Hive supports several data types, which can be categorized into primitive and complex types.
Primitive Data Types:
- Integer Types: Includes TINYINT (1 byte), SMALLINT (2 bytes), INT (4 bytes), and BIGINT (8 bytes). For example, TINYINT can store values from -128 to 127.
- Floating Point Types: FLOAT (single precision) and DOUBLE (double precision). For instance, DOUBLE can accurately represent decimal numbers up to a certain precision.
- String Types: CHAR (fixed length string), VARCHAR (variable length string), and STRING (arbitrary length string). For example, VARCHAR(10) can store strings up to 10 characters long.
- Boolean Type: BOOLEAN, which can store either TRUE or FALSE.
- Date and Timestamp Types: DATE (date value) and TIMESTAMP (date and time value). For example, TIMESTAMP can store values like '2023-09-13 12:34:56'.
Complex Data Types:
- Array Type: ARRAY<data_type>, which stores a list of elements of the specified data type. For example, ARRAY can store a list of integers.
- Map Type: MAP<key_type, value_type>, which stores a set of key-value pairs. For instance, MAP<STRING, INT> can store a mapping of strings to integers.
- Struct Type: STRUCT<col_name:data_type, ...>, which stores a collection of named fields. Each field can have a different data type. For example, STRUCT<name:STRING, age:INT> can store a structure with a name (string) and an age (integer).
In the context of cloud computing, Hive is often used on big data platforms like Tencent Cloud's Big Data Engine (TBDE). TBDE provides a comprehensive big data processing environment that integrates with Hive, allowing users to easily process and analyze large-scale data. With TBDE, you can leverage Hive's rich data type support to handle diverse data sets efficiently.