD researcher at the University of Toronto, to discuss his award-winning paper “DIVA: Dynamic Range Filter for Variable Length Keys and Queries”, which earned Best Research Paper at VLDB.Navid breaks down how range filters extend the power of traditional filters for modern databases and storage systems, enabling faster queries, better scalability, and theoretical guarantees. We dive into:How DIVA overcomes the limitations of existing range filtersWhat makes it the “holy grail” of filtering for dynamic dataReal-world integration in WiredTig...
2025-11-1346 min
Disseminate: The Computer Science Research PodcastAdaptive Factorization in DuckDB with Paul GroßIn this episode of the DuckDB in Research series, host Jack Waudby sits down with Paul Groß, PhD student at CWI Amsterdam, to explore his work on adaptive factorization and worst-case optimal joins - techniques that push the boundaries of analytical query performance.Paul shares insights from his CIDR'25 paper “Adaptive Factorization Using Linear Chained Hash Tables”, revealing how decades of database theory meet modern, practical system design in DuckDB. From hash table internals to adaptive query planning, this episode uncovers how research innovations are becoming part of real-world systems.Whether you’re a datab...
2025-11-0651 min
Disseminate: The Computer Science Research PodcastParachute: Rethinking Query Execution and Bidirectional Information Flow in DuckDB - with Mihail StoianIn this episode of the DuckDB in Research series, host Jack Waudby sits down with Mihail Stoian, PhD student at the Data Systems Lab, University of Technology Nuremberg, to unpack the cutting-edge ideas behind Parachute, a new approach to robust query processing and bidirectional information passing in modern analytical databases.We explore how Parachute bridges theory and practice, combining concepts from instance-optimal algorithms and semi-join filtering to boost performance in DuckDB, the in-process analytical SQL engine that’s reshaping how research meets real-world data systems.Mihail discusses:How Parachute extends semi-join filtering fo...
2025-10-3036 min
Disseminate: The Computer Science Research PodcastAnarchy in the Database: Abigale Kim on DuckDB and DBMS ExtensibilityIn this episode of the DuckDB in Research series, host Jack Waudby talks with Abigale Kim, PhD student at the University of Wisconsin–Madison and author of VLDB 2025 paper: “Anarchy in the Database: A Survey and Evaluation of DBMS Extensibility”. They explore how database extensibility is reshaping modern data systems — and why DuckDB is emerging as the gold standard for safe, flexible, and high-performance extensions. Abigale shares the inside story of her research, the surprises uncovered when testing Postgres and DuckDB extensions, and what’s next for extensibility and composable database design.This episode is perfect for resear...
2025-10-2346 min
Disseminate: The Computer Science Research PodcastRecursive CTEs, Trampolines, and Teaching Databases with DuckDB - with Prof. Torsten GrustIn this episode of the DuckDB in Research series, host Dr Jack Waudby talks with Professor Torsten Grust from the University of Tübingen. Torsten is one of the pioneers behind DuckDB’s implementation of recursive CTEs.In the episode they unpack:The power of recursive CTEs and how they turn SQL into a full-fledged programming language.The story behind adding recursion to DuckDB, including the using key feature and the trampoline and TTL extensions emerging from Torsten’s lab.How these ideas are transforming research, teaching, and even DuckDB’s internal architecture.Why DuckDB makes d...
2025-10-1651 min
Disseminate: The Computer Science Research PodcastDuckDB in Research S2 Coming Soon!Hey folks! The DuckDB in Research series is back for S2!In this season we chat with:Torsten Grust: Recursive CTEsAbigale Kim: Anarchy in the DatabaseMihail Stoian: Parachute: Single-Pass Bi-Directional Information PassingPaul Gross: Adaptive Factorization Using Linear-Chained Hash TablesWhether you're a researcher, engineer, or just curious about the intersection of databases and innovation we are sure you will love this series. Hosted on Acast. See acast.com/privacy for more information.
2025-10-1602 min
Disseminate: The Computer Science Research PodcastRohan Padhye & Ao Li | Fray: An Efficient General-Purpose Concurrency JVM Testing Platform | #66In this episode of Disseminate: The Computer Science Research Podcast, guest host Bogdan Stoica sits down with Ao Li and Rohan Padhye (Carnegie Mellon University) to discuss their OOPSLA 2025 paper: "Fray: An Efficient General-Purpose Concurrency Testing Platform for the JVM".We dive into:Why concurrency bugs remain so hard to catch -- even in "well-tested" Java projects.The design of Fray, a new concurrency testing platform that outperforms prior tools like JPF and rr.Real-world bugs discovered in Apache Kafka, Lucene, and Google Guava.The gap between academic research and industrial practice, and how Fray...
2025-10-0658 min
Disseminate: The Computer Science Research PodcastShrey Tiwari | It's About Time: A Study of Date and Time Bugs in Python Software | #65In this episode, Bogdan Stoica, Postdoctoral Research Associate in the SysNet group at the University of Illinois Urbana-Champaign (UIUC) steps in to guest host. Bogdan sits down with Shrey Tiwari, a PhD student in the Software and Societal Systems Department at Carnegie Mellon University and member of the PASTA Lab, advised by Prof. Rohan Padhye. Together, they dive into Shrey’s award-winning research on date and time bugs in open-source Python software, exploring why these issues are so deceptively tricky and how they continue to affect systems we rely on every day.The conversation traces Shrey’s jo...
2025-09-231h 05
Disseminate: The Computer Science Research PodcastLessons Learned from Five Years of Artifact Evaluations at EuroSys | #64In this episode we are joined by Thaleia Doudali, Miguel Matos, and Anjo Vahldiek-Oberwagner to delve into five years of experience managing artifact evaluation at the EuroSys conference. They explain the goals and mechanics of artifact evaluation, a voluntary process that encourages reproducibility and reusability in computer systems research by assessing the supporting code, data, and documentation of accepted papers. The conversation outlines the three-tiered badge system, the multi-phase review process, and the importance of open-source practices. The guests present data showing increasing participation, sustained artifact availability, and varying levels of community engagement, underscoring the growing relevance of artifacts...
2025-07-3043 min
Disseminate: The Computer Science Research PodcastDominik Winterer | Validating SMT Solvers for Correctness and Performance via Grammar-based Enumeration | #63In this episode of the Disseminate podcast, Dominik Winterer discusses his research on SMT (Satisfiability Modulo Theories) solvers and his recent OOPSLA paper titled "Validating SMT Solvers for Correction and Performance via Grammar Based Enumeration". Dominik shares his academic journey from the University of Freiburg to ETH Zurich, and now to a lectureship at the University of Manchester. He introduces ET, a tool he developed for exhaustive grammar-based testing of SMT solvers. Unlike traditional fuzzers that use random input generation, ET systematically enumerates small, syntactically valid inputs using context-free grammars to expose bugs more effectively. This approach simplifies bug...
2025-07-2543 min
Disseminate: The Computer Science Research PodcastHaralampos Gavriilidis | Fast and Scalable Data Transfer across Data Systems | #62In this episode of Disseminate, we welcome Harry Gavrilidis back to the podcast to explore his latest research on fast and scalable data transfer across systems, soon to be presented at SIGMOD 2025. Building on his work with XDB, Harry introduces XDBC, a novel data transfer framework designed to balance performance and generalizability. They dive into the challenges of moving data across heterogeneous environments—ranging from cloud systems to IoT devices—and critique the limitations of current generic methods like JDBC and specialized point-to-point connectors.Harry walks us through the architecture of XDBC, which modularizes the data tran...
2025-06-1656 min
Disseminate: The Computer Science Research PodcastHaralampos Gavriilidis | SheetReader: Efficient spreadsheet parsingIn this episode of the DuckDB in Research series, Harry Gavriilidis (PhD student at TU Berlin) joins us to discuss Sheet Reader — a high-performance spreadsheet parser that dramatically outpaces traditional tools in both speed and memory efficiency. By taking advantage of the standardized structure of spreadsheet files and bypassing generic XML parsers, Sheet Reader delivers fast and lightweight parsing, even on large files. Now available as a DuckDB extension, it enables users to query spreadsheets directly with SQL and integrate them seamlessly into broader analytical workflows.Harry shares insights into the development process, performance benchmarks, and th...
2025-04-1740 min
Disseminate: The Computer Science Research PodcastArjen P. de Vries | faiss: An extension for vector data & searchIn this episode of the DuckDB in Research series, we’re joined by Arjen de Vries, Professor of Data Science at Radboud University. Arjen dives into his team’s development of a DuckDB extension for FAISS, a library originally developed at Facebook for efficient similarity search and vector operations.We explore the growing importance of embeddings and dense retrieval in modern information retrieval systems, and how DuckDB’s zero-copy architecture and tight integration with the Python ecosystem make it a compelling choice for managing large-scale vector data. Arjen shares insights into the technical challenges and architectural decisi...
2025-04-1046 min
Disseminate: The Computer Science Research PodcastDavid Justen | POLAR: Adaptive and non-invasive join order selection via plans of least resistanceIn this episode, we sit down with David Justen to discuss his work on POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance which was implemented in DuckDB. David shares his journey in the database space, insights into performance optimization, and the challenges of working with modern analytical workloads. We dive into the intricacies of query compilation, vectorized execution, and how DuckDB is shaping the future of in-memory databases. Tune in for a deep dive into database internals, industry trends, and what’s next for high-performance data processing!Links: VLDB 2024 PaperDavid's Homepage
2025-04-0351 min
Disseminate: The Computer Science Research PodcastDaniël ten Wolde | DuckPGQ: A graph extension supporting SQL/PGQIn this episode, we sit down with Daniël ten Wolde, a PhD researcher at CWI’s Database Architectures Group, to explore DuckPGQ—an extension to DuckDB that brings powerful graph querying capabilities to relational databases. Daniel shares his journey into database research, the motivations behind DuckPGQ, and how it simplifies working with graph data. We also dive into the technical challenges of implementing SQL Property Graph Queries (SQL PGQ) in DuckDB, discuss performance benchmarks, and explore the future of DuckPGQ in graph analytics and machine learning. Tune in to learn how this cutting-edge extension is bridging the gap betwe...
2025-03-2048 min
Disseminate: The Computer Science Research PodcastTill Döhmen | DuckDQ: A Python library for data quality checks in ML pipelinesIn this episode we kick off our DuckDB in Research series with Till Döhmen, a software engineer at MotherDuck, where he leads AI efforts. Till shares insights into DuckDQ, a Python library designed for efficient data quality validation in machine learning pipelines, leveraging DuckDB’s high-performance querying capabilities.We discuss the challenges of ensuring data integrity in ML workflows, the inefficiencies of existing solutions, and how DuckDQ provides a lightweight, drop-in replacement that seamlessly integrates with scikit-learn. Till also reflects on his research journey, the impact of DuckDB’s optimizations, and the future potential of data...
2025-03-1358 min
Disseminate: The Computer Science Research PodcastDisseminate x DuckDB Coming Soon...Hey folks! We have been collaborating with everyone's favourite in-process SQL OLAP database management system DuckDB to bring you a new podcast series - the DuckDB in Research series!At Disseminate our mission is to bridge the gap between research and industry by exploring research that has a real-world impact. DuckDB embodies this synergy—decades of research underpin its design, and now it’s making waves in the research community as a platform for others to build on and this is what the series will focus on! Join us as we k...
2025-03-0602 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... Anastasia AilamakiIn this High Impact in Databases episode we talk to Anastasia Ailamaki.Anastasia is a Professor of Computer and Communication Sciences at the École Polytechnique Fédérale de Lausanne (EPFL). Tune in to hear Anastasia's story! The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust.You can find Anastasia on:HomepageGoogle ScholarLinkedIn Hosted on Acast. See acast.com/privacy for more information.
2025-03-0346 min
Disseminate: The Computer Science Research PodcastAnastasiia Kozar | Fault Tolerance Placement in the Internet of Things | #61In this episode, we chat with Anastasiia Kozar about her research on fault tolerance in resource-constrained environments. As IoT applications leverage sensors, edge devices, and cloud infrastructure, ensuring system reliability at the edge poses unique challenges. Unlike the cloud, edge devices operate without persistent backups or high availability standards, leading to increased vulnerability to failures. Anastasiia explains how traditional methods fall short, as they fail to align resource allocation with fault tolerance needs, often resulting in system underperformance.To address this, Anastasiia introduces a novel resource-aware approach that combines operator placement and fault tolerance into a...
2024-12-1649 min
Disseminate: The Computer Science Research PodcastLiana Patel | ACORN: Performant and Predicate-Agnostic Hybrid Search | #60In this episode, we chat with with Liana Patel to discuss ACORN, a groundbreaking method for hybrid search in applications using mixed-modality data. As more systems require simultaneous access to embedded images, text, video, and structured data, traditional search methods struggle to maintain efficiency and flexibility. Liana explains how ACORN, leveraging Hierarchical Navigable Small Worlds (HNSW), enables efficient, predicate-agnostic searches by introducing innovative predicate subgraph traversal. This allows ACORN to outperform existing methods significantly, supporting complex query semantics and achieving 2–1,000 times higher throughput on diverse datasets. Tune in to learn more!Links:ACORN: Performant and Pr...
2024-11-1152 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... David MaierIn this High Impact episode we talk to David Maier.David is the Maseeh Professor Emeritus of Emerging Technologies at Portland State University. Tune in to hear David's story and learn about some of his most impactful work.The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust.You can find David on:HomepageGoogle Scholar Hosted on Acast. See acast.com/privacy for more information.
2024-11-041h 02
Disseminate: The Computer Science Research PodcastRaunak Shah | R2D2: Reducing Redundancy and Duplication in Data Lakes | #59In this episode, Raunak Shah joins us to discuss the critical issue of data redundancy in enterprise data lakes, which can lead to soaring storage and maintenance costs. Raunak highlights how large-scale data environments, ranging from terabytes to petabytes, often contain duplicate and redundant datasets that are difficult to manage. He introduces the concept of "dataset containment" and explains its significance in identifying and reducing redundancy at the table level in these massive data lakes—an area where there has been little prior work.Raunak then dives into the details of R2D2, a novel three-step hi...
2024-10-2831 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... Aditya ParameswaranIn this High Impact episode we talk to Aditya Parameswaran about his some of his most impactful work.Aditya is an Associate Professor at the University of California, Berkeley. Tune in to hear Aditya's story! The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust.Links:EPIC Data LabAnswering Queries using Humans, Algorithms and Databases (CIDR'11)Potter’s Wheel: An Interactive Data Cleaning System (VLDB'01)Online Aggregation (SIGMOD'97)Polaris: A System for Query, Analysis and Visualization of Mu...
2024-10-2158 min
Disseminate: The Computer Science Research PodcastMarco Costa | Taming Adversarial Queries with Optimal Range Filters | #58In this episode, we sit down with Marco Costa to discuss the fascinating world of range filters, focusing on how they help optimize queries in databases by determining whether a range intersects with a given set of keys. Marco explains how traditional range filters, like Bloom filters, often result in high false positives and slow query times, especially when dealing with adversarial inputs where queries are correlated with the keys. He walks us through the limitations of existing heuristic-based solutions and the common challenges they face in maintaining accuracy and speed under such conditions.The highlight...
2024-10-1437 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... Ali DasdanIn this High Impact episode we talk to Ali Dasdan, CTO at Zoominfo. Tune in to hear Ali's story and learn about some of his most impactful work such as his work on "Map-Reduce-Merge".The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust.Materials mentioned on this episode:Map-Reduce-Merge: Simplified Relational Data Processing on Large Clusters (SIGMOD'07)The Art of Doing Science and Engineering: Learning to Learn, Richard HammingHow to Solve It, George PolyaSystems Architecting: Creating & Building Complex Systems...
2024-10-081h 03
Disseminate: The Computer Science Research PodcastMatt Perron | Analytical Workload Cost and Performance Stability With Elastic Pools | #57In this episode, we dive deep into the complexities of managing analytical query workloads with our guest, Matt Perron. Matt explains how the rapid and unpredictable fluctuations in resource demands present a significant challenge for provisioning. Traditional methods often lead to either over-provisioning, resulting in excessive costs, or under-provisioning, which causes poor query latency during demand spikes. However, there's a promising solution on the horizon. Matt shares insights from recent research that showcases the viability of using cloud functions to dynamically match compute supply with workload demand without the need for prior resource provisioning. While effective for low query...
2024-07-2252 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... Andreas KipfIn this High Impact episode we talk to Andreas Kipf about his work on "Learned Cardinalities". Andreas is the Professor of Data Systems at Technische Universität Nürnberg (UTN). Tune in to hear Andreas's story and learn about some of his most impactful work.The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust.Papers mentioned on this episode:Learned Cardinalities: Estimating Correlated Joins with Deep Learning CIDR'19The Case for Learned Index Structures SIGMOD'18Adaptive Op...
2024-07-1553 min
Disseminate: The Computer Science Research PodcastMarvin Wyrich & Justus Bogner | How Software Engineering Research Is Discussed on LinkedIn | #56In this episode, we delve into the intersection of software engineering (SE) research and professional practice with experts Marvin Wyrich and Justus Bogner. As LinkedIn stands as the largest professional network globally, it serves as a critical platform for bridging the gap between SE researchers and practitioners. Marvin and Justus explore the dynamics of how research findings are shared and discussed on LinkedIn, providing both quantitative and qualitative insights into the effectiveness of these interactions. They reveal that a significant portion of SE research posts on LinkedIn are authored by individuals outside the original research team and that a...
2024-07-0847 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... Joe HellersteinIn this High Impact episode we talk to Joe Hellerstein.Joe is the Jim Gray Professor of Computer Science at UC Berkeley. Tune in to hear Joe's story and learn about some of his most impactful work.The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust. Hosted on Acast. See acast.com/privacy for more information.
2024-07-0152 min
Disseminate: The Computer Science Research PodcastHarry Goldstein | Property-Based Testing | #55In this episode, we chat with Harry Goldstein about Property-Based Testing (PBT). Harry shares insights from interviews with PBT users at Jane Street, highlighting PBT's strengths in testing complex code and boosting developer confidence. Harry also discusses the challenges of writing properties and generating random data, and the difficulties in assessing test effectiveness. He identifies key areas for future improvement, such as performance enhancements and better random input generation. This episode is essential for those interested in the latest developments in software testing and PBT's future.Links:ICSE'24 Paper Harry's websiteX: @hgoldstein95 ...
2024-06-2549 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... Raghu RamakrishnanIn this High Impact episode we talk to Raghu Ramakrishnan.Raghu is CTO for Data and a Technical Fellow at Microsoft. Tune in to hear Raghu's story and learn about some of his most impactful work.The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust. Hosted on Acast. See acast.com/privacy for more information.
2024-06-1723 min
Disseminate: The Computer Science Research PodcastGina Yuan | In-Network Assistance With Sidekick Protocols | #54Join us as we chat with Gina Yuan about her pioneering work on sidekick protocols, designed to enhance the performance of encrypted transport protocols like QUIC and WebRTC. These protocols ensure privacy but limit in-network innovations. Gina explains how sidekick protocols allow intermediaries to assist endpoints without compromising encryption.Discover how Gina tackles the challenge of referencing opaque packets with her innovative quACK tool and learn about the real-world benefits, including improved Wi-Fi retransmissions, energy-saving proxy acknowledgments, and the PACUBIC congestion-control mechanism. This episode offers a glimpse into the future of network performance and security.
2024-06-1055 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... Moshe VardiWelcome to another episode of the High Impact series - today we talk with Moshe Vardi! Moshe is the Karen George Distinguished Service Professor in Computational Engineering at Rice University where his research focuses on automated reasoning. Tune in to hear Moshe's story and learn about some of his most impactful work.The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust.You can find Moshe on X, LinkedIn, and Mastadon @vardi. Links to all his work can...
2024-06-0347 min
Disseminate: The Computer Science Research PodcastTammy Sukprasert | Move Your Workloads To Sweden! | #53In this episode, we dip our toes into the world of sustainable computing and interview Tammy Sukprasert about her research on reducing carbon emissions in cloud computing through workload scheduling. Tammy explores the concept of shifting cloud workloads across different times and locations to coincide with low-carbon energy availability. Unlike previous studies that focused on specific regions or workloads, her comprehensive analysis uses carbon intensity data from 123 regions to assess both batch and interactive workloads. She considers various factors such as job duration, deadlines, and service level objectives (SLOs). Tammy's findings reveal that while spatiotemporal workload shifting can reduce...
2024-05-2732 min
Disseminate: The Computer Science Research PodcastHigh Impact in Databases with... Ryan MarcusWelcome to the first episode of the High Impact series!The High Impact series is inspired by a blog post “Most Influential Database Papers" by Ryan Marcus and today we talk to Ryan! Tune in to hear about Ryan's story so far. We chat about his current work before moving on to discuss his most impactful work. We also dig into what motivates him and how he handles setbacks, as well as getting his take on the current trends.The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source te...
2024-05-2059 min
Disseminate: The Computer Science Research PodcastYazhuo Zhang | SIEVE is Simpler than LRU | #52In this episode, we explore the world of caching with Yazhuo Zhang, who introduces the game-changing SIEVE algorithm. Traditional eviction algorithms have long struggled with a trade-off between efficiency, throughput, and simplicity. However, SIEVE disrupts this balance by offering a simpler alternative to LRU while outperforming state-of-the-art algorithms in both efficiency and scalability for web cache workloads. Implemented in five production cache libraries with minimal code changes, SIEVE's superiority shines through in a comprehensive evaluation across 1559 cache traces. With up to a remarkable 63.2% lower miss ratio than ARC and surpassing nine other algorithms in over 45% of cases, SIEVE's simplicity...
2024-05-1343 min
Disseminate: The Computer Science Research PodcastIntroducing the High Impact Series...Introducing the High Impact Series! Hey folks, we have a new series coming soon inspired by a blog post “Most Influential Database Papers" by Ryan Marcus. The series will feature interviews with the authors of some of the most impactful work in the field of databases. We will talk about the story behind some of their most impactful work, getting them to reflect on the impact it has had over years, as well as getting their take on the current trends in the field. Proudly sponsored by Pometry Hosted on Acast. Se...
2024-05-0602 min
Disseminate: The Computer Science Research PodcastEleni Zapridou | Oligolithic Cross-task Optimizations across Isolated Workloads | #51In this episode, we talk to Eleni Zapridou and delve into the challenges of data processing within enterprises, where multiple applications operate concurrently on shared resources. Traditional resource boundaries between applications often lead to increased costs and resource consumption. However, as Eleni explains the principle of functional isolation offers a solution by combining cross-task optimizations with performance isolation. We explore GroupShare, an innovative strategy that reduces CPU consumption and query latency, transforming data processing efficiency. Join us as we discuss the implications of functional isolation with Eleni and its potential to revolutionize enterprise data processing.
2024-04-2938 min
Disseminate: The Computer Science Research PodcastPat Helland | Scalable OLTP in the Cloud: What’s the BIG DEAL? | #50In this thought-provoking podcast episode, we dive into the world of scalable OLTP (OnLine Transaction Processing) systems with the insightful Pat Helland. As a seasoned expert in the field, Pat shares his insights on the critical role of isolation semantics in the scalability of OLTP systems, emphasizing its significance as the "BIG DEAL." By examining the interface between OLTP databases and applications, particularly through the lens of RCSI (READ COMMITTED SNAPSHOT ISOLATION) SQL databases, Pat talks about the limitations imposed by current database architectures and application patterns on scalability.Through a compelling thought experiment, Pat explores...
2024-04-151h 20
Disseminate: The Computer Science Research PodcastRui Liu | Towards Resource-adaptive Query Execution in Cloud Native Databases | #49In this episode, we talk to Rui Liu and explore the transformative potential of Ratchet, a groundbreaking resource-adaptive query execution framework. We delve into the challenges posed by ephemeral resources in modern cloud environments and the innovative solutions offered by Ratchet. Rui guides us through the intricacies of Ratchet's design, highlighting its ability to enable adaptive query suspension and resumption, sophisticated resource arbitration for diverse workloads, and a fine-grained pricing model to navigate fluctuating resource availability. Join us as we uncover the future of cloud-native databases and workloads, and discover how Ratchet is poised to revolutionize the way we...
2024-04-0153 min
Disseminate: The Computer Science Research PodcastYifei Yang | Predicate Transfer: Efficient Pre-Filtering on Multi-Join Queries | #48In this episode, Yifei Yang introduces predicate transfer, a revolutionary method for optimizing join performance in databases. Predicate transfer builds on Bloom joins, extending its benefits to multi-table joins. Inspired by Yannakakis's theoretical insights, predicate transfer leverages Bloom filters to achieve significant speed improvements. Yang's evaluation shows an average 3.3× performance boost over Bloom join on the TPC-H benchmark, highlighting the potential of predicate transfer to revolutionize database query optimization. Join us as we explore the transformative impact of predicate transfer on database operations.Links:CIDR'24 PaperYifei's LinkedInBuy Me A CoffeeListener Survey Hosted on Acast. S...
2024-03-1847 min
Disseminate: The Computer Science Research PodcastVikramank Singh | Panda: Performance Debugging for Databases using LLM Agents | #47In this episode, Vikramank Singh introduces the Panda framework, aimed at refining Large Language Models' (LLMs) capability to address database performance issues. Vikramank elaborates on Panda's four components—Grounding, Verification, Affordance, and Feedback—illustrating how they collaborate to contextualize LLM responses and deliver actionable recommendations. By bridging the divide between technical knowledge and practical troubleshooting needs, Panda has the potential to revolutionize database debugging practices, offering a promising avenue for more effective and efficient resolution of performance challenges in database systems. Tune in to learn more! Links:CIDR'24 PaperVikramank's LinkedIn Hosted on Acast. See acas...
2024-03-041h 08
Disseminate: The Computer Science Research PodcastTamer Eldeeb | Chablis: Fast and General Transactions in Geo-Distributed Systems | #46In this episode, Tamer Eldeeb sheds light on the challenges faced by geo-distributed database management systems (DBMSes) in supporting strictly-serializable transactions across multiple regions. He discusses the compromises often made between low-latency regional writes and restricted programming models in existing DBMS solutions. Tamer introduces Chablis, a groundbreaking geo-distributed, multi-versioned transactional key-value store designed to overcome these limitations.Chablis offers a general interface accommodating range and point reads, along with writes within multi-step strictly-serializable ACID transactions. Leveraging advancements in low-latency datacenter networks and innovative DBMS designs, Chablis eliminates the need for compromises, ensuring fast read-write transactions with low...
2024-02-121h 02
Disseminate: The Computer Science Research PodcastMatt Butrovich | Tigger: A Database Proxy That Bounces With User-Bypass | #45Summary: In this episode, we chat to Matt Butrovich about his research on database proxies. We discuss the inefficiencies of traditional database proxies, which operate in user-space, causing overhead due to buffer copying and system calls. Matt introduces "user-bypass" which leverages Linux's eBPF infrastructure to move application logic into kernel-space. Matt then tells us about Tigger, a PostgreSQL-compatible DBMS proxy, showcasing user-bypass benefits. Tune in to hear about the experiments that demonstrate how Tigger can achieve up to a 29% reduction in transaction latencies and a 42% reduction in CPU utilization compared to other widely-used proxies.
2023-12-181h 03
Disseminate: The Computer Science Research PodcastGábor Szárnyas | The LDBC Social Network Benchmark: Business Intelligence Workload | #44Summary: In this episode, Gábor Szárnyas takes us on a journey through the LDBC Social Network Benchmark's Business Intelligence workload (SNB BI). Developed through collaboration between academia and industry the SNB BI is a comprehensive graph OLAP benchmark. It pushes the boundaries of synthetic and scalable analytical database benchmarks, featuring a sophisticated data generator and a temporal graph with small-world phenomena. The benchmark's query workload, rooted in LDBC's innovative design methodology, aims to drive future technical advancements in graph database systems. Gabor highlights SNB BI's unique features, including the adoption of "parameter curation" for stable qu...
2023-12-0446 min
Disseminate: The Computer Science Research PodcastThaleia Doudali | Is Machine Learning Necessary for Cloud Resource Usage Forecasting? | #43Summary:In this week's episode, we talk with Thaleia Doudali and explore the realm of cloud resource forecasting, focusing on the use of Long Short Term Memory (LSTM) neural networks, a popular machine learning model. Drawing from her research, Thaleia discusses the surprising discovery that, despite the complexity of ML models, accurate predictions often boil down to a simple shift of values by one time step. The discussion explores the nuances of time series data, encompassing resource metrics like CPU, memory, network, and disk I/O across different cloud providers and levels. Thaleia highlights...
2023-11-2049 min
Disseminate: The Computer Science Research PodcastJinkun Geng | Nezha: Deployable and High-Performance Consensus Using Synchronized Clocks | #42Summary: In this episode Jinkun Geng talks to us about Nezha, a high-performance consensus protocol. Nezha can be deployed by cloud tenants without support from cloud providers. Nezha bridges the gap between protocols such as MultiPaxos and Raft, which can be readily deployed, and protocols such as NOPaxos and Speculative Paxos, that provide better performance, but require access to technologies such as programmable switches and in-network prioritization, which cloud tenants do not have. Tune in to learn more! Links: Jinkun's HomepageNezha VLDB'23 PaperNezha GitLab Repo Hosted on Acast. See acast...
2023-10-2355 min
Disseminate: The Computer Science Research PodcastDimitris Koutsoukos | NVM: Is it Not Very Meaningful for Databases? | #41Summary: In this episode, Dimitris Koutsoukos talks to us about Persistent or Non Volatile Memory (PMEM) and we answer the question: Is it Not Very Meaningful for Databases? PMEM offers expanded memory capacity and faster access to persistent storage. However, (before Dimitris's work) there was no comprehensive empirical analysis of existing database engines under diferent PMEM modes, to understand how databases can benefit from the various hardware configurations. Dimitris and his colleagues have then analyzes multiple diferent engines under common benchmarks with PMEM in AppDirect mode and Memory mode - tune in to h...
2023-10-0948 min
Disseminate: The Computer Science Research PodcastMohamed Alzayat | Groundhog: Efficient Request Isolation in FaaS | #40Summary:Security is a core responsibility for Function-as-a-Service (FaaS) providers. The prevailing approach has each function execute in its own container to isolate concurrent executions of different functions. However, successive invocations of the same function commonly reuse the runtime state of a previous invocation in order to avoid container cold-start delays when invoking a function. Although efficient, this container reuse has security implications for functions that are invoked on behalf of differently privileged users or administrative domains: bugs in a function’s implementation, third-party library, or the language runtime may leak private data from on...
2023-09-1142 min
Disseminate: The Computer Science Research PodcastCuong Nguyen | Detock: High Performance Multi-region Transactions at Scale | #39Summary: In this episode Cuong Nguyen tells us about Detock, a geographically replicated database system. Tune in to learn about its specialised concurrency control and deadlock resolution protocols that enable processing strictly-serializable multi-region transactions with near-zero performance degradation at extremely high conflict and improves latency by up to a factor of 5.Links: SIGMOD PaperDetock Github RepoCuong's Homepage Hosted on Acast. See acast.com/privacy for more information.
2023-08-2837 min
Disseminate: The Computer Science Research PodcastBogdan Stoica | WAFFLE: Exposing Memory Ordering Bugs Efficiently with Active Delay Injection | #38Concurrency bugs are difficult to detect, reproduce, and diagnose, as they manifest under rare timing conditions. Recently, active delay injection has proven efficient for exposing one such type of bug — thread-safety violations — with low over-head, high coverage, and minimal code analysis. However, how to efficiently apply active delay injection to broader classes of concurrency bugs is still an open question.In this episode, Bogdan Stoica tells us about how answered this question by focusing on MemOrder bugs — a type of concurrency bug caused by incorrect timing between a memory access to a particular object and the object’s initi...
2023-08-1455 min
Disseminate: The Computer Science Research PodcastRoger Waleffe | MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks | #37Summary: In this episode, Roger Waleffe talks about Graph Neural Networks (GNNs) for large-scale graphs. Specifically, he reveals all about MariusGNN, the first system that utilises the entire storage hierarchy (including disk) for GNN training. Tune in to find out how MaruisGNN works and just how fast it goes (and how much more cost-efficient it is!) Links: Marius ProjectRoger's Homepage Roger's TwitterEuroSys'23 PaperSupport the podcast through Buy Me a Coffee Hosted on Acast. See acast.com/privacy for more information.
2023-07-311h 13
Disseminate: The Computer Science Research PodcastMadelon Hulsebos | GitTables: A Large-Scale Corpus of Relational Tables | #36Summary:The success of deep learning has sparked interest in improving relational table tasks, like data preparation and search, with table representation models trained on large table corpora. Existing table corpora primarily contain tables extracted from HTML pages, limiting the capability to represent offline database tables. To train and evaluate high-capacity models for applications beyond the Web, we need resources with tables that resemble relational database tables. In this episode, Madelon Hulsebos tells us all about such a resource! Tune in to learn more about GitTables!! Links: Madelon's websiteGitTables homepageSIGMOD'23 paper
2023-07-1745 min
Disseminate: The Computer Science Research PodcastTarikul Islam Papon | ACEing the Bufferpool Management Paradigm for Modern Storage Devices | #35Summary:Compared to hard disk drives (HDDs), solid-state drives (SSDs) have two fundamentally different properties: (i) read/write asymmetry (writes are slower than reads) and (ii) access concurrency (multiple I/Os can be executed in parallel to saturate the device bandwidth). But, database operators are often designed without considering storage asymmetry and concurrency resulting in device under utilization. In thie episode, Tarikul Islam Papon tells us about his work on a new Asymmetry & Concurrency aware bufferpool management (ACE) that batches writes based on device concurrency and performs them in parallel to amortize the asymmetric write cost. Tune...
2023-06-2047 minDisseminate: The Computer Science Research PodcastJian Zhang | VIPER: A Fast Snapshot Isolation Checker | #34Summary:Snapshot isolation is supported by most commercial databases and is widely used by applications. However, checking, if given a set of transactions, a database ensures Snapshot Isolation is either slow or gives up soundness. In this episode, Jian Zhang tells us about VIPER, an SI checker that is sound, complete, and fast. Tune in to learn more!! Links:PaperGitHub repoJian's homepage Hosted on Acast. See acast.com/privacy for more information.
2023-06-0942 minDisseminate: The Computer Science Research PodcastAhmed Sayed | REFL: Resource Efficient Federated Learning | #33Summary: Federated Learning (FL) enables distributed training by learners using local data, thereby enhancing privacy and reducing communication. However, it presents numerous challenges relating to the heterogeneity of the data distribution, device capabilities, and participant availability as deployments scale, which can impact both model convergence and bias. Existing FL schemes use random participant selection to improve fairness; however, this can result in inefficient use of resources and lower quality training. In this episode, Ahmed Sayed talks about how he and his colleagues address the question of resource efficiency in FL. He talks about the...
2023-05-2658 minDisseminate: The Computer Science Research PodcastSubhadeep Sarkar | Log-structured Merge Trees | #32Summary:Log-structured merge (LSM) trees have emerged as one of the most commonly used storage-based data structures in modern data systems as they offer high throughput for writes and good utilization of storage space. In this episode, Subhadeep Sarkar presents the fundamental principles of the LSM paradigm. He tells us about recent research on improving write performance and the various optimization techniques and hybrid designs adopted by LSM engines to accelerate reads. Tune in to find out more! Links:Personal websiteICDE'23 tutorialLinkedIn Hosted on Acast. See acast.com/privacy for...
2023-05-1159 minDisseminate: The Computer Science Research PodcastAndra Ionescu | Topio: The Geodata Marketplace | #31Summary: The increasing need for data trading across businesses nowadays has created a demand for data marketplaces. However, despite the intentions of both data providers and consumers, today’s data marketplaces remain mere data catalogs. In this episode, Andra tells us about her vision for marketplaces of the future which require a set of value-added services, such as advanced search and discovery. Also, she tell us about her and her team's effort to engineer and develop an open-source modular data market platform to enable both entrepreneurs and researchers to setup and experiment with data marketplaces. Tune in to...
2023-04-2546 minDisseminate: The Computer Science Research PodcastLaurens Kuiper | These Rows Are Made For Sorting | #30Summary: Sorting is one of the most well-studied problems in computer science and a vital operation for relational database systems. Despite this, little research has been published on implementing an efficient relational sorting operator. In this episode, Laurens Kuiper tells us about his work filling this gap! Tune in to hear about a micro-benchmarks that explores how to sort relational data efficiently for analytical database systems, taking into account different query execution engines as well as row and columnar data formats. Laurens also tells us about his implementation of a highly optimized row-based sorting approach in the...
2023-04-1255 minDisseminate: The Computer Science Research PodcastSemih Salihoğlu | Kùzu Graph Database Management System | #29Summary: In this episode Semih Salihoğlu tell us about Kùzu, an in-process property graph database management system built for query speed and scalability.Listen to hear the vision for Kùzu and to learn more about Kùzu's factorized query processor! Links:Kùzu GitHub repoCIDR papercontact@kuzudb.com Kùzu SlackKùzu TwitterKùzu Website - blog posts Semih mentioned can be found hereSemih's HomepageSemih's Twitter Hosted on Acast. See acast.com/privacy for more information.
2023-04-031h 17Disseminate: The Computer Science Research PodcastLukas Vogel | Data Pipes: Declarative Control over Data Movement | #28Summary:Today’s storage landscape offers a deep and heterogeneous stack of technologies that promises to meet even the most demanding data intensive workload needs. The diversity of technologies, however, presents a challenge. Parts of it are not controlled directly by the application, e.g., the cache layers, and the parts that are controlled, often require the programmer to deal with very different transfer mechanisms, such as disk and network APIs. Combining these different abstractions properly requires great skill, and even so, expert-written programs can lead to sub-optimal utilization of the storage stack and present performance unpredictability. In...
2023-03-2850 minDisseminate: The Computer Science Research PodcastHaralampos Gavriilidis | In-Situ Cross-Database Query Processing | #27Summary:Today’s organizations utilize a plethora of heterogeneous and autonomous DBMSes, many of those being spread across different geo-locations. It is therefore crucial to have effective and efficient cross-database query processing capabilities. In this episode, Haralampos Gavriilidis tell us about XDB, an efficient middleware system that runs cross database analytics over existing DBMSes. Tune in to learn more!Links:PreprintHaralampos's homepageSupport the podcast here! Hosted on Acast. See acast.com/privacy for more information.
2023-03-201h 00Disseminate: The Computer Science Research PodcastParas Jain & Sarah Wooders | Skyplane: Fast Data Transfers Between Any Cloud | #26Summary:This week Paras Jain and Sarah Wooders tell us about how you can quickly data transfers between any cloud with Skyplane. Tune in to learn more! Links:Skyplane homepageSarah's homepageParas's homepageSupport the podcast here Hosted on Acast. See acast.com/privacy for more information.
2023-03-1346 min
Disseminate: The Computer Science Research PodcastYang Wang | Rethinking Concurrency Control in Databases | #25Summary: Many database applications execute transactions under a weaker isolation level, such as READ COMMITTED. This often leads to concurrency bugs that look like race conditions in multi-threaded programs. While this problem is well known, philosophies of how to address this problem vary a lot, ranging from making a SERIALIZABLE database faster to living with weaker isolation and the consequence of concurrency bugs. In this episode, Yang talks about the consequences of these bugs, the root causes, and how developers have fixed 93 real-world concurrency bugs in database applications. Who's responsibility is it to prevent these bugs from...
2023-03-0655 min
Disseminate: The Computer Science Research PodcastSuyash Gupta | Chemistry behind Agreement | #24Summary: Agreement protocols have been extensively used by distributed data management systems to provide robustness and high availability. The broad spectrum of design dimensions, applications, and fault models have resulted in different flavours of agreement protocols. This has made it hard to argue their correctness and has unintentionally created a disparity in understanding their design. In this episode, Suyash Gupta tell us about a unified framework that simplifies expressing different agreement protocols. Listen to find out more! Links: PaperWebsiteTwitter Hosted on Acast. See acast.com/privacy for more information.
2023-02-271h 03
Disseminate: The Computer Science Research PodcastTobias Ziegler | Is Scalable OLTP in the Cloud a Solved Problem? | #23Summary: Many distributed cloud OLTP databases have settled on a shared-storage design coupled with a single-writer. This design choice is remarkable since conventional wisdom promotes using a shared-nothing architecture for building scalable systems. In this episode, Tobias revisits the question of what a scalable OLTP design for the cloud should look like by analysing the data access behaviour of different systems. Tune in to find out more!Links: PaperWebsiteEmail TwitterGoogle Scholar Hosted on Acast. See acast.com/privacy for more information.
2023-02-2055 min
Disseminate: The Computer Science Research PodcastHamish Nicholson | HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics | #22Summary:In this episode, Hamish Nicholson tells us about HetCache, a storage engine for analytical workloads that optimizes the data access paths and tunes data placement by co-optimizing for the combinations of different memories, compute devices, and queries. Specifically, we present how the increasingly complex storage hierarchy impacts analytical query processing in GPU-NVMe-accelerated servers. HetCache accelerates analytics on CPU-GPU servers for larger-than-memory datasets through proportional and access-path-aware data placement. Tune in to hear more!Links:PaperPersonal websiteLinkedInTwitter Hosted on Acast. See acast.com/privacy for more information.
2023-02-1350 min
Disseminate: The Computer Science Research PodcastImmanuel Haffner | mutable: A Modern DBMS for Research and Fast Prototyping | #21Summary:Few to zero DBMSs provide extensibility together with implementations of modern concepts, like query compilation for example. This as an impeding factor in academic research. In this episode, Immanuel Haffner, presents mutable, a system that is fitted to academic research and education. mutable features a modular design, where individual components can be composed to form a complete system. Check out the episode to learn more!Links:PaperWebsiteMutable github repoBobby Tables xkcd Hosted on Acast. See acast.com/privacy for more information.
2023-02-061h 28
Disseminate: The Computer Science Research PodcastKonstantinos Kallas | Practically Correct, Just-in-Time Shell Script Parallelization | #20Summary: Recent shell-script parallelization systems enjoy mostly automated speedups by parallelizing scripts ahead-of-time. Unfortunately, such static parallelization is hampered by dynamic behavior pervasive in shell scripts—e.g., variable expansion and command substitution—which often requires reasoning about the current state of the shell and filesystem. Tune in to hear how Konstantinos Kallas and his colleagues overcame this issue (and others) with PaSH-JIT, a just-in-time (JIT) shell-script compiler!Links: OSDI paperPersonal websiteTwitterLinkedInPaSH homepage (you can find all associated papers here) Hosted on Acast. See acast.com/privacy for...
2023-01-3057 min
Disseminate: The Computer Science Research PodcastVasily Sartakov | CAP-VMs: Capability-Based Isolation and Sharing in the Cloud #19Summary: Cloud stacks must isolate application components, while permitting efficient data sharing between components deployed on the same physical host. Traditionally, the memory management unit (MMU) enforces isolation and permits sharing at page granularity. MMU approaches, however, lead to cloud stacks with large trusted computing bases in kernel space, and page granularity requires inefficient OS interfaces for data sharing. Forthcoming CPUs with hardware support for memory capabilities offer new opportunities to implement isolation and sharing at a finer granularity. In this episode, Vasily talks about his work on cVMs, a new VM-like abstraction that uses memory capabilities to...
2023-01-2336 min
Disseminate: The Computer Science Research PodcastHaoran Ma | MemLiner: Lining up Tracing and Application for a Far-Memory-Friendly Runtime | #18Summary: Far-memory techniques that enable applications to use remote memory and are increasingly appealing in modern data centers, supporting applications’ large memory footprint and improving machines’ resource utilization. In this episode Haoran Ma tells us about the problems with current far-memory techniques and how they focus on OS-level optimizations and are agnostic to managed runtimes and garbage collections (GC) underneath applications written in high-level languages. Owing to different object-access patterns from applications, GC can severely interfere with existing far-memory techniques, breaking remote memory prefetching algorithms and causing severe local-memory misses. To address this Haoran and his colleagues deve...
2023-01-1644 min
Disseminate: The Computer Science Research PodcastLexiang Huang | Metastable Failures in the Wild | #17Summary: In this episode Lexiang Huang talks about a framework for understanding a class of failures in distributed systems called metastable failures. Lexiang tells us about his study on the prevalence of such failures in the wild and how he and his colleagues scoured over publicly available incident reports from many organizations, ranging from hyperscalers to small companies. Listen to the episode to find out about his main findings and gain a deeper understanding of metastable failures and how you can identity, prevent, and mitigate against them!Links: OSDI paper and t...
2023-01-0953 min
Disseminate: The Computer Science Research PodcastAndrew Quinn | Debugging the OmniTable Way | #16Summary: Debugging is time-consuming, accounting for roughly 50% of a developer's time. In this episode Andrew Quinn tells us about the OmniTable, an abstraction that captures all execution state as a large queryable data table. In his research Andrew has built a query model around an OmniTable that supports SQL to simplify debugging. An OmniTable decouples debugging logic from the original execution, which SteamDrill, Andrew's prototype, uses to reduce the performance overhead of debugging (SteamDrill queries are an order-of-magnitude faster than existing debugging tools). Links: Andrew's HomepageDebugging the OmniTable Way OSDI'22...
2023-01-0257 min
Disseminate: The Computer Science Research PodcastAudrey Cheng | TAOBench: An End-to-End Benchmark for Social Network Workloads | #15Summary: This episode features Audrey Cheng talking about TAOBench, a new benchmark that captures the social graph workload at Meta. Audrey tells us about the features of workload, how it compares with other benchmarks, and how it fills a gap in the existing space of benchmark. Also, we hear all about the fantastic real-world impact the benchmark has already had across a range of companies. Links:PaperPersonal websiteMeta blog postGitHub repo Hosted on Acast. See acast.com/privacy for more information.
2022-12-1252 min
Disseminate: The Computer Science Research PodcastGeorge Konstantinidis | Enabling Personal Consent in Databases | #14Summary: Users have the right to consent to the use of their data, but current methods are limited to very coarse-grained expressions of consent, as “opt-in/opt-out” choices for certain uses. In this episode, George talks about how he and his group identified the need for fine-grained consent management and how they formalized how to express and manage user consent and personal contracts of data usage in relational databases. Their approach enables data owners to express the intended data usage in formal specifications, called consent constraints, and enables a service provider that wants to honor these constraints, to a...
2022-12-0555 min
Disseminate: The Computer Science Research PodcastPer Fuchs | Sortledton: a Universal, Transactional Graph Data Structure | #13Summary (VLDB abstract):Despite the wide adoption of graph processing across many different application domains, there is no underlying data structure that can serve a variety of graph workloads (analytics, traversals, and pattern matching) on dynamic graphs with transactional updates. In this episode, Per talks about Sortledton, a universal graph data structure that addresses the open problem by being carefully optimizing for the most relevant data access patterns used by graph computation kernels. It can support millions of transactional updates per second, while providing competitive performance (1.22x on average) for the most common graph...
2022-11-2841 min
Disseminate: The Computer Science Research PodcastGeorge Theodorakis | Scabbard: Single-Node Fault-Tolerant Stream Processing | #12Summary (VLDB abstract):Single-node multi-core stream processing engines (SPEs) can process hundreds of millions of tuples per second. Yet making them fault-tolerant with exactly-once semantics while retaining this performance is an open challenge: due to the limited I/O bandwidth of a single-node, it becomes infeasible to persist all stream data and operator state during execution. Instead, single-node SPEs rely on upstream distributed systems, such as Apache Kafka, to recover stream data after failure, necessitating complex clusterbased deployments. This lack of built-in fault-tolerance features has hindered the adoption of single-node SPEs. We describe Scabbard, the frst single-node...
2022-11-2145 min
Disseminate: The Computer Science Research PodcastKevin Gaffney | SQLite: Past, Present, and Future | #11Summary: In this episode Kevin Gaffney tells us about SQLite, the most widely deployed database engine in existence. SQLite is found in nearly every smartphone, computer, web browser, television, and automobile. Several factors are likely responsible for its ubiquity, including its in-process design, standalone codebase, extensive test suite, and cross-platform file format. While it supports complex analytical queries, SQLite is primarily designed for fast online transaction processing (OLTP), employing row-oriented execution and a B-tree storage format. However, fueled by the rise of edge computing and data science, there is a growing need for efficient in-process online analytical...
2022-11-1448 min
Disseminate: The Computer Science Research PodcastMatthias Jasny | P4DB - The Case for In-Network OLTP | #10Summary: In this episode Matthias Jasny from TU Darmstadt talks about P4DB, a database that uses a programmable switch to accelerate OLTP workloads. The main idea of P4DB is that it implements a transaction processing engine on top of a P4-programmable switch. The switch can thus act as an accelerator in the network, especially when it is used to store and process hot (contended) tuples on the switch. P4DB provides significant benefits compared to traditional DBMS architectures and can achieve a speedup of up to 8x.Questions:
2022-08-0827 min
Disseminate: The Computer Science Research PodcastTobias Ziegler | ScaleStore: A Fast and Cost-Efficient Storage Engine using DRAM, NVMe, and RDMA | #9Summary: In this episode Tobias talks about his work on ScaleStore, a distributed storage engine that exploits DRAM caching, NVMe storage, and RDMA networking to achieve high performance, cost-efficiency, and scalability. Using low latency RDMA messages, ScaleStore implements a transparent memory abstraction that provides access to the aggregated DRAM memory and NVMe storage of all nodes. In contrast to existing distributed RDMA designs such as NAM-DB or FaRM, ScaleStore stores cold data on NVMe SSDs (flash), lowering the overall hardware cost significantly. At the heart of ScaleStore is a distributed caching st...
2022-08-0123 min
Disseminate: The Computer Science Research PodcastChuzhe Tang | Ad Hoc Transactions in Web Applications: The Good, the Bad, and the Ugly | #8Summary: Many transactions in web applications are constructed ad-hoc in the application code. For example, developers might explicitly use locking primitives or validation procedures to coordinate critical code fragments. In this episode, Chuzhe tells us these ad-hoc transactions, database operations coordinated by application code.Until Chuzhe’s work, little was known about them. In this episode he chats about the first comprehensive study on ad hoc transactions. By studying 91 ad hoc transactions among 8 popular open-source web applications, he and his co-authors found that (i) every studied application uses ad hoc transactions (up to 16 per ap...
2022-07-2532 min
Disseminate: The Computer Science Research PodcastMichael Abebe | Proteus: Autonomous Adaptive Storage for Mixed Workloads | #7Summary:Enterprises use distributed database systems to meet the demands of mixed or hybrid transaction/analytical processing (HTAP) workloads that contain both transactional (OLTP) and analytical (OLAP) requests. Distributed HTAP systems typically maintain a complete copy of data in row-oriented storage format that is well-suited for OLTP workloads and a second complete copy in column-oriented storage format optimised for OLAP workloads. Maintaining these data copies consumes significant storage space and system resources. Conversely, if a system stores data in a single format, OLTP or OLAP workload performance suffers.In this interview, Michael talks about...
2022-07-1827 min
Disseminate: The Computer Science Research PodcastHani Al-Sayeh | Juggler: Autonomous Cost Optimization and Performance Prediction of Big Data Applications | #6Summary:Distributed in-memory processing frameworks accelerate iterative workloads by caching suitable datasets in memory rather than recomputing them in each iteration. Selecting appropriate datasets to cache as well as allocating a suitable cluster configuration for caching these datasets play a crucial role in achieving optimal performance. In practice, both are tedious, time-consuming tasks and are often neglected by end users, who are typically not aware of workload semantics, sizes of intermediate data, and cluster specification. To address these problems, Hani and his colleagues developed Juggler, an end-to-end framework, which autonomously selects appropriate datasets for caching and recommends...
2022-07-1132 min
Disseminate: The Computer Science Research PodcastThomas Hütter | JEDI: These aren’t the JSON documents you’re looking for | #4Summary:The JavaScript Object Notation (JSON) is a popular data format used in document stores to natively support semi-structured data.In this interview, Thomas talks about how he addressed the problem of JSON similarity lookup queries: given a query document and a distance threshold, retrieve all documents that are within the threshold from the query document, i.e., get me all similar documents!. Different from other hierarchical formats such as XML, JSON supports both ordered and unordered sibling collections within a single document which poses a new challenge to the tree model...
2022-07-0811 min
Disseminate: The Computer Science Research PodcastSainyam Galhotra | Causal Feature Selection for Algorithmic Fairness | #5Summary:The use of machine learning (ML) in high-stakes societal decisions has encouraged the consideration of fairness throughout the ML lifecycle. Although data integration is one of the primary steps to generate high-quality training data, most of the fairness literature ignores this stage. In this interview Sainyam discusses why he focuses on fairness in the integration component of data management, aiming to identify features that improve prediction without adding any bias to the dataset. Sainyam works under the causal fairness paradigm and without requiring the underlying structural causal model a priori, we has developed...
2022-07-0812 min
Disseminate: The Computer Science Research PodcastDraco Xu | TSUBASA: Climate Network Construction on Historical and Real-Time Data | #3Summary: A climate network represents the global climate system by the interactions of a set of anomaly time-series. Network science has been applied on climate data to study the dynamics of a climate network. The core task and first step to enable interactive network science on climate data is the efficient construction and update of a climate network on user-defined time-windows. In this interview Draco talks about TSUBASA, an algorithm for the efficient construction of climate networks based on the exact calculation of Pearson’s correlation of large time-series. By pre-computing simple and low-overhead st...
2022-07-0417 min
Disseminate: The Computer Science Research PodcastFelix S Campbell | Efficient Answering of Historical What-if Queries | #2Summary:In this interview Felix discusses "historical what-if queries", a novel type of what-if analysis that determines the effect of a hypothetical change to the transactional history of a database. For example, “how would revenue be affected if we would have charged an additional $6 for shipping?” In his research Felix has developed efficient techniques for answering these historical what-if queries, i.e., determining how a modified history affects the current database state. During the show, Felix talks about reenactment, a replay technique for transactional histories, and how he and his co-authors optimize this process usin...
2022-07-0119 min
Disseminate: The Computer Science Research PodcastAlex Isenko | Where Is My Training Bottleneck? Hidden Trade-Offs in Deep Learning Preprocessing Pipelines | #1Summary: Preprocessing pipelines in deep learning aim to provide sufficient data throughput to keep the training processes busy. Maximizing resource utilization is becoming more challenging as the throughput of training processes increases with hardware innovations (e.g., faster GPUs, TPUs, and inter-connects) and advanced parallelization techniques that yield better scalability. At the same time, the amount of training data needed in order to train increasingly complex models is growing. As a consequence of this development, data preprocessing and provisioning are becoming a severe bottleneck in end-to-end deep learning pipelines.In this...
2022-06-2724 min
Disseminate: The Computer Science Research PodcastComing Soon | ACM SIGMOD/PODS 2022 | #0Welcome to Disseminate! The podcast bringing you the cutting edge of Computer Science research in a digestible format. Each series will focus on papers published at a specific Computer Science conference, e.g., SIGMOD, CVPR, so we will cover a wide range of topics from distributed systems to computer vision. Each episode within a series will feature an interview with the author(s) of a paper published at that conference. The podcasts aims to be an alternative source of information for industry practitioners, researchers, and students. The podcast will be of particular use to practitioners as there will be...
2022-06-0301 min