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code, you have to decide if the productivity bene ts of the abstraction are worth the costs The costs vary depending on the operation and the sizes of collections The following are some aspects of the cost of using LINQ in general and some of the key LINQ components in particular First, it is critical to understand the difference between a LINQ query and its results A LINQ query is the de nition of a computation You can execute it as many times as you like, or you can execute it once and cache the results The low-hanging fruit for better performance is often avoiding unnecessary re-execution of a query You can execute the query once and cache the results over a certain period of time if you do not expect the results to change (or if your application can tolerate stale data) This optimization matters most when the basic cost of running a query is high (you have to execute a database query, for example) or when the queried collection is large (for instance, you are going through a large collection to nd a few objects in the result) or when the computation itself is very expensive method or clause) (such as when an expensive predicate is run in the Beyond this general opportunity exist component-speci c challenges and opportunities LINQ to Objects implementation relies on extension methods for C# or the VBNET compiler translates a LINQ query from expression syntax into a set of method calls The translation to method calls and the execution of the method calls typically performs only basic optimizations based on the structure of the code Unlike in the case of a database, it does not have statistics about the data (such as the size of a collection, indexes, or distribution of values) for doing additional optimizations such as picking hash joins or nested loop joins based on sizes of collections Hence, there may be more optimal ways to deal with very large sets of data than bringing them all into memory and using LINQ to Objects queries against them This is exactly why LINQ uses expression trees that are translated more ef ciently into query data LINQ to SQL is one such component that translates expression trees into SQL statements that the database query processor can optimize LINQ to SQL provides object abstraction over relational data This (which is not surinvolves the following costs over the use of a in its implementation) The prising, because LINQ to SQL uses
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costs are incurred because services are provided over and above what you : get from a Query translation: As shown in Figure 81 in 8, Reading Objects with LINQ to SQL, a compiler generates an expression tree that is translated into SQL at runtime This does involve some cost that can be amortized using compiled queries Object materialization: Objects need to be constructed and lled with values from rows returned by the database Identity caching: Updates require object identity, and object identity is obtained by maintaining a cache to look up an object reference given a key value Some overhead is associated with hashing the key values This overhead applies only to queries returning entities It is not applicable to those returning nonentity objects (projections) Copy of original values: This overhead is incurred only if you don t use designer/SqlMetal-generated classes and don t implement If you nd that a particular query is on a critical path, you can use the following optimizations: Compiled query: As discussed in 8, a LINQ to SQL query can be parameterized and compiled This does not eliminate the translation cost, but it amortizes it over multiple executions Use of a compiled query provides the maximum performance gain in query scenarios Alternatively, you could also use a stored procedure or a TVF for the performance-sensitive queries These two options are at very different levels Compiled query is a choice of an application developer and can be considered speci c to an application Stored procedure or TVF may be controlled by a database administrator (DBA) and should be appropriate for the database Object materialization speed is automatically signi cantly improved by LINQ to SQL implementation through the use of cached materializers You don t need to write any code to take advantage of it In
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