How does the Entity Framework handle model changes in a large database during migration?

  • Automatically generates and executes migration scripts
  • Halts the migration process until model changes are resolved
  • Requires manual intervention for every model change
  • Skips model changes altogether
The Entity Framework automatically generates and executes migration scripts to update the database schema according to the model changes. This automated process helps streamline the migration process and reduces the likelihood of errors.

What is the importance of backup in migration strategies for large databases?

  • Ensures data integrity and provides a fallback option in case of migration failure
  • Speeds up the migration process by skipping backup steps
  • Increases the risk of data loss during migration
  • Backup is unnecessary for large databases
Backup is crucial in migration strategies for large databases as it ensures data integrity and provides a fallback option in case the migration process encounters errors or failures. Without backups, there's a significant risk of data loss during the migration process.

Entity Framework's logging can be integrated with the ________ framework for better traceability and analysis.

  • Log4Net
  • Microsoft.Extensions.Logging
  • NLog
  • Serilog
Entity Framework's logging capabilities can be seamlessly integrated with the Microsoft.Extensions.Logging framework, which provides a flexible and extensible logging infrastructure. Integration with this framework offers various benefits, including enhanced traceability, centralized log management, and compatibility with various logging providers and sinks. Such integration empowers developers to leverage a unified logging solution for comprehensive analysis and monitoring.

To reduce load during migration, large databases often use ________ to distribute data across multiple servers.

  • Clustering
  • Partitioning
  • Replication
  • Sharding
Sharding involves horizontally partitioning data across multiple servers, distributing the load and improving scalability during migration processes.

In large databases, what strategy is typically used to minimize downtime during migration?

  • Blue-green deployment
  • Full database lock
  • Rolling deployment
  • Stop-the-world deployment
Rolling deployment is a strategy commonly used in large databases to minimize downtime during migration. This approach involves gradually migrating subsets of the database while maintaining the overall availability of the system. By rolling out changes incrementally, downtime is minimized, and users experience less disruption.

How can partitioning be used in migration strategies for large databases?

  • Applying horizontal sharding
  • Employing vertical scaling
  • Leveraging data mirroring
  • Utilizing partition switching
Partitioning is a technique where a large table is divided into smaller, manageable parts. In database migration, partitioning allows migrating data in smaller, more manageable chunks, reducing downtime and enabling parallel processing. Partition switching is a method where a partition of a table is moved in or out of a table quickly, useful for large-scale data movements without impacting other parts of the system.

What role does data archiving play in database migration?

  • Enhancing data consistency
  • Maintaining data integrity
  • Minimizing data footprint during migration
  • Streamlining data access
Data archiving involves moving historical or infrequently accessed data to separate storage, reducing the size of the database being migrated. By minimizing the data footprint, migration processes become faster and more efficient, reducing downtime and resource consumption. Archiving also helps in maintaining data integrity by preserving older records while enabling a smoother migration process.

How are complex data transformations typically handled during large database migrations?

  • Applying batch processing
  • Employing ETL processes
  • Leveraging distributed computing
  • Utilizing NoSQL databases
Complex data transformations involve altering the structure or format of data during migration. ETL (Extract, Transform, Load) processes are commonly used to extract data from the source database, transform it according to the target schema, and load it into the destination database. ETL processes enable comprehensive data transformations, such as data cleansing, normalization, and aggregation, ensuring compatibility between source and target systems.

In large databases, ________ can be employed to test the migration process before actual deployment.

  • Mock databases
  • Mock frameworks
  • Mock objects
  • Mock scenarios
Mock objects are commonly used in software testing, including database migration testing. They simulate the behavior of real objects in a controlled way, allowing for thorough testing without impacting live data.

The process of moving data from old to new schema in large databases is known as ________.

  • Data migration
  • Data restructuring
  • Data transformation
  • Schema migration
Schema migration specifically refers to the process of migrating the structure of a database from an old schema to a new one, ensuring data consistency and integrity while transitioning to a new design.