How can you speed up LINQ queries?

1 Use the right query type

There are two types of LINQ queries: query syntax and method syntax. Query syntax resembles SQL and uses keywords like from, where, select, group, and join. Method syntax uses extension methods and lambda expressions to chain query operations. Both types of syntax can achieve the same results, but they have different advantages and disadvantages. Query syntax is more concise and expressive, but method syntax is more flexible and powerful. Depending on your scenario, you may want to use one or the other, or even combine them, to optimize your query performance. For example, query syntax is better for filtering and projecting data, while method syntax is better for aggregating and ordering data.

2 Use deferred execution

Deferred execution means that a LINQ query is not executed until you iterate over the results, such as using a foreach loop, a ToList method, or a Count method. Deferred execution can improve performance by avoiding unnecessary computation and memory allocation. For example, if you have a query that filters a large collection based on a user input, you can defer the execution until the user enters the input, rather than executing the query every time the collection changes. However, deferred execution can also have drawbacks, such as repeated execution, stale data, or dependency on external sources. You can use the ToArray or ToList methods to force immediate execution and cache the results in memory, but this will consume more resources and may not be feasible for very large data sets.

3 Use parallel queries

Parallel queries use multiple threads to execute a LINQ query, taking advantage of the multicore processors in modern computers. Parallel queries can significantly speed up your LINQ queries, especially when dealing with CPU-intensive operations, such as sorting, grouping, or aggregating. You can use the AsParallel method to convert a regular LINQ query into a parallel query, and the ParallelEnumerable class to perform parallel operations. However, parallel queries also have some limitations and trade-offs, such as increased overhead, potential concurrency issues, or non-deterministic ordering. You should only use parallel queries when you have a performance bottleneck and when the query is suitable for parallelization.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?