How should an Entity Framework application be designed to efficiently handle a sudden surge in user traffic?
- Implementing Asynchronous Query Execution
- Implementing Caching
- Implementing Connection Pooling
- Implementing Connection Resiliency
Implementing Connection Resiliency in an Entity Framework application involves configuring the framework to automatically retry failed database connections, transient errors, or network issues. This approach enhances application robustness and availability, ensuring that the application can gracefully handle sudden spikes in user traffic without experiencing downtime or service disruptions due to connection failures. By resiliently managing database connections, Entity Framework applications can efficiently scale to meet increased demand and maintain a seamless user experience during peak usage periods.
What is an Entity Type in the context of Entity Framework?
- A class representing a database table
- A collection of complex properties
- A database constraint
- A method for querying the database
An Entity Type in Entity Framework represents a class that maps to a database table. It defines the structure of the data stored in that table and includes properties that correspond to the table's columns. When working with Entity Framework, developers interact with Entity Types to perform CRUD operations on the underlying database. Understanding Entity Types is fundamental to modeling and querying data effectively in Entity Framework.
To optimize performance in large data sets, using ________ loading over lazy loading is recommended in Entity Framework.
- Bulk
- Deferred
- Eager
- Pre-loading
Eager loading involves retrieving related data along with the main data in a single query, reducing the number of database trips. This is beneficial for large datasets as it minimizes database round-trips, enhancing performance. Lazy loading, on the other hand, delays the retrieval of related data until it's specifically requested, potentially resulting in numerous individual database calls.
In a distributed system, ________ can be used alongside Entity Framework to handle transaction management efficiently.
- Consistency Models
- Data Partitioning
- Distributed Transaction Coordinator (DTC)
- Two-Phase Commit
In a distributed system, Distributed Transaction Coordinator (DTC) can be used alongside Entity Framework to handle transaction management efficiently. DTC is a Microsoft Windows service that coordinates transactions that span multiple resource managers, ensuring the atomicity, consistency, isolation, and durability (ACID) properties of distributed transactions. It helps manage transactions across different databases or systems in a distributed environment.
For optimal scalability, Entity Framework can be combined with ________ to manage complex query operations.
- Indexes
- NoSQL Databases
- Raw SQL Queries
- Stored Procedures
For optimal scalability, Entity Framework can be combined with stored procedures to manage complex query operations. Stored procedures are precompiled SQL queries stored in the database server. They can improve performance by reducing network traffic and database load, especially for complex queries or frequently executed operations. Entity Framework allows developers to execute stored procedures directly, providing flexibility and efficiency in managing complex queries.
How are Complex Types different from Entity Types in Entity Framework?
- Complex types can have navigation properties
- Complex types can't be mapped to tables
- Complex types can't be queried directly
- Complex types don't have keys
Complex Types in Entity Framework represent non-entity objects that don't have their own identity and lifecycle. Unlike Entity Types, Complex Types can't be mapped to tables and don't have keys. They are typically used to represent parts of an entity or to encapsulate reusable groups of properties. Understanding the differences between Entity Types and Complex Types is essential for designing efficient and maintainable data models in Entity Framework.
What is the primary purpose of Data Annotations in Entity Framework?
- To configure entity mapping
- To define relationships between entities
- To specify database constraints
- To validate entity properties
Data Annotations in Entity Framework provide a way to configure entity mapping directly within the model classes using attributes. They allow developers to specify database mappings, define relationships, and set constraints such as primary keys and indexes. While Data Annotations offer a convenient way to configure aspects of the data model, they also provide a means for validating entity properties, making them versatile tools for defining and enforcing data integrity rules in Entity Framework applications.
How can you configure a property in an Entity Type to be a primary key using Fluent API?
- EntityKey()
- HasKey()
- MapToKey()
- PrimaryKey()
In Entity Framework, to configure a property as a primary key using Fluent API, you use the PrimaryKey() method. This method allows you to specify the primary key for the entity.
In Entity Framework, how do you configure a property in a Complex Type to map to a specific column in the database?
- Column()
- Map()
- Property()
- ToColumn()
To map a property in a complex type to a specific column in the database in Entity Framework, you use the Column() method. This method lets you specify the column name for the property.
What is the role of Shadow Properties in Entity Framework?
- Caching database queries
- Handling complex data types
- Mapping to properties that are not defined in the entity class
- Tracking changes in entity state
In Entity Framework, Shadow Properties play a vital role in mapping properties that are not defined in the entity class. They allow mapping to database columns without corresponding properties in the entity class, useful for scenarios like auditing or data migration.