Nosql Questions Medium
Sharding is a technique used in NoSQL databases to horizontally partition data across multiple servers or nodes. It involves dividing a large dataset into smaller, more manageable subsets called shards, which are then distributed across different machines in a cluster.
The purpose of sharding is to improve scalability and performance by allowing the database to handle larger amounts of data and higher workloads. By distributing the data across multiple servers, the system can handle more concurrent read and write operations, as each server only needs to handle a fraction of the total dataset.
When sharding is implemented in a NoSQL database, a shard key is defined to determine how the data is partitioned. The shard key is typically a field or attribute in the data that is used to determine which shard a particular piece of data belongs to. The shard key is chosen carefully to ensure an even distribution of data across the shards, avoiding hotspots or imbalances.
When a client application wants to access data from a sharded NoSQL database, it first sends a request to a coordinator node, which acts as a gateway to the shards. The coordinator node determines which shard or shards contain the requested data based on the shard key. It then forwards the request to the appropriate shard(s) to retrieve the data.
Once the data is retrieved from the shards, the coordinator node may need to merge or aggregate the results before sending them back to the client. This coordination and aggregation process adds some overhead, but it allows the system to provide a unified view of the data across multiple shards.
Sharding in NoSQL databases offers several benefits, including improved scalability, fault tolerance, and performance. It allows the system to handle larger datasets and higher workloads by distributing the data across multiple servers. Additionally, sharding provides fault tolerance as the failure of one shard or server does not result in the loss of the entire dataset.