Deterministic vs Non-Deterministic Functions

Deterministic vs Non-Deterministic Functions in SQL Server: A Comprehensive Guide

Introduction

When working with databases, particularly in SQL Server, understanding the difference between deterministic and non-deterministic functions is crucial for optimizing performance, ensuring accuracy, and writing efficient queries. Functions are a fundamental part of SQL Server and are used to encapsulate logic, simplify queries, and return results. The distinction between deterministic and non-deterministic functions plays a critical role in query optimization, indexing, and performance, especially when these functions are involved in indexes, triggers, or computations that require consistency and reliability.

In this detailed guide, we will explore deterministic and non-deterministic functions in-depth, focusing on their definitions, how they work, their differences, implications on query performance, use cases, and best practices.

1. What Are Functions in SQL Server?

In SQL Server, functions are pre-defined operations or routines that perform a specific task. SQL Server supports several types of functions, such as:

Scalar Functions: Return a single value based on the input parameters.
Aggregate Functions: Operate over a set of rows and return a single result (e.g., SUM(), AVG()).
Table-Valued Functions (TVFs): Return a table as a result (e.g., inline TVFs, multistatement TVFs).

Functions can be classified into two broad categories: deterministic and non-deterministic. These classifications determine whether the result of a function can be predicted reliably based on its inputs.

2. What Are Deterministic Functions?

A deterministic function is a function that always returns the same result when provided with the same input values. In other words, a deterministic function’s output is entirely predictable based on the function’s input.

Key Characteristics of Deterministic Functions

Same Output for Same Input: A deterministic function produces the same result every time it is called with the same input values.
Predictability: The output is predictable and consistent, which makes deterministic functions ideal for scenarios requiring repeatable behavior.
Optimization: SQL Server can optimize queries that use deterministic functions, such as by storing results in indexes or cached query plans.

Examples of Deterministic Functions

Some common examples of deterministic functions in SQL Server include:

Mathematical Functions: Functions like ABS(), ROUND(), and CEILING() are deterministic because they always return the same result for the same input.
String Functions: Functions like LEN(), UPPER(), LOWER() are deterministic as they return the same result every time they are executed with the same string input.
Date and Time Functions: Functions like YEAR(), MONTH(), and DAY() are deterministic when used on fixed date-time values.

Example of a Deterministic Function:

SELECT ABS(-10) AS AbsoluteValue; -- Always returns 10
SELECT LEN('Hello') AS Length; -- Always returns 5

How Deterministic Functions Work

Deterministic functions follow a simple logic: they depend only on the input parameters and do not rely on external states or changes in the environment. For example, ABS() will always return the absolute value of its argument, and LEN() will always return the length of the string provided to it.

Because of this predictable behavior, SQL Server can:

Cache Execution Plans: SQL Server can cache the results of deterministic functions and reuse them across different queries or sessions. This is particularly helpful for improving query performance by avoiding redundant calculations.
Use in Indexes: Deterministic functions can be indexed, which can help speed up queries that filter on or sort by function results.
Use in Computed Columns: SQL Server supports computed columns that can be indexed if the computation involves deterministic functions.

3. What Are Non-Deterministic Functions?

A non-deterministic function, on the other hand, is a function that does not always return the same result for the same set of input values. The output may vary even if the input does not change. This can happen because the function may rely on factors like system state, session settings, or external data, which can change with each execution.

Key Characteristics of Non-Deterministic Functions

Variable Output: Non-deterministic functions return different results each time they are called, even with identical input values.
Dependence on External Factors: The output of a non-deterministic function may be influenced by factors outside the function’s parameters, such as system settings, time, or random values.
Limited Optimization: SQL Server cannot optimize queries involving non-deterministic functions as effectively as deterministic functions because the output cannot be predicted or cached.

Examples of Non-Deterministic Functions

Some common examples of non-deterministic functions include:

GETDATE(): Returns the current system date and time. Its value is different each time it is called, depending on when the query is executed.
NEWID(): Generates a new uniqueidentifier (GUID). Each call to NEWID() produces a different value.
RAND(): Returns a random number, which changes every time it is called.
USER(): Returns the name of the current user executing the query, which could vary depending on the user context.

Example of a Non-Deterministic Function:

SELECT GETDATE() AS CurrentDate; -- Returns current date and time
SELECT NEWID() AS UniqueID; -- Generates a unique GUID

How Non-Deterministic Functions Work

Non-deterministic functions introduce randomness or depend on system state, making their output unpredictable. For example:

GETDATE() returns the current date and time, which naturally changes with each execution.
NEWID() generates a unique identifier each time it is called, ensuring that no two calls return the same value.

Because the results of these functions are not predictable, SQL Server cannot cache their results or use them in indexed operations.

4. Deterministic vs Non-Deterministic Functions: Key Differences

Aspect	Deterministic Functions	Non-Deterministic Functions
Definition	Always return the same result for the same input.	Return different results for the same input over time.
Predictability	Output is predictable and repeatable.	Output is not predictable and may change over time.
Caching	Results can be cached for performance optimization.	Results cannot be cached reliably.
Use in Indexes	Can be indexed to improve query performance.	Cannot be indexed due to unpredictable results.
Impact on Query Plans	Queries are easier to optimize by SQL Server.	Queries are harder to optimize due to variability.
Use in Computed Columns	Can be used in computed columns that are indexed.	Cannot be used in indexed computed columns.
Examples	`LEN()`, `UPPER()`, `ABS()`	`GETDATE()`, `NEWID()`, `RAND()`

5. Performance Implications of Using Deterministic vs Non-Deterministic Functions

5.1. Performance of Deterministic Functions

Query Optimization: SQL Server can cache the execution plan for queries that use deterministic functions, reducing the need to recompile the query each time it is executed. This leads to better overall performance, particularly in repetitive tasks.
Indexing: Because deterministic functions return the same result for the same input, SQL Server can index computed columns or expressions that use these functions, improving query performance by making the search process faster.
Parallelism: Deterministic functions can be optimized for parallel execution, which can be beneficial when working with large datasets.
Predictability: As deterministic functions produce the same results every time, query results can be more easily predicted, leading to better and more reliable performance.

5.2. Performance of Non-Deterministic Functions

Query Optimization: Non-deterministic functions hinder query optimization. Since the result can change each time the function is called, SQL Server cannot cache execution plans for queries that use them, leading to slower query performance.
Indexing: Non-deterministic functions cannot be indexed. As a result, queries that rely on these functions may experience slower performance, especially when used in WHERE clauses or JOIN conditions.
Parallelism: Non-deterministic functions can also hinder parallel execution, as SQL Server may be unable to predict how the function will behave across different threads.

6. Use Cases and Best Practices

6.1. When to Use Deterministic Functions

Use in Indexes: If you need to index a computed column or expression, ensure that the function used is deterministic. This allows SQL Server to optimize the query and improve performance.
Performance-Critical Queries: For queries where performance is a priority, favor deterministic functions over non-deterministic functions whenever possible. The predictability of deterministic functions allows for better query optimization and reduced execution times.
Computed Columns: If you have computed columns in a table, make sure the functions used in the computation are deterministic, especially if those columns are indexed.

6.2. When to Use Non-Deterministic Functions

Date and Time: Use non-deterministic functions like GETDATE() or SYSDATETIME() when you need to include the current date and time in your queries. These functions are essential for operations like timestamping, tracking, and auditing.
Randomized Results: Non-deterministic functions like NEWID() or RAND() are useful when you need to generate random results, such as for shuffling records or creating unique identifiers.
Session-Specific Values: Functions like USER() or SESSION_USER() are useful when you need to retrieve session-specific data.

7. Conclusion

In summary, deterministic and non-deterministic functions serve different purposes in SQL Server, and understanding their characteristics is essential for optimizing query performance, ensuring consistency, and applying the correct logic in your database queries.

Deterministic functions provide consistent and predictable results, which enables SQL Server to optimize query execution, cache results, and use indexes efficiently.
Non-deterministic functions introduce variability in query results, making them less suitable for optimization techniques like indexing and plan caching. However, they are indispensable