Types - Kinetica Docs

A type is analogous to a traditional database definition for a table. Before data can be stored in Kinetica, a type must be specified for that data. For every type, Kinetica assigns a unique GUID. Kinetica will use the same GUID for all types with identical characteristics. Every type in Kinetica consists of the following:

Type Label (text to identify this type)
Type Definition (list of columns)
Properties (optional)

For details on nullability and working with nulls, see Nulls.

Type Label

A type label serves as a tagging mechanism for the type. The type label can be any text string specified by the client. The type label serves two purposes. First, it identifies tables with similar data. Second, it helps determine a type’s uniqueness.

Type Definition

A type definition (sometimes referred to as type schema) consists of a set of column names, their respective base data types, and their nullability.

Column Types

Each column in the database will have a specific type that is the combination of a base type and an optional set of column properties, listed below. A given column in a type definition must be of one of the following base types. If no data type column properties are specified to modify the base type, the column will take on the corresponding default specific type. For example, a column with an int base type and no column properties that modify the data type will have a specific type of int, which is a 32-bit signed integer. A column with an int base type and a data type column property of int16 will have a specific type of int16, which is a 16-bit signed integer.

The following lists the specific type within each base type, the number of bytes in memory an instance of the specific type occupies, and the minimum and maximum values the specific type can be assigned.

`int`

Specific Type	Bytes	Minimum Value	Maximum Value
`int` (default)	4	-2147483648	2147483647
`int16`	2	-32768	32767
`int8`	1	-128	127
`boolean`	1	0	1

`long`

Specific Type	Bytes	Minimum Value	Maximum Value
`long` (default)	8	-9223372036854775808	9223372036854775807
`timestamp`	8	-30610224000000 (1/1/1000 00:00:00.000)	29379542399999 (12/31/2900 23:59:59.999)

`float`

Specific Type	Bytes	Minimum Value	Maximum Value
`float`	4	-3.40282 * 10³⁸	3.40282 * 10³⁸

`double`

Specific Type	Bytes	Minimum Value	Maximum Value
`double`	8	-1.79769313486231 * 10³⁰⁸	1.79769313486231 * 10³⁰⁸

`string`

Specific Type	Bytes	Minimum Value	Maximum Value
`string` (default)	32 + length	(empty string)	(100,000,000,000 bytes)
`array(boolean[,n])`	varies	(empty array)	(100,000,000,000 bytes)
`array(int[,n])`	varies	(empty array)	(100,000,000,000 bytes)
`array(long[,n])`	varies	(empty array)	(100,000,000,000 bytes)
`array(ulong[,n])`	varies	(empty array)	(100,000,000,000 bytes)
`array(float[,n])`	varies	(empty array)	(100,000,000,000 bytes)
`array(double[,n])`	varies	(empty array)	(100,000,000,000 bytes)
`array(string[,n])`	varies	(empty array)	(100,000,000,000 bytes)
`char1`	1	(empty string)	(1 byte)
`char2`	2	(empty string)	(2 bytes)
`char4`	4	(empty string)	(4 bytes)
`char8`	8	(empty string)	(8 bytes)
`char16`	16	(empty string)	(16 bytes)
`char32`	32	(empty string)	(32 bytes)
`char64`	64	(empty string)	(64 bytes)
`char128`	128	(empty string)	(128 bytes)
`char256`	256	(empty string)	(256 bytes)
`decimal(p<=18,s)`	8	-999999999999999999	999999999999999999
`decimal(p>=19,s)`	12	-39614081257132168796771975168	39614081257132168796771975167
`date`	4	1000-01-01	2900-12-31
`datetime`	8	1000-01-01 00:00:00.000	2900-12-31 23:59:59.999
`ipv4`	4	0.0.0.0	255.255.255.255
`json`	varies	(empty string)	(100,000,000,000 bytes)
`time`	4	00:00:00.000	23:59:59.999
`ulong`	8	0	18446744073709551615
`uuid`	16	(empty string)	(36 bytes)
`wkt`	varies	(empty geometry)	(100,000,000,000 bytes)

`bytes`

Specific Type	Bytes	Minimum Value	Maximum Value
`bytes` (default)	N/A	(empty array)	(100,000,000,000 bytes)
`vector(n)`	4 * n	(empty vector)	(100,000,000,000 bytes)
`wkt`	varies	(empty geometry)	(100,000,000,000 bytes)

For more information on complex column types, see: Arrays, JSON, and Vector Type.
Character types use UTF-8 encoding and are defined using byte-designated sizes; the use of wide (multi-byte) characters will decrease the total number of characters that can be stored in a given fixed-width string type.
The decimal type should be used instead of float or double when exact values of decimal places need to be represented. This is often used with currency.
The decimal type will be stored in a byte size appropriate for the p value (precision) specified; p values 18 and under will be stored in 8 bytes, while p values 19 and over will be stored in 12 bytes. The maximum p value is 27 and the maximum s value (scale) is 18.
Any date/time within the year 9999 can be used to denote an unknown or out-of-range date. No dates/times in between 2900 and 9999 will be recognized.
Adding nullability to a column requires an additional byte per value; e.g., a nullable integer requires 5 bytes in memory instead of 4.
A valid UUID can be either 32 characters (without hyphens) or 36 characters (with hyphens), e.g., 1bd0b4cc0cbc11eb97be02420a000046 or 1bd0b4cc-0cbc-11eb-97be-02420a000046
Numeric literals may be specified in decimal, hexadecimal with a leading 0x, octal with a leading 0o, or binary with a leading 0b. For example, the number 42 may be represented in any of the following ways: 42, 0x2a, 0o52, and 0b101010. Hexadecimal, octal and binary literals may also be specified as: x'2a', o'52', and b'101010', respectively.

Column Properties

Kinetica has an additional layer of semantic regarding column data type. At the time of creation, a column can be given one or more of the supported properties, which give the column special meaning or handling. The properties can refine the data type, direct special handling, or define the keyed nature of the column. These modifiers can impact the number of records that can be stored in memory, the performance of queries, and the types of operations that can be performed on the data.

Data Types

The following properties can be used to modify the allowable set of values for the corresponding base type. Only one of the following properties may be applied to a given column, and the column must be of the stated base type. The exception to this is nullability, which can be applied to any column in addition to the data type specifiers listed here. However, nullable is not used at type creation, but will be returned in a /show/table call. Denoting a column’s nullability is API-dependent, and, with the exception of the Java API, does not involve the direct use of the nullable column property.

Property	Base Type	Description
`array(boolean[,n])`	string	Boolean array of any length
`array(int[,n])`	string	Integer array of any length
`array(long[,n])`	string	Long array of any length
`array(ulong[,n])`	string	Unsigned long array of any length
`array(float[,n])`	string	Float array of any length
`array(double[,n])`	string	Double array of any length
`array(string[,n])`	string	String array of any length
`boolean`	int	Numbers limited to `0` & `1`; optimizes memory and query performance
`char1`	string	Text of up to 1 character; optimizes memory, disk, and query performance
`char2`	string	Text of up to 2 characters; optimizes memory, disk, and query performance
`char4`	string	Text of up to 4 characters; optimizes memory, disk, and query performance
`char8`	string	Text of up to 8 characters; optimizes memory, disk, and query performance
`char16`	string	Text of up to 16 characters; optimizes memory, disk, and query performance
`char32`	string	Text of up to 32 characters; optimizes memory, disk, and query performance
`char64`	string	Text of up to 64 characters; optimizes memory, disk, and query performance
`char128`	string	Text of up to 128 characters; optimizes memory, disk, and query performance
`char256`	string	Text of up to 256 characters; optimizes memory, disk, and query performance
`date`	string	Interprets a string field as a date of the form `YYYY-[M]M-[D]D`
`datetime`	string	Interprets a string field as a combination of date and time in the form of `YYYY-[M]M-[D]D [H]H24:MI:SS[.mmm]`
`decimal`	string	Interprets a string field as a decimal number, with up to 27 digits of precision and 18 digits of scale
`int8`	int	Numbers limited to 8-bit signed integers; optimizes memory and query performance
`int16`	int	Numbers limited to 16-bit signed integers; optimizes memory and query performance
`ipv4`	string	Dotted decimal IPv4 addresses of the form: `A.B.C.D` where `A`, `B`, `C` and `D` are between `0` and `255`, inclusive (e.g. `127.0.0.1`); optimizes memory, disk, and query performance
`json`	string	Interprets a string field as a JSON object
`nullable`	<any>	Values can be set to null See Nulls for working with null types & values in the API
`time`	string	Interprets a string field as a time of the form `[H]H24:MI:SS[.mmm]`
`timestamp`	long	Timestamps in milliseconds since the Unix epoch: Jan 1 1970 00:00:00
`ulong`	string	Interprets a string field as a 64-bit unsigned long
`uuid`	string	Interprets a string field as a 32 character (without hyphens) or 36 character (with hyphens) universally unique identifier (UUID)
`vector(n)`	bytes	Vector of n float values, generally used in vector search
`wkt`	string or bytes	Indicates that the column has WKT (or WKB) strings that should be handled as geometry objects.

Data Handling

One or more of the following properties can be assigned to a column to alter the way the data is stored & handled. Valid combinations are detailed in the descriptions.

Property	Description
`compress(type)`	This property will compress the values of the associated column using the specified compression `type`, reducing disk usage and I/O load time. Queries against the column may also be faster. For column compression details, see Column Compression.
`data`	Directs that the column’s data should be stored in memory, making it available for use in query expressions. Default property for all columns.
`dict`	This property will dictionary encode the associated column, reducing memory and disk usage. Queries against the column will also be faster. For Dictionary Encoding details, see Dictionary Encoding.
`normalize`	For `vector` column type, automatically normalizes each vector to have a magnitude (L2 norm) of 1; see Vector Type
`text_search`	Enables full text search for string columns. For full text search details & limitations, see Full Text Search.

Data Keys

One or both of these keyed attributes can be assigned to one or more columns. For more information, see the sections on primary keys & shard keys. Foreign keys cannot be assigned as column properties.

Property	Description
`primary_key`	Makes this column part of (or the entire) primary key
`shard_key`	Makes this column part of (or the entire) shard key

Data Replacement

The following property can be assigned to a column to replace certain kinds of data.

Property	Description
`init_with_now`	For date, time, datetime, and timestamp columns, this property will replace empty strings and invalid timestamp values with `NOW()` when inserting data.
`init_with_uuid`	For uuid columns, this property will replace empty strings with a universally unique identifier (UUID).
`update_with_now`	For date, datetime, time, and timestamp columns, this property will replace empty strings and invalid timestamp values with `NOW()` when updating data.
`update_with_user`	For string columns, this property will replace the column value with the name of the requesting user when updating data.

​Type Label

​Type Definition

​Column Types

​int

​long

​float

​double

​string

​bytes

​Column Properties

​Data Types

​Data Handling

​Data Keys

​Data Replacement

Type Label

Type Definition

Column Types

`int`

`long`

`float`

`double`

`string`

`bytes`

Column Properties

Data Types

Data Handling

Data Keys

Data Replacement