Database sharding is a technique for managing large datasets by dividing a single database into smaller, more manageable shards. Each shard is housed on a separate server, allowing for parallel processing and improved performance. This method is crucial for scalability and is used by major platforms like Pinterest and Instagram to handle vast amounts of user data efficiently.
Show More
Database sharding is a technique used in computer science to divide a single logical database into smaller, manageable pieces for efficient data management
Performance Improvement
Database sharding improves performance by distributing workload and allowing for parallel processing
Scalability
Database sharding allows for scalability by adding more servers to accommodate growing data demands
Database sharding differs from partitioning in that it distributes data across multiple database instances, while partitioning divides a database into segments within the same server environment
Shard Key
The Shard Key is used to assign data rows to specific shards in database sharding
Shards
Shards are distinct databases that store portions of data in database sharding
Shard Map
The Shard Map is a directory that associates Shard Keys with the corresponding shards in database sharding
A comprehensive understanding of the components of database sharding is crucial for efficient management of large datasets
Choosing a Suitable Shard Key
A suitable Shard Key is essential for even data distribution and preventing overloading of a single shard in database sharding
Reliable Method for Data Discovery
A reliable method for data discovery, such as maintaining an accurate shard map, is crucial for effective database sharding
Selecting the Appropriate Sharding Pattern
The appropriate sharding pattern, whether range, list, or hash, should be chosen based on specific data distribution and access requirements in database sharding
Over-Sharding
Over-sharding, or creating more shards than immediately necessary, can be advantageous for future growth and scalability in database sharding
Importance of Planning for Future Growth
Planning for future growth is critical for optimizing the sharding process and achieving desired performance improvements in database sharding
Social media platforms like Pinterest and Instagram use database sharding to efficiently process and store large volumes of user data
E-commerce platforms, such as 'ShopAtoZ', can implement database sharding by dividing customer order databases based on 'CustomerID' for quicker data retrieval
00
Shards are stored on individual ______ servers and each contains a portion of the original database's data.
database
01
Database sharding is beneficial for tables with ______ of rows, facilitating quicker data access.
billions
02
Purpose of Shard Key
Assigns data rows to specific shards for distribution and retrieval.
