Which Data Type Is Not Supported by Hive?


Scott Campbell

Which Data Type Is Not Supported by Hive?

When working with Apache Hive, it is important to understand the supported data types. Hive supports many data types that are commonly used in data analysis and processing. However, there is one data type that is not supported by Hive, and it is the BOOLEAN data type.

What is the BOOLEAN Data Type?

The BOOLEAN data type represents a logical value that can be either true or false. It is often used to store boolean values such as whether a condition is true or false.

Why Isn’t the BOOLEAN Data Type Supported by Hive?

Hive is based on Apache Hadoop, which stores data in distributed file systems such as Hadoop Distributed File System (HDFS). These file systems are designed to handle large amounts of structured and semi-structured data efficiently. However, they do not have native support for boolean values.

In order to work around this limitation, Hive uses other data types to represent boolean values. For example, you can use TINYINT, which represents an 8-bit signed integer, with 0 representing false and 1 representing true.

Supported Data Types in Hive

Hive supports a wide range of data types for storing different kinds of values. Some of the commonly used data types supported by Hive include:

  • TINYINT: Represents a 1-byte signed integer.
  • SMALLINT: Represents a 2-byte signed integer.
  • INT: Represents a 4-byte signed integer.
  • BIGINT: Represents an 8-byte signed integer.
  • FLOAT: Represents a single-precision floating-point number.
  • DOUBLE: Represents a double-precision floating-point number.
  • STRING: Represents a sequence of characters.
  • TIMESTAMP: Represents a date and time value.


While Hive supports a wide range of data types for efficient data processing, the BOOLEAN data type is not one of them. Instead, other data types like TINYINT can be used to represent boolean values in Hive. Understanding the supported data types in Hive is crucial for designing and querying your data effectively.

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