10+ Himalayan Bio Organic Foods Interview Questions and Answers

Mongo query to increase age by 20% for documents with age field

• Use $exists operator to filter documents with age field

• Use $mul operator to increase age by 20%

• Example: db.users.updateMany({ age: { $exists: true } }, { $mul: { age: 1.2 } })

Key considerations include data modeling, indexing, sharding, and replication.

• Consider the data model carefully to ensure it fits the application's needs.

• Use indexing to improve query performance.

• Plan for sharding to distribute data across multiple servers for scalability.

• Implement replication for high availability and fault tolerance.

Over-indexing in MongoDB can negatively impact performance by increasing memory usage and slowing down query execution.

• Over-indexing can lead to increased memory usage as each index consumes memory.

• Having too many indexes can slow down write operations as each index needs to be updated when a document is inserted, updated, or deleted.

• To prevent over-indexing, carefully analyze query patterns and create indexes only for fields that are frequently queried.

• Regularly review and r...read more

Promises are objects representing the eventual completion or failure of an asynchronous operation, while callbacks are functions passed as arguments to be executed after a task is completed.

• Promises allow chaining multiple asynchronous operations, while callbacks can lead to callback hell.

• Promises have built-in error handling through .catch(), while callbacks rely on error-first callbacks.

• Promises are easier to read and maintain due to their sequential nature, while callbacks...read more

Use the KEYS command in Redis to retrieve all keys containing a specific substring.

• Use the KEYS command followed by the pattern '*xyz*' to retrieve all keys containing the substring 'xyz'.

• Be cautious when using the KEYS command as it can be resource-intensive on large datasets.

• Consider using SCAN command for better performance when dealing with large datasets.

I believe no-code tools like XANO are great for rapid prototyping and simplifying development processes.

• No-code tools like XANO allow for faster development by eliminating the need for manual coding

• They are great for prototyping and testing ideas quickly

• XANO specifically offers a visual interface for building backend logic without writing code

• I have used XANO in a few projects and found it to be user-friendly and efficient

Key factors include data modeling, normalization, indexing, scalability, and performance.

• Consider data modeling to ensure efficient storage and retrieval of data.

• Normalize the database to reduce redundancy and improve data integrity.

• Use indexing to speed up data retrieval operations.

• Design for scalability to accommodate future growth and changes.

• Optimize for performance by considering query optimization and data caching.

Different authentication methods include OAuth, JWT, Basic Auth, and OAuth2.

• OAuth: Allows third-party applications to access resources without sharing credentials.

• JWT (JSON Web Tokens): Securely transmit information between parties as a JSON object.

• Basic Auth: Sends user credentials in the header of each request.

• OAuth2: Authorization framework that enables a third-party application to obtain limited access to an HTTP service.

The request-response cycle in node.js involves a client sending a request to a server, which processes the request and sends back a response.

• Client sends a request to the server using HTTP methods like GET, POST, PUT, DELETE.

• Server receives the request, processes it, and generates a response.

• The response is sent back to the client, typically in the form of HTML, JSON, or other data formats.

• Node.js uses event-driven, non-blocking I/O model to handle multiple requests efficient...read more

My approach for Heavy Data Handling involves optimizing database queries, using indexing, caching, and implementing efficient algorithms.

• Optimizing database queries by using proper indexing and avoiding unnecessary joins

• Implementing caching mechanisms to reduce the load on the database

• Using efficient algorithms for data processing and manipulation

• Batch processing large datasets to minimize resource usage

• Implementing data partitioning and sharding for scalability

• Utilizing para...read more