How can statistics about data distribution be used in query optimization?
- Data distribution statistics are not relevant for query optimization and are primarily used for reporting purposes.
- Data distribution statistics are only useful for offline analytics and have no impact on real-time query optimization.
- Statistics guide query optimization by determining the order of query execution without impacting performance.
- Statistics help identify anomalies in data distribution, leading to improved query performance by fine-tuning indexing strategies.
Statistics about data distribution play a crucial role in query optimization, aiding in the creation of efficient execution plans for queries.
Which metric is commonly used to measure the success of a CI/CD pipeline?
- Code Churn
- Code Complexity
- Lead Time for Changes
- Lines of Code
Lead Time for Changes is a commonly used metric to measure the success of a CI/CD pipeline. It represents the time taken for a code change to be implemented and deployed into a production environment. Shorter lead times indicate faster and more efficient pipelines.
What does merging in Git involve?
- Combining changes from one branch to another
- Creating a new repository
- Deleting branches in a repository
- Rewriting commit history
Merging in Git involves combining changes from one branch to another. It allows developers to integrate changes made in one branch into another branch, typically merging feature branches into the main development branch.
Ruby is frequently used for server-side scripting in web development, particularly with frameworks like _______ on Rails.
- Django
- Laravel
- Ruby
- Ruby
Ruby is frequently used for server-side scripting in web development, particularly with frameworks like Ruby on Rails. Ruby on Rails is a popular web development framework.
You're working on a project and need to add a new feature. How would you approach it using TDD?
- Implement the feature directly and then write tests to validate it
- Skip testing for new features as they might not have a significant impact
- Write a failing test for the new feature, implement the feature to pass the test, refactor if needed
- Write tests after implementing the feature to ensure its correctness
The TDD (Test-Driven Development) approach involves writing a failing test first, then implementing the feature to make the test pass, and finally refactoring if necessary. This process helps ensure that the feature works as expected and catches regressions early.
_______ caching stores copies of frequently accessed data on the client-side.
- Browser
- Client
- Frontend
- Local
Client caching involves storing copies of frequently accessed data on the client-side. This reduces the need to fetch the data from the server, improving performance.
Google Cloud Platform's _______ is a fully managed serverless data warehouse.
- BigQuery
- Cloud Storage
- Compute Engine
- Datastore
Google Cloud BigQuery is a serverless, highly scalable, and cost-effective multi-cloud data warehouse. It allows for super-fast SQL queries using the processing power of Google's infrastructure.
In a project with multiple developers, how would you utilize a collaboration tool to ensure smooth coordination and efficient code integration?
- Establish version control with Git, use branching for parallel development, and implement pull requests for code review
- Implement a single code file for all developers, use a shared password-protected document for communication
- Use email for code sharing, conduct daily in-person meetings, rely on individual IDEs for version control
- Utilize a shared network drive for code storage, schedule weekly team meetings, conduct manual code integration
In a collaborative development environment, leveraging version control with Git, branching, and pull requests is essential. This approach allows developers to work on features independently, ensuring smooth coordination and efficient code integration through code reviews and merges.
Which tool is commonly used for managing infrastructure as code in cloud environments?
- Ansible
- Docker
- Jenkins
- Terraform
Terraform is commonly used for managing infrastructure as code in cloud environments. It allows users to define and provision infrastructure using a declarative configuration language.
In a project where requirements are expected to evolve over time, which SDLC model would you recommend and why?
- Agile
- Spiral
- V-Model
- Waterfall
In a project with evolving requirements, Agile is recommended. Agile emphasizes adaptability, collaboration, and iterative development, making it suitable for projects where requirements are subject to change. It allows for continuous feedback and adjustments during the development process.