What Are the Data Type of Hive?

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Larry Thompson

Data types in Hive are important for defining the structure and characteristics of the data stored in tables. Hive supports several data types, each with its own purpose and usage. In this article, we will explore the different data types available in Hive and understand their significance.

Primitive Data Types

Hive supports a variety of primitive data types, which are the building blocks for defining more complex data structures. Here are some commonly used primitive data types:

  • TINYINT: A 1-byte signed integer (-128 to 127).
  • SMALLINT: A 2-byte signed integer (-32,768 to 32,767).
  • INT: A 4-byte signed integer (-2,147,483,648 to 2,147,483,647).
  • BIGINT: An 8-byte signed integer (-9,223,372,036,854,775,808 to 9,223,372,036,854,775,807).
  • FLOAT: A single-precision floating-point number.
  • DOUBLE: A double-precision floating-point number.
  • BOOLEAN: A boolean value (true or false).
  • STRING: A sequence of characters.

Complex Data Types

In addition to the primitive data types mentioned above, Hive also provides support for complex data types. These data types allow you to work with structured and nested data. Let’s take a look at some commonly used complex data types:

Array

An array is an ordered collection of elements of the same data type. In Hive, arrays can be defined using the ARRAY<data_type> syntax. For example, ARRAY<STRING> represents an array of strings.

Map

A map is a collection of key-value pairs, where each key and value can be of different data types. In Hive, maps can be defined using the MAP<key_type, value_type> syntax. For example, MAP<STRING, INT> represents a map with string keys and integer values.

Struct

A struct is a collection of fields with each field having its own data type. In Hive, structs can be defined using the STRUCT<field1: data_type1, field2: data_type2,..> syntax. For example, STRUCT<name: STRING, age: INT> represents a struct with name and age fields.

Date and Time Data Types

Hive also provides support for date and time-related data types:

  • TIMESTAMP: Represents a specific point in time with nanosecond precision.
  • DATE: Represents a date without any time component.

User-Defined Data Types

In addition to the built-in data types, Hive allows you to define your own custom data types using the CREATE TYPE statement. This feature enables you to work with complex data structures tailored to your specific requirements.

In conclusion, understanding the different data types in Hive is crucial for effectively storing and manipulating data. Whether you are dealing with basic values or complex nested structures, Hive offers a wide range of data types to suit your needs.

7 Related Question Answers Found

What Is Hive Data Type?

What Is Hive Data Type? Hive is a popular data warehousing framework built on top of Hadoop that provides a simple and efficient way to query large datasets. One of the key features of Hive is its support for various data types, which allow users to define the structure and constraints of their data.

Which of the Following Data Type Is Supported by Hive?

When working with Hive, it is essential to understand the different data types that are supported. These data types allow for efficient storage and manipulation of data within the Hive environment. In this article, we will explore the various data types that are supported by Hive and how they can be used in your queries.

What Is Map Data Type in Hive?

The Map data type in Hive is a complex data type that allows you to store key-value pairs. It is similar to a dictionary or associative array in other programming languages. In Hive, the Map data type is represented as a collection of key-value pairs, where both the key and value can be of any primitive data type supported by Hive.

What Is Float Data Type in Hive?

What Is Float Data Type in Hive? The float data type in Hive is used to store single-precision floating-point numbers. It is one of the numeric data types available in Hive, which allows you to represent decimal values with a fractional part.

Which Is Not a Complex Data Type in Hive?

When working with Hive, it is essential to understand the different data types available. Hive supports both primitive and complex data types. While primitive data types include integers, strings, and booleans, complex data types allow you to store structured or nested data within a single column.

What Is Homogeneous Data Type?

A homogeneous data type refers to a data type that contains elements of the same kind. In other words, all the values within a homogeneous data type are of the same data type. Examples of Homogeneous Data Types: Let’s take a look at some commonly used homogeneous data types: Arrays: An array is a collection of elements, all of which are of the same data type.

What Type of Tables Are Stored in the Hive Data Warehouse?

Tables in the Hive data warehouse are a fundamental component of the Hive ecosystem. They provide a structured way to store and organize data, making it easier for users to query and analyze large datasets. In this article, we will explore the different types of tables that can be stored in Hive and their unique characteristics.

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