Software Engineer, Product

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Table: Sales +-------------+-------+ | Column Name | Type | +-------------+-------+ | sale_id | int | | product_id | int | | year | int | | quantity | int | | price | int | +-------------+-------+ (sale_id, year) is the primary key (combination of columns with unique values) of this table. product_id is a foreign key (reference column) to Product table. Each row of this table shows a sale on the product product_id in a certain year. Note that the price is per unit. Table: Product +--------------+---------+ | Column Name | Type | +--------------+---------+ | product_id | int | | product_name | varchar | +--------------+---------+ product_id is the primary key (column with unique values) of this table. Each row of this table indicates the product name of each product. Write a solution to select the product id, year, quantity, and price for the first year of every product sold. Return the resulting table in any order. Example: Sales table: +---------+------------+------+----------+-------+ | sale_id | product_id | year | quantity | price | +---------+------------+------+----------+-------+ | 1 | 100 | 2008 | 10 | 5000 | | 2 | 100 | 2009 | 12 | 5000 | | 7 | 200 | 2011 | 15 | 9000 | Product table: +------------+--------------+ | product_id | product_name | +------------+--------------+ | 100 | Nokia | | 200 | Apple | | 300 | Samsung | Output: +------------+------------+----------+-------+ | product_id | first_year | quantity | price | +------------+------------+----------+-------+ | 100 | 2008 | 10 | 5000 | | 200 | 2011 | 15 | 9000 | `

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Design a System for Real-Time Twitter Trending Topics Let's design a system to identify trending topics on Twitter in real-time. Consider the following: Data Ingestion: How would you ingest the massive stream of tweets from Twitter? Processing: How would you process the tweets to extract relevant information (e.g., hashtags, keywords)? Trending Detection: How would you identify trending topics based on the processed data? What algorithms or techniques would you use? Scalability: How would you design the system to handle a large volume of tweets and users? Storage: What storage solutions would you use to store the tweets and trending topics? Consider both short-term and long-term storage. Network Requirements: Estimate the network bandwidth required for data ingestion and processing. Performance Optimization: How would you optimize the system for low latency and high throughput? For example, assume that Twitter generates 500 million tweets per day. Design a system that can identify trending topics within a few minutes, considering the computational resources, storage, and network bandwidth needed.

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Describe a time you had to work in an ambiguous environment. What was the situation, what actions did you take, and what was the result? Be specific and provide details about the ambiguity you faced. For example: Lack of Clear Requirements: Describe a project where the initial requirements were poorly defined or constantly changing. How did you navigate the uncertainty and ensure the project moved forward? Conflicting Information: Share an experience where you received conflicting information from different stakeholders. How did you reconcile these discrepancies and make informed decisions? Unclear Goals: Tell me about a time when the overall goals of a project or task were not well-defined. How did you work to clarify the objectives and achieve a successful outcome? Limited Resources: Describe a situation where you had to work with limited resources (time, budget, personnel). How did you prioritize your efforts and make the most of what you had available? New Technology or Domain: Share an experience where you had to work with a new technology or in a domain where you had limited prior experience. How did you quickly learn and adapt to the unfamiliar environment?