Summary
As data grows exponentially over time, query performance is an important ask from all stakeholders. Delta is based on the columnar Parquet format, which is highly compressible, consuming less storage and memory and automatically creating and maintaining indices on data. Data skipping helps with getting faster access to data and is achieved by maintaining file statistics so that only the relevant files are read, avoiding full scans. Delta caching improves the performance of common queries that repeat. optimize compacts smaller files and zorder colocates relevant details that are usually queried together, leading to fewer file reads.
The Delta architecture pattern has empowered data engineers not only by simplifying a lot of their daily activities but also by also improving the query performance for data analysts who consume the hard work and output produced by these upstream data engineers. In this chapter, we looked at some common techniques to apply to our Delta tables...
