Solving the River Crossing problem with SQL Graph. Let’s see if we can solve this classic problem, using T-SQL and the graph capabilities in Azure SQL / SQL Server!
Are you are familiar with the classic “river crossing” problem? If not, an easy 4 minutes introduction using Wildebeest and Lions as the actors in the problem, is presented in this TED-Ed talk. If you observe carefully, the video briefly mentions using an enumeration approach to list all the possible transitions, and for each transition, the end state. It so happens that this is the classic algorithmic approach as well to solve such problems – to create a graph of all possible states (represented by vertices / nodes in the graph) and the transitions (represented by edges) which result into those states. If you search online, there are plenty of references showing you how to use Breadth-First-Search (BFS) to find the shortest path to solve the problem. David Kopec’s Classic Computer Science Problems books also present implementations of this problem in Python and other languages.
Let’s see if we can solve this classic problem, using T-SQL and the graph capabilities in Azure SQL / SQL Server!
Let’s present the main “rules” of this problem, as presented in the TED talk:
SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
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