Summary:

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:

• Preprint
• Haralampos's homepage

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Summary:

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 homepage
• Sarah's homepage
• Paras's homepage

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Summary:

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 happening? The database or the developer? Listen to find out more!

Links:

• Paper
• Homepage

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Summary:

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:

• Paper
• Website
• Twitter

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Summary:

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:

• Paper
• Website
• Email 
• Twitter
• Google Scholar

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Summary:

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:

• Paper
• Personal website
• LinkedIn
• Twitter

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Summary:

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:

• Paper
• Website
• Mutable github repo
• Bobby Tables xkcd

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Summary:

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 paper
• Personal website
• Twitter
• LinkedIn
• PaSH homepage (you can find all associated papers here)

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Summary:

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 isolate application components while supporting efficient data sharing, all without mandating application code to be capability-aware. Listen to find out more!

Links:

• OSDI Paper
• Vasily's homepage
• Vasily's LinkedIn

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Summary:

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 developed MemLiner, a runtime technique that improves the performance of far-memory systems by “lining up” memory accesses from the application and the GC so that they follow similar memory access paths, thereby (1) reducing the local-memory working set and (2) improving remote-memory prefetching through simplified memory access patterns. Listen to the episode to learn more!

Links:

• OSDI'22 MemLiner paper
• OSDI'22 Presentation
• Haoran's website

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