The document discusses the implementation of a Cost-Based Optimizer (CBO) for N1QL, Couchbase's SQL-like query language for JSON data, introduced in Couchbase 6.5. Unlike traditional rule-based optimizers, the CBO leverages statistical data to optimize query execution by selecting the most efficient query plan based on cost estimation. This involves collecting and organizing statistics on JSON's flexible schema, including scalars, objects, and arrays, to handle the complexities of JSON data structures. The CBO aims to improve query performance and system efficiency by addressing challenges such as mixed data types and nested structures, ultimately reducing the total cost of ownership by minimizing the need for performance debugging. The document also highlights the challenges and methodologies involved in collecting statistics on JSON data and how these are used to enhance query optimization.