Product Quality Engineer, Network Hardware

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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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Where are you from in the US?