Question

How would we use hashing to speed up computation through sharding

A) Hashing the entire dataset
B) Hashing the keys to distribute data across nodes
C) Hashing the output of each computation
D) Hashing the column names

Answer 1

Hashing can be used to speed up computation through sharding by distributing data across nodes based on hash values.

Step-by-step explanation:

Hashing can be used to speed up computation through sharding by hashing the keys to distribute data across nodes.

When we use hashing to distribute data across nodes, we generate a hash value for each key and then use that hash value to determine which node the data should be stored in. This allows for efficient retrieval of data as the computation is distributed across multiple nodes, improving speed.

For example, in a cloud computing environment, a sharded database can use hashing to distribute the data across multiple servers. Each server is responsible for a subset of the data, and when a query is made, the hash value of the key is used to determine which server to query. This helps in speeding up the computation as the workload is distributed across multiple nodes.