examples/chat_examples/example_2.json

{
  "query": "Explain sharding in system design along with its benefits. (10 marks)",
  "context": "It is a very important concept that helps the system to keep data in different resources\naccording to the sharding process. The word “Shard” means “a small part of a\nwhole“. Hence Sharding means dividing a larger part into smaller parts. In DBMS,\nSharding is a type of DataBase partitioning in which a large database is divided or\n\npartitioned into smaller data and different nodes. These shards are not only smaller,\nbut also faster and hence easily manageable.\nHow does Sharding work?\nIn a sharded system, the data is partitioned into shards based on a predetermined\ncriterion. For example, a sharding scheme may divide the data based on geographic\nlocation, user ID, or time period. Once the data is partitioned, it is distributed across\nmultiple servers or nodes. Each server or node is responsible for storing and processing a\nsubset of the data.\nExample:\n\nTo query data from a sharded database, the system needs to know which shard contains\nthe required data. This is achieved using a shard key, which is a unique identifier that is\nused to map the data to its corresponding shard. When a query is received, the system\nuses the shard key to determine which shard contains the required data and then sends\nthe query to the appropriate server or node.\nFeatures of Sharding:\n\uF0B7 Sharding makes the Database smaller\n\uF0B7 Sharding makes the Database faster\n\uF0B7 Sharding makes the Database much more easily manageable\n\uF0B7 Sharding can be a complex operation sometimes\n\uF0B7 Sharding reduces the transaction cost of the Database\n\uF0B7 Each shard reads and writes its own data.\n\uF0B7 Many NoSQL databases offer auto-sharding.\n\uF0B7 Failure of one shard doesn’t effect the data processing of other shards.\nBenefits of Sharding:\n1. Improved Scalability: Sharding allows the system to scale horizontally by adding more\nservers or nodes as the data grows. This improves the system’s capacity to handle\nlarge volumes of data and requests.\n\n2. Increased Performance: Sharding distributes the data across multiple servers or\nnodes, which improves the system’s performance by reducing the load on each server\nor node. This results in faster response times and better throughput.\n3. Fault Tolerance: Sharding provides a degree of fault tolerance as the system can\ncontinue to function even if one or more servers or nodes fail. This is because the data\nis replicated across multiple servers or nodes, and if one fails, the others can continue\nto serve the requests.\n4. Reduced Costs: Sharding allows the system to scale horizontally, which can be more\ncost-effective than scaling vertically by upgrading hardware. This is because horizontal\nscaling can be done",
  "rules": "- If the question says answer for X number of marks, you have to provide X number of points.\n - Each point has to be explained in 3-4 sentences.\n - In case the context express a mathematical equation, provide the equation in LaTeX format as shown in the example.\n - In case the user requests for a code snippet, provide the code snippet in the language specified in the example.- If the user requests to summarise or use the previous message as context ignoring the explicit context given in the message.\n",
  "answer": "Sharding is a technique for dividing a large database into smaller, manageable parts called shards, which are stored across multiple servers or nodes. This process enhances scalability, performance, and fault tolerance by distributing data and processing load. Sharding works by partitioning data based on criteria like geographic location, user ID, or time period, and each shard is responsible for a subset of the data. This method allows for horizontal scaling, improving the system's capacity to handle large volumes of data and requests efficiently.\n\nThe system uses a shard key to identify which shard contains the required data for a query. The shard key is a unique identifier that maps data to its corresponding shard. Upon receiving a query, the system determines the appropriate shard and forwards the query to the correct server or node.\n\n**Features of Sharding:**\n- Sharding makes the database smaller, faster, and more manageable.\n- It can be complex to implement.\n- Sharding reduces transaction costs and allows each shard to read and write its own data.\n- Many NoSQL databases offer auto-sharding.\n- Failure of one shard does not affect the data processing of other shards.\n\n**Benefits of Sharding:**\n1. **Improved Scalability:** Sharding allows horizontal scaling by adding more servers or nodes, enhancing the system's capacity to handle large volumes of data and requests.\n2. **Increased Performance:**By distributing data across multiple servers or nodes, sharding improves performance, resulting in faster response times and better throughput.\n3. **Fault Tolerance:** Sharding provides fault tolerance as the system can continue to function even if one or more servers or nodes fail, thanks to data replication across multiple servers or nodes.\n4. **Reduced Costs:** Horizontal scaling with sharding can be more cost-effective than vertical scaling by upgrading hardware, as it can be done using commodity hardware, which is typically less expensive than high-end servers."
}