Range based sharding involves sharding data based on ranges of a given value. To illustrate, let’s say you have a database that stores information about all the products within a retailer’s catalog. You could create a few different shards and divvy up each products’ information based on which price range they fall into, like this:
The main benefit of range based sharding is that it’s relatively simple to implement. Every shard holds a different set of data but they all have an identical schema as one another, as well as the original database. The application code just reads which range the data falls into and writes it to the corresponding shard.
On the other hand, range based sharding doesn’t protect data from being unevenly distributed, leading to the aforementioned database hotspots. Looking at the example diagram, even if each shard holds an equal amount of data the odds are that specific products will receive more attention than others. Their respective shards will, in turn, receive a disproportionate number of reads.
references:
https://www.digitalocean.com/community/tutorials/understanding-database-sharding
Sharding Architecture - Directory Based Sharding
To implement directory based sharding, one must create and maintain a lookup table that uses a shard key to keep track of which shard holds which data. In a nutshell, a lookup table is a table that holds a static set of information about where specific data can be found.
This is similar to range based sharding, but instead of determining which range the shard key’s data falls into, each key is tied to its own specific shard. Directory based sharding is a good choice over range based sharding in cases where the shard key has a low cardinality and it doesn’t make sense for a shard to store a range of keys. Note that it’s also distinct from key based sharding in that it doesn’t process the shard key through a hash function; it just checks the key against a lookup table to see where the data needs to be written.
The main appeal of directory based sharding is its flexibility. Range based sharding architectures limit you to specifying ranges of values, while key based ones limit you to using a fixed hash function which, as mentioned previously, can be exceedingly difficult to change later on. Directory based sharding, on the other hand, allows you to use whatever system or algorithm you want to assign data entries to shards, and it’s relatively easy to dynamically add shards using this approach.
While directory based sharding is the most flexible of the sharding methods discussed here, the need to connect to the lookup table before every query or write can have a detrimental impact on an application’s performance. Furthermore, the lookup table can become a single point of failure: if it becomes corrupted or otherwise fails, it can impact one’s ability to write new data or access their existing data.
references:
https://www.digitalocean.com/community/tutorials/understanding-database-sharding
The main benefit of range based sharding is that it’s relatively simple to implement. Every shard holds a different set of data but they all have an identical schema as one another, as well as the original database. The application code just reads which range the data falls into and writes it to the corresponding shard.
On the other hand, range based sharding doesn’t protect data from being unevenly distributed, leading to the aforementioned database hotspots. Looking at the example diagram, even if each shard holds an equal amount of data the odds are that specific products will receive more attention than others. Their respective shards will, in turn, receive a disproportionate number of reads.
references:
https://www.digitalocean.com/community/tutorials/understanding-database-sharding
Sharding Architecture - Directory Based Sharding
To implement directory based sharding, one must create and maintain a lookup table that uses a shard key to keep track of which shard holds which data. In a nutshell, a lookup table is a table that holds a static set of information about where specific data can be found.
This is similar to range based sharding, but instead of determining which range the shard key’s data falls into, each key is tied to its own specific shard. Directory based sharding is a good choice over range based sharding in cases where the shard key has a low cardinality and it doesn’t make sense for a shard to store a range of keys. Note that it’s also distinct from key based sharding in that it doesn’t process the shard key through a hash function; it just checks the key against a lookup table to see where the data needs to be written.
The main appeal of directory based sharding is its flexibility. Range based sharding architectures limit you to specifying ranges of values, while key based ones limit you to using a fixed hash function which, as mentioned previously, can be exceedingly difficult to change later on. Directory based sharding, on the other hand, allows you to use whatever system or algorithm you want to assign data entries to shards, and it’s relatively easy to dynamically add shards using this approach.
While directory based sharding is the most flexible of the sharding methods discussed here, the need to connect to the lookup table before every query or write can have a detrimental impact on an application’s performance. Furthermore, the lookup table can become a single point of failure: if it becomes corrupted or otherwise fails, it can impact one’s ability to write new data or access their existing data.
references:
https://www.digitalocean.com/community/tutorials/understanding-database-sharding
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