Partitioning in Hive is used to increase query performance. Hive is very good tool to perform queries on large datasets, especially datasets that require a scan of an entire table. Generally, users are aware of their data domain, and in most of cases they want to search for a particular type of data. For such cases, a simple query takes large time to return the result because it requires the scan of the entire dataset. The concept of partitioning can be used to reduce the cost of querying the data. Partitions are like horizontal slices of data that allows the large sets of data as more manageable chunks.

Table partitioning means dividing the table data into some parts based on the unique values of particular columns (for example, city and country) and segregating the input data records into different files or directories.