DATABASE FUNDAMENTALS
BASICS OF BIG DATA
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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process the same dataset in multiple locations
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data storage on multiple nodes
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aggregation
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summary data
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Detailed explanation-1: -Sharding is a method for distributing a single dataset across multiple databases, which can then be stored on multiple machines. This allows for larger datasets to be split into smaller chunks and stored in multiple data nodes, increasing the total storage capacity of the system.
Detailed explanation-2: -Sharding is a method for distributing data across multiple machines. MongoDB uses sharding to support deployments with very large data sets and high throughput operations. Database systems with large data sets or high throughput applications can challenge the capacity of a single server.
Detailed explanation-3: -Shards can be set up to split automatically when they get too large or they can be more directed. Auto-sharding takes a load off of the programming, which would otherwise not only have to manage the placement of data, but also the application code’s data retrieval.
Detailed explanation-4: -Sharding is the process of distributing data across multiple hosts. In MongoDB, sharding is achieved by splitting large data sets into small data sets across multiple MongoDB instances.
Detailed explanation-5: -Explanation: Sharding is a method for storing data across multiple machines.