Sharding is a database topic that many developers understand vaguely, but the details may not be completely clear. The only time someone understands this is if they have used sharding themselves.
According to realtimecampaign.com, many people want to know exactly how sharding works. To find out for sure, use this useful reference and keep reading.
Defining the Partition Key
Sharding at the very core is the act of splitting data where it resides into smaller chunks and spreading it across separate but distinct buckets. Buckets include things like a Postgres schema, a table, or a different type of physical database. As a company continues to scale, they can then move their shard to a new physical node, which will improve performance.
One step that occurs with all sharding implementation is deciding what the data will be partitioned or sharded on. There are several trade-offs to know about for various keys and what is right is usually dependent on the application. Once the sharding key is decided, the goal is to make sure the sharding key is in the right place through the entire application. There are a few ways to do this, with the easiest being to materialize the sharding key through all models. By de-normalizing it, it is possible for the application to make fewer queries for defining how the data is routed and prevent cases where IT employees allege server meltdown caused by staff.
If a request comes in and the sharding is being conducted at the application layer, the application will have to determine the right way to route the request. There’s no need to take additional steps to figure out how to route the request, instead services like Couchbase have this predetermined.
Shard Key = The Shard Number
One misconception related to sharding is when the shard key is defined, the real value of the shard key which is a value that exists in the metadata tables used for determining the routing used.
For example, if a SaaS application is being constructed, in year one 20 customers are acquired, year two results in 100 customers, and year three results in 500 customers. Now, imagine the SaaS application is a CRM system and you make the decision to shard by the customer since the data for each of the customers must remain separate from the others. Since the early adopter customers will likely be using the application for a longer amount of time, customers from year one and two will likely have more data than the customers who were onboarded during year three. There are several options for sharding the data.
While some people find sharding confusing, some experts can help. Using these services can help ensure that the sharding process is successful and that there are no issues with the implementation of it. Being informed is the best way to start using sharding and all the benefits that it offers.