Towards a Learning-Based Query Optimizer

While transforming the plan into vectors is interesting, I wish they'd gone into more detail about how the ML model prunes and filters the best plan. It is also not clear what attributes of a plan the corresponding vector encodes. I do not know much about Databloom, but it looks like this "Learning-Based Query Optimizer" is built for specific use-cases in a Data engineering/analytics setting(like K-means as cited in the article). It might not be a replacement for optimizers in traditional Databases.

This is cool, I’ve always thought db optimization would be a great place for ML