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Understanding the concept of Query Plan Hashes is essential for SQL Server users who need to analyze and optimize their query performance. A query plan hash is a unique identifier generated by the SQL Server for each distinct query execution plan. It helps in identifying multiple instances of the same query that may be running at the same time, thus allowing for efficient analysis and optimization.

To visualize how to generate a query plan hash, consider the following T-SQL code snippet from SQL Server 2016:

-- Create a table
CREATE TABLE Employees (
    ID int,
    Name varchar(255),
    Salary float
);
-- Insert data into the table
INSERT INTO Employees (ID, Name, Salary) VALUES (1, 'John Doe', 50000);
-- Query the table
SELECT * FROM Employees WHERE Salary > 45000;

Once the query is executed, SQL Server 2016 generates an execution plan, then a hash of this plan. While the exact process of hash generation is part of SQL Server's internal algorithm and is not exposed to users, you can retrieve the query plan hash for any executed query using the following T-SQL command:

-- Retrieve the query plan hash
SELECT query_plan_hash 
FROM sys.dm_exec_requests 
WHERE session_id = @@SPID;

In SQL Server 2017, the process remains the same, but you can now also use the sys.dm_exec_query_stats dynamic management view to retrieve the query plan hash for any query in the cache, providing more flexibility in performance analysis.

MySQL 5.7 and DB2 11.1 do not natively support query plan hashes. However, similar functionality can be achieved through other means. For instance, in MySQL 5.7, the EXPLAIN command can be used to analyze query execution plans, while in DB2 11.1, the EXPLAIN PLAN FOR command serves a similar purpose.

Lastly, Azure SQL, Microsoft's cloud-based SQL Server offering, also supports query plan hashes. The process is identical to SQL Server 2016 and 2017, providing a consistent experience across Microsoft's SQL Server offerings.

In conclusion, understanding and using query plan hashes can provide valuable insights into your SQL Server query performance. Whether you're using SQL Server 2016, 2017, or Azure SQL, the process is straightforward and powerful. While MySQL 5.7 and DB2 11.1 do not natively support this feature, similar functionality can be achieved through other means.