Dremel is a scalable, interactive ad-hoc query system for analysis of read-only nested data. By combining multi-level execution trees and columnar data layout, it is capable of running aggregation queries over trillion-row tables in seconds. The system scales to thousands of CPUs and petabytes of data, and has thousands of users at Google. In this paper, we describe the architecture and implementation of Dremel, and explain how it complements MapReduce-based computing. We present a novel colu...| research.google
The API used to read files has evolved over time, from simple "full table" reads to batch reads and eventually to iterative "record batch readers". These more sophisticated APIs add additional power and flexibility. Lance takes this a step further to return a "stream of read tasks". This originates from| LanceDB Blog
Recently, I shared our plans for a new file format, Lance v2. As I'm creating a file reader for this new format I plan to create a series of posts talking about the design, challenges and limitations in many existing file readers, and how we plan to overcome these. Much| LanceDB Blog
Streaming data applications can be tricky. When you can read data faster than you can process the data then bad things tend to happen. The most common scenario is you run out of memory and your process crashes. When the process doesn't crash, it often breaks performance (e.g. swapping| LanceDB Blog
Conventional wisdom states that compression and random access do not go well together. However, there are many ways you can compress data, and some of them support random access better than others. Figuring out which compression we can use, and when, and why, has been an interesting challenge. As we've| LanceDB Blog
