Stream processing, LSMs and leaky abstractions with Chris Riccomini
Aug 23, 2024
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Chris Riccomini, an expert in stream processing and LSMs, dives into the evolution of streaming systems, highlighting the challenges developers face. He critiques SQL's limitations in this space and emphasizes the need for better API designs. The discussion also touches on the impact of Rust on usability and efficiency, particularly in embedded libraries. Chris shares insights about his exciting project involving log-structured merge trees on object storage, and the future of data systems with a focus on composable databases and the importance of metadata in AI.
Stream processing has evolved significantly, yet challenges remain in enhancing developer experience and the efficiency of production systems.
The debate over SQL in streaming systems highlights the tension between accessibility for analytics engineers and the complications of leaky abstractions.
Shifting towards object storage and modular data systems can improve scalability, durability, and operational efficiency while meeting modern application needs.
Deep dives
The Evolution of Stream Processing
Stream processing has seen significant advancements since its inception, particularly with the introduction of systems like Kafka. The speaker discusses how Kafka aimed to unify various data management practices, including log aggregation and change data capture, to enhance developer productivity within streaming environments. The goal was to simplify the complex nature of stream processing, which differs greatly from the straightforwardness of batch processing. Despite its progress, challenges still remain regarding developer experience and the efficiency of production systems utilizing stream processing.
The Debate Over SQL in Stream Processing
The conversation touches on the use of SQL in stream processing applications, revealing a divide in opinions regarding its effectiveness. While some advocate for SQL as a familiar and accessible interface for analytics engineers, others criticize it as a leaky abstraction that often complicates rather than simplifies the development process. The speaker emphasizes the need for alternative APIs that can better accommodate the requirements of developing production-level streaming applications. This highlights a persistent challenge in striking a balance between user-friendliness and robust technical functionality.
The Shift Towards Object Storage
There is a growing recognition that object storage systems offer significant advantages for modern data applications. By leveraging object storage, developers can build distributed systems that simplify data management while allowing for greater scalability. The speaker shares insights from their own projects involving log-structured merge trees, constructed specifically onto object storage. This shift not only enhances durability but also addresses latency and cost concerns, making it an appealing option for data storage solutions.
The Future of Programming with Rust
The speaker expresses enthusiasm for Rust, particularly its potential for building robust systems that integrate seamlessly across platforms. Rust's ability to compile code efficiently for various architectures positions it as a powerful tool for developers. However, the learning curve associated with Rust can be steep, and the complexities it introduces may challenge those accustomed to more straightforward programming languages. Despite these challenges, the perceived benefits of Rust, such as performance and safety, continue to drive interest and investment in the language.
Emerging Trends and Innovations in Data Systems
The discussion highlights a trend towards the decomposition of data systems into modular components, facilitating innovation and development of diverse data solutions. There is an increasing understanding that investing in metadata management and operational efficiency is essential to meet evolving business needs. Furthermore, the rise of sophisticated analytics demands a more focused approach on enriching metadata to provide context rather than simply schema definitions. As technology evolves, the integration of these varied components will likely lead to more flexible and capable data management systems.
In this episode, we chat with Chris Riccomini about the evolution of stream processing and the challenges in building applications on streaming systems. We also chat about leaky abstractions, good and bad API designs, what Chris loves and hates about Rust and finally about his exciting new project that involves object storage and LSMs.