Custom caching solutions in Entity Framework may require overriding the ________ method to intercept query execution.
- OnQueryExecuting
- OnQueryExecuted
- OnModelCreating
- OnSaveChanges
Option 2, OnQueryExecuted, is correct. This method allows developers to intercept queries after they've been executed, enabling custom caching solutions in Entity Framework.
To handle cache invalidation in a scalable Entity Framework application, ________ patterns can be implemented.
- Cache-Aside
- Repository
- Unit of Work
- Dependency Injection
Option 1, Cache-Aside, is correct. The Cache-Aside pattern involves checking the cache for an item before querying the database, allowing efficient cache invalidation in Entity Framework applications.
In advanced scenarios, ________ can be integrated with Entity Framework to manage complex caching needs.
- Redis
- Memcached
- SQLite
- MongoDB
Option 1, Redis, is correct. Redis is often used in advanced scenarios to manage complex caching needs with Entity Framework due to its high performance and support for advanced data types.
In a high-traffic web application using Entity Framework, how would you design a caching strategy to reduce database load?
- Implementing a distributed caching solution such as Redis or Memcached
- Using in-memory caching with the Entity Framework Core MemoryCache
- Utilizing the second-level cache provided by Entity Framework
- Storing frequently accessed data in a local file cache
Option 1: Implementing a distributed caching solution such as Redis or Memcached would be ideal for a high-traffic web application as it allows for efficient caching of data across multiple servers, reducing the load on the database. This approach ensures that data is readily available and can be accessed quickly, enhancing the application's performance and scalability.
Describe a scenario where caching in Entity Framework might lead to stale data issues and how to mitigate them.
- When dealing with frequently updated data in a multi-user environment, stale data issues may arise if the cached data is not refreshed regularly. Mitigation can be achieved by implementing a cache expiration policy based on data volatility or using cache invalidation techniques such as Dependency Injection (DI) to update the cache when the underlying data changes.
- In scenarios where concurrent transactions are updating the same data, stale data issues may occur if the cache is not properly synchronized. This can be mitigated by employing optimistic concurrency control mechanisms in Entity Framework or utilizing distributed cache locking mechanisms to ensure data consistency.
- Stale data issues may arise when caching data retrieved using lazy loading in Entity Framework, as related entities may not be included in the cache, leading to incomplete or outdated data. To mitigate this, eager loading or explicit loading can be used to prefetch related entities and ensure data consistency.
- When caching query results in Entity Framework, stale data issues may occur if the cache is not invalidated when underlying data changes. To address this, a cache dependency mechanism can be implemented to automatically refresh the cache when relevant data is modified.
Option 4: When caching query results in Entity Framework, stale data issues may occur if the cache is not invalidated when underlying data changes. To address this, a cache dependency mechanism can be implemented to automatically refresh the cache when relevant data is modified. This ensures that the cached data remains up-to-date and consistent with the underlying database, mitigating the risk of stale data issues.
How would you implement caching in an Entity Framework application that deals with real-time data updates?
- Implementing a cache expiration policy based on data volatility to automatically refresh the cache at regular intervals
- Utilizing the Change Tracking feature in Entity Framework to detect and propagate data changes to the cache
- Implementing a cache eviction strategy to remove outdated data from the cache and replace it with updated data
- Using a combination of polling and cache invalidation techniques to detect and update the cache in real-time
Option 2: Utilizing the Change Tracking feature in Entity Framework allows for real-time detection and propagation of data changes to the cache. This ensures that the cached data remains synchronized with the underlying database, even in scenarios involving frequent real-time data updates.
How does Entity Framework manage relationships in a model that uses mixed inheritance strategies (e.g., TPH with TPT)?
- By creating a separate table for each class and using foreign keys to establish relationships between them
- By creating a single table for the base class and separate tables for each derived class
- By creating a table for each class and duplicating columns from the base class in each derived class
- By creating separate tables for each class in the hierarchy
Entity Framework manages relationships in a mixed inheritance strategy like TPH with TPT by creating a single table for the base class and separate tables for each derived class. This ensures that the shared properties from the base class are stored only once, avoiding redundancy. Relationships are established using foreign keys, linking the derived class tables to the base class table. This approach allows for efficient querying and navigation of the object graph.
The ________ attribute in Entity Framework is used to specify the base class in a TPH inheritance hierarchy.
- InheritanceMapping
- TablePerConcrete
- TablePerHierarchy
- [Not Provided by User]
The InheritanceMapping attribute in Entity Framework is used to specify the base class in a Table-Per-Hierarchy (TPH) inheritance hierarchy. This attribute helps Entity Framework to understand how to map the inheritance hierarchy to the database schema.
What is Table-per-Hierarchy (TPH) inheritance in Entity Framework?
- Each type in the inheritance hierarchy is mapped to a separate file in the project.
- Each type in the inheritance hierarchy is mapped to a single table in the database.
- Each type in the inheritance hierarchy is mapped to its own schema in the database.
- Each type in the inheritance hierarchy is mapped to its own table in the database.
Table-per-Hierarchy (TPH) inheritance in Entity Framework maps all derived types in an inheritance hierarchy to a single database table. This means all properties of the derived types are stored in one table, and a discriminator column is used to differentiate between the types. This approach is useful when the derived types share most of their properties and have only a few unique properties. It simplifies the database schema but may lead to null values in the table for properties that are specific to certain derived types.
In Entity Framework, how is Table-per-Type (TPT) inheritance different from Table-per-Hierarchy (TPH)?
- All types in the hierarchy are mapped to a single table.
- Each type in the inheritance hierarchy has its own table.
- The base type and its derived types are stored in separate files.
- The base type and its derived types share the same table.
Table-per-Type (TPT) inheritance in Entity Framework maps each type in the inheritance hierarchy to its own table in the database. This means the base type and its derived types have separate tables, and the tables are connected through a shared primary key. Unlike TPH, TPT ensures that each type has its own table, which can lead to a more normalized database schema. However, it may result in complex queries due to the need for joins to retrieve data from multiple tables.