Statistics can be automatically generated and updated depending upon certain conditions set at the database level. But sometimes it makes sense to manually add statistics objects to your tables & indexes in Microsoft SQL Server.
Why are statistics so critical? Because without this insight into how your data is distributed in your tables and indexes, the SQL Server Query Optimizer (QO) would not have any understanding of how your data is distributed.
The challenge involves an undirected cyclic graph that represents pairs of connected nodes that have some kind of a relationship between them. The goal is to group all nodes that are connected either directly or indirectly (transitively).
Practical use cases for finding a maximum matching are quite obvious--for example, maximum utilization of agents. But what could be practical use cases for finding a maximal matching? Here's what you need to know.