Configuring an Entity Type as immutable in Entity Framework means that once an entity is created, its state cannot be changed. While this can lead to improved performance and enhanced security by preventing unintended modifications, it also reduces flexibility in data manipulation, as entities cannot be updated after creation. Additionally, query optimization may be simplified due to the immutable nature of the entities.

A primary key in Entity Framework serves to uniquely identify each record in a table. It ensures that each row in the table can be uniquely identified. This is crucial for data integrity and efficient data retrieval operations. Without a primary key, it would be challenging to manage and manipulate data effectively.

Entity Framework supports several strategies for implementing complex inheritance structures. One common approach is Table Per Hierarchy (TPH), where all classes in the inheritance hierarchy are mapped to a single table with a discriminator column to distinguish between different types. This simplifies the database schema but can lead to unused columns and potential performance issues.

The correct option is Option 1: NotMapped. This data annotation is used to specify that a property should be excluded from the database schema. It is typically applied to properties that are not mapped to any database table column, such as calculated properties or properties used for internal processing within the application. Using NotMapped prevents Entity Framework from attempting to create a corresponding column in the database.

Not defining an index on a frequently queried column can lead to slower query performance as the database engine needs to perform full table scans to locate the desired data. This results in increased overhead and longer query execution times, impacting the overall performance of the application.

Entity Framework automatically creates indexes on foreign key columns to optimize performance. These indexes help in efficient querying and joining of related entities, resulting in faster database operations.

Indexes in Entity Framework are primarily used to improve query performance. By creating indexes on columns frequently used in search criteria or join conditions, the database management system can locate the relevant rows more efficiently, leading to faster query execution. However, it's essential to use indexes judiciously as they can also impact insert and update performance.

In Entity Framework, a composite key is defined by using the [Key] attribute on multiple properties within an entity class. This tells Entity Framework that the combination of these properties forms a unique identifier for each record in the table. Composite keys are useful when a single property cannot uniquely identify records, and a combination of properties is needed for this purpose.

When mapping an Entity Type to a database view in Entity Framework, you can use the [Table] attribute on the entity class and provide the database view name as a parameter. This approach explicitly specifies the mapping between the entity and the database view. This ensures that Entity Framework knows how to interact with the database view when querying or modifying data.

Non-clustered indexes help improve query performance by allowing efficient data retrieval based on columns frequently used in WHERE clauses. Unlike clustered indexes, non-clustered indexes don't alter the physical order of the table data. They're particularly useful for improving search performance on large datasets without affecting the way the data is stored on disk.

In Entity Framework, when naming conventions are followed, a primary key is automatically configured if the property name is 'Id' or the class name followed by 'Id'. For example, if you have a class named 'Product', the primary key conventionally would be 'ProductId'.

When using the Code-First approach in Entity Framework, you create an index that spans multiple columns using Fluent API's HasIndex method. This method allows you to define an index on multiple columns by specifying the properties involved in the index. Using Fluent API provides more flexibility and control over index creation compared to using attributes like Index or Key.