When should you choose PreparedStatement over Statement in JDBC?

  • Execute multiple queries efficiently
  • Execute parameterized queries
  • Improve query optimization
  • Simplify complex join operations
The PreparedStatement in JDBC is used to execute parameterized queries, which helps prevent SQL injection and improves performance by reusing the compiled query plan. It is suitable when you need to execute the same SQL statement multiple times with different parameters.

What is the advantage of using CallableStatement in JDBC?

  • Execute SQL queries with parameters
  • Execute stored procedures
  • Improve connection pooling
  • Streamline complex transactions
The CallableStatement in JDBC is used to execute stored procedures, providing a way to encapsulate and execute multiple SQL statements as a single unit. This enhances code modularity, reusability, and security by allowing the use of stored procedures in the database.

How does transaction isolation level impact database performance and consistency?

  • Control concurrency issues
  • Ensure data consistency
  • Increase transaction throughput
  • Read uncommitted data
The transaction isolation level in JDBC determines the degree to which one transaction can affect another. Choosing the appropriate isolation level balances performance and consistency. Lower levels improve performance but may introduce consistency issues, while higher levels enhance consistency at the expense of performance.

How does the use of 'lazy loading' in an ORM framework like Hibernate affect database performance?

  • Decreases performance by loading all data at once
  • Depends on the specific use case
  • Has no impact on performance
  • Increases performance by loading data on demand
'Lazy loading' in Hibernate increases performance by loading data on demand, reducing the initial load time and resource consumption.

What are the implications of using optimistic vs. pessimistic locking strategies in database transactions?

  • Both have similar implications
  • Optimistic locking prevents blocking, may lead to conflicts
  • Pessimistic locking reduces contention, but can cause blocking
  • They are used interchangeably based on convenience
Optimistic locking in database transactions prevents blocking but may lead to conflicts, while pessimistic locking reduces contention but can cause blocking due to exclusive locks.

Explain the role of database indexing in query optimization.

  • Depends on the size of the database and data distribution
  • Has no impact on query optimization
  • Slows down queries by adding complexity
  • Speeds up data retrieval by providing faster access
Database indexing plays a crucial role in query optimization by speeding up data retrieval. Indexes provide faster access to specific data, reducing the time it takes to execute queries, especially in scenarios with large datasets.

Reducing the number of database ________ can significantly improve performance in a web application.

  • connections
  • indexes
  • queries
  • transactions
Reducing the number of repeated SQL queries can significantly improve performance in a web application.

_________ is a technique used to minimize the cost of repeatedly executing similar SQL queries.

  • Caching
  • Normalization
  • Sharding
  • Triggers
Caching is a technique used to minimize the cost of repeatedly executing similar SQL queries by storing the results of expensive operations and returning the cached result when the same operations occur.

What is the role of the doHead method in HTTP servlets?

  • It handles HEAD requests.
  • It is invoked after the doGet method.
  • It is used for handling GET requests.
  • It processes the HTTP headers.
The doHead method in HTTP servlets is used to process the HTTP headers. It does not have a body, making it suitable for handling requests where only the headers need to be processed without returning a full response body.

When designing a system for reporting purposes, what techniques would you use to ensure minimal impact on the transactional database system?

  • Caching, Denormalization, Stored Procedures, Asynchronous Processing
  • Data Warehousing, Materialized Views, Scheduled ETL Processes, Read-Only Replicas
  • Indexing, Query Optimization, Database Partitioning, Load Balancing
  • Vertical Scaling, Horizontal Scaling, Compression, Normalization
Techniques like data warehousing, materialized views, scheduled ETL processes, and read-only replicas can help ensure minimal impact on the transactional database system in a reporting system.