Partitioning and Sharding | System Design | High Level Design
Welcome to an in-depth guide on partitioning and sharding in system design!
Join me as I break down these essential techniques for managing large-scale data systems. This video offers a comprehensive overview of partitioning and sharding, explaining their differences, uses, and benefits. In upcoming episodes, I'll delve deeper into each concept, providing practical examples and answering common interview questions step by step.
Partitioning and sharding are crucial for scaling databases and ensuring they can handle massive amounts of data efficiently. As systems grow, managing data storage and retrieval becomes increasingly challenging. These techniques help distribute data across multiple servers, improving performance, reliability, and scalability.
Partitioning
Partitioning involves dividing a database into smaller, more manageable pieces called partitions. Each partition can be stored on a different server, allowing the system to handle more data and queries simultaneously. There are different types of partitioning:
Sharding
Sharding is a specific type of horizontal partitioning where data is distributed across multiple databases or servers. Each shard operates independently, holding a portion of the total data set. Sharding is particularly useful for large-scale applications with high read and write demands. Key benefits of sharding include:
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Пікірлер: 4
Sharding use shard key to distribute the data. This means each database will have different content. However, you were saying that maintaining consistency is a major issue in sharding. Isn't it an issue of replication and not sharding?
@ReactifyLabs
5 күн бұрын
@averroussaloom893 I am glad somebody asked this question. Consistency does not need to be within the same entity. For example, your friend went to a different country and made an account on Instagram. Then, his data will be in that country's shard which would be different from your country's shard. Now, if he follows you, both your's and your friend's followers and following list should get updated to adhere to consistency. But, they are in different shards. So, we need to handle that case. I hope this answers your question.
@averroussaloom893
5 күн бұрын
@@ReactifyLabs aa i see. So the inconsistency can occur if one shard interact with other shard. In this scenario, some data references cannot be validated with the the DB constraint because the data is in other shard. This can results to inconsistency like when the data in one shard is removed and other shard still have the data reference for it. Now i understand! Thanks!
@ReactifyLabs
5 күн бұрын
@@averroussaloom893 great