Sampling in Hive is a way to write queries on a small chunk of data instead of the entire table. This is required when you have a large dataset and you want to work on a small piece of that dataset. Sampling queries are most efficient when they are performed on bucketed column. Sampling is required when you just need to run queries on a smaller set of data instead of accuracy of the result set of the entire data. That is, it is mostly required for testing purposes. Sampling is most efficient when it is used for auditing purposes. In auditing, sampling can be used to pick a random set of rows or data with respect to the entire data that is huge in number.

Another use case is where you need to perform some aggregation-like average on a sample of data or smaller set of data, keeping aside the accuracy of the data.

To use this sampling feature in Hive, you need to use the TABLESAMPLE clause, which helps in writing...