Data Engineer (L5) - Conversation

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You are given the definition of a binary tree node: class Node: def init(self, val=0, left=None, right=None): self.val = val self.left = left self.right = right Write a function is_bst(root) that takes the root of a binary tree as input and returns True if the tree is a valid Binary Search Tree (BST), and False otherwise. Definition of a BST: The left subtree of a node contains only nodes with keys less than the node's key. The right subtree of a node contains only nodes with keys greater than the node's key. Both the left and right subtrees must also be binary search trees. Example 1: Input: root = [2,1,3] Output: true 2 / 1 3 Example 2: Input: root = [5,1,4,null,null,3,6] Output: false 5 / 1 4 / 3 6 Explanation: The root node's value is 5 but its right child's value is 4. Constraints: The number of nodes in the tree is in the range [1, 10000]. -10000 <= Node.val <= 10000 Your solution should handle edge cases such as an empty tree or a tree with only one node.

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Let's discuss architecture and data modeling. Consider you're designing a system for a popular online bookstore. This bookstore needs to manage a vast catalog of books, track customer orders, and provide personalized recommendations. Walk me through your approach to designing the system's architecture and data model, keeping in mind scalability, performance, and maintainability. Be specific by considering these points: Microservices vs. Monolith: Would you opt for a microservices architecture or a monolithic architecture? Explain your reasoning, considering the bookstore's scale and potential future features. Data Storage: What types of databases would you use (e.g., relational, NoSQL)? Justify your choices for different parts of the system (e.g., catalog, orders, user profiles). Data Model: Describe the key entities (e.g., books, authors, customers, orders) and their relationships. Provide a simplified schema for these entities, highlighting essential attributes and data types. How would you handle relationships like a book having multiple authors or a customer placing multiple orders? Scalability: How would you design the system to handle a massive increase in traffic and data volume during peak seasons (e.g., holidays)? Consider aspects like load balancing, caching, and database sharding. Search Functionality: How would you implement the search functionality to allow users to quickly find books based on title, author, ISBN, or keywords? Consider indexing strategies and search algorithms. Recommendation Engine: Briefly outline how you would design a recommendation engine to suggest relevant books to users based on their browsing history, purchase history, and ratings. What data would you need to collect and how would you analyze it? Data Consistency: How would you ensure data consistency across different microservices and databases, especially when dealing with transactions like placing an order or updating inventory levels?

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Tell me about a time you went above and beyond what was expected of you.