Angela Chang, a backend engineering intern at Cockroach Labs, details her work on a new vectorized execution engine that significantly enhances the performance of CockroachDB's SQL operations, particularly the hash join operator. This new model, which processes data in batches of columns rather than rows, achieves a 40x speed increase over the traditional row-at-a-time "Volcano" model. The vectorized execution approach leverages the efficiency of CPU cache and reduces the need for type casting and runtime decisions, making it more CPU-friendly. The blog post delves into the implementation challenges and advantages of vectorized execution, illustrating the differences through practical examples and demonstrating the superior performance of the new engine with benchmark results. Angela credits her internship for providing valuable insights into CPU architecture and compiler optimizations, and concludes with an invitation for engineers to join Cockroach Labs to work on innovative projects like this one.