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Data Types in Hive





Data types:
  • Types are associated with the columns in the tables. The following Primitive types are supported:
  • Integers
    • TINYINT - 1 byte integer
    • SMALLINT - 2 byte integer
    • INT - 4 byte integer
    • BIGINT - 8 byte integer
  • Boolean type
    • BOOLEAN - TRUE/FALSE
  • Floating point numbers
    • FLOAT - single precision
    • DOUBLE - Double precision
  • String type
    • STRING - sequence of characters in a specified character set


Implicit conversion is allowed for types from child to an ancestor. So when a query expression expects type1 and the data is of type2, type2 is implicitly converted to type1 if type1 is an ancestor of type2 in the type hierarchy. Note that the type hierarchy allows the implicit conversion of STRING to DOUBLE.


Complex Types

Complex Types can be built up from primitive types and other composite types using:
  • Structs: the elements within the type can be accessed using the DOT (.) notation. For example, for a column c of type STRUCT {a INT; b INT} the a field is accessed by the expression c.a
  • Maps (key-value tuples): The elements are accessed using ['element name'] notation. For example in a map M comprising of a mapping from 'group' -> gid the gid value can be accessed using M['group']
  • Arrays (indexable lists): The elements in the array have to be in the same type. Elements can be accessed using the [n] notation where n is an index (zero-based) into the array. For example for an array A having the elements ['a', 'b', 'c'], A[1] retruns 'b'.
Using the primitive types and the constructs for creating complex types, types with arbitrary levels of nesting can be created. For example, a type User may comprise of the following fields:
  • gender - which is a STRING.
  • active - which is a BOOLEAN.

- See more at: http://labstrikes.blogspot.in/2012/08/adsense-middle-blog-post.html#sthash.gQgSkqx8.dpuf
 
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