Which method is commonly used in Node.js to handle errors in callbacks?
- try...catch
- process.exit()
- console.error()
- callback(error)
In Node.js, it's common to handle errors in callbacks by passing an error object as the first argument to the callback function. This allows the callback to check if an error occurred during the asynchronous operation and take appropriate action. The other options (try...catch, process.exit(), and console.error()) are not used to handle errors in callbacks but serve different purposes.
Which method can be used to add new elements to an array in JavaScript?
- append()
- push()
- add()
- insert()
To add new elements to an array in JavaScript, you should use the push() method. It adds one or more elements to the end of an array. The other options are not valid methods for adding elements to an array in JavaScript.
What is the significance of the process.nextTick() method in Node.js?
- It schedules a callback function to be executed in the next iteration of the event loop, immediately after the current operation is complete.
- It delays the execution of a callback function for a specific number of milliseconds.
- It cancels the execution of a callback function.
- It executes the callback function asynchronously in a new Node.js process.
process.nextTick() is used to schedule a callback function to be executed in the next iteration of the event loop, immediately after the current operation is complete. This allows for efficient asynchronous code execution. The other options do not accurately describe the purpose of process.nextTick().
How can composite indexing be optimized to enhance query performance in relational databases?
- Use covering indexes
- Increase the number of indexed columns
- Avoid indexing on frequently updated columns
- Use B-tree indexes only
Composite indexing can be optimized by using covering indexes, which include all the columns required by a query. This reduces the need for additional table lookups and can significantly enhance query performance. Increasing the number of indexed columns may not always be beneficial as it can increase index maintenance overhead. Indexing frequently updated columns should be avoided to prevent write performance degradation. B-tree indexes are just one type of composite index, and the choice of index type depends on the specific use case.
What is the significance of the tilde (~) symbol in a version number, like ~1.2.3, in semantic versioning?
- It allows upgrades to the specified version and any future versions, including breaking changes.
- It signifies that downgrades are allowed.
- It restricts upgrades to only the specified version.
- It allows upgrades to the specified version and any future backward-compatible versions.
The tilde (~) symbol allows upgrades to the specified version and any future backward-compatible versions while keeping you within the same major version. It's more restrictive than the caret (^).
What does a 0 as the major version (e.g. 0.1.2) signify in semantic versioning?
- It indicates an unstable or experimental version with no guarantees of backward compatibility.
- It signifies the absence of a major version.
- It means that the software is in its initial release and is highly stable.
- It represents a pre-release version.
A 0 as the major version signifies an unstable or experimental version with no guarantees of backward compatibility. It's often used for initial development phases.
When utilizing closures, it is crucial to manage memory effectively to avoid ________.
- memory leaks
- buffer overflows
- infinite loops
- syntax errors
When utilizing closures, it is crucial to manage memory effectively to avoid memory leaks. If closures capture references to objects that are no longer needed, those objects will not be garbage collected, leading to memory leaks. Properly managing references and being mindful of what is captured in closures is essential to prevent this issue.
You are developing a real-time chat application in Node.js. How would you design the application to handle a high number of simultaneous connections without degrading performance, considering the nature of the Event Loop and Non-Blocking I/O?
- Use worker threads to offload CPU-intensive tasks.
- Utilize Node.js cluster module for load balancing.
- Implement microservices architecture for scalability.
- Increase the Event Loop's thread pool size.
To handle a high number of simultaneous connections without degrading performance in Node.js, you can use the cluster module, which allows you to create multiple child processes (workers) to distribute the load efficiently. Options a and c do not directly address the Node.js Event Loop's nature, and option d is not a recommended approach as it may lead to thread contention.
You are developing a high-traffic RESTful API with Express. How would you design the architecture to ensure optimal performance, scalability, and maintainability?
- Use a single server instance for simplicity.
- Implement a microservices architecture with multiple small services.
- Rely solely on client-side caching to reduce server load.
- Don't worry about code structure; focus on hardware upgrades for scalability.
Implementing a microservices architecture with multiple small services allows for optimal performance, scalability, and maintainability. Using a single server instance can become a bottleneck in high-traffic scenarios. Relying solely on client-side caching doesn't address server-side performance and scalability issues. Neglecting code structure and relying on hardware upgrades is not a best practice for maintainability.
What are the implications of choosing an improper data type for a field in a database schema on storage and performance?
- Increased storage space, slower queries
- Decreased storage space, faster queries
- Improved data integrity
- No impact on storage or performance
Choosing an improper data type can lead to increased storage space and slower queries. For example, using a large data type for a small piece of data wastes space and may result in more I/O operations, slowing down queries. It's crucial to choose appropriate data types to optimize storage and performance.