LTable

scalation.database.table.LTable
See theLTable companion class
object LTable

The LTable companion object provides factory methods for creating linkable-tables. Supported domains/data-types are 'D'ouble, 'I'nt, 'L'ong, 'S'tring, and 'T'imeNum.

Attributes

Companion
class
Graph
Supertypes
trait Product
trait Mirror
class Object
trait Matchable
class Any
Self type
LTable.type

Members list

Type members

Inherited and Abstract types

type MirroredElemLabels <: Tuple

The names of the product elements.

The names of the product elements.

Attributes

Inherited from:
Mirror
type MirroredLabel <: String

The name of the type.

The name of the type.

Attributes

Inherited from:
Mirror

Value members

Concrete methods

def apply(name: String, schema: String, domain_: String, key: String): LTable

Create a linkable-table given convenient string specifications.

Create a linkable-table given convenient string specifications.

Value parameters

domain_

the domains/data-types for attributes ('D', 'I', 'L', 'S', 'X', 'T')

key

the attributes forming the primary key

name

the name of the linkable-table

schema

the attributes for the linkable-table

Attributes

def apply(name: String, tab: Table): LTable

Create a new empty linkable-table with the same schema as an existing table.

Create a new empty linkable-table with the same schema as an existing table.

Value parameters

name

the name of the new linkable-table

tab

the existing table

Attributes

def apply(tab: Table): LTable

Create a new linkable-table from an existing table.

Create a new linkable-table from an existing table.

Value parameters

tab

the existing table

Attributes

def load(fileName: String, name: String, domain_: String, key: String, pos: Array[Int], sep: String): LTable

Read/create the linked-table with the given name into memory loading its columns with data from the CSV file named fileName. The attribute names are read from the FIRST LINE.

Read/create the linked-table with the given name into memory loading its columns with data from the CSV file named fileName. The attribute names are read from the FIRST LINE.

Value parameters

domain_

the domains/data-types (as one string) for attributes ('D', 'I', 'L', 'S', 'X', 'T')

fileName

the file name (or file-path) of the data file

key

the attributes forming the primary key

name

the name of the table

pos

the sequence of column positions in the input file to be used (null => select all)

sep

the element separation string/regex (e.g., "," ";" " +")

Attributes

def load(fileName: String, name: String, domain: Domain, key: String = ..., pos_: Array[Int] = ..., sep: String = ...): LTable

Read/create the linked-table with the given name into memory loading its columns with data from the CSV file named fileName. The attribute names are read from the FIRST LINE.

Read/create the linked-table with the given name into memory loading its columns with data from the CSV file named fileName. The attribute names are read from the FIRST LINE.

Value parameters

domain

the domains/data-types for attributes ('D', 'I', 'L', 'S', 'X', 'T')

fileName

the file name (or file-path) of the data file

key

the attributes forming the primary key

name

the name of the table

pos_

the sequence of column positions in the input file to be used (null => select all)

sep

the element separation string/regex (e.g., "," ";" " +")

Attributes

See also

scalation.readFileIntoArray

def load(fileName: String, name: String, numCol: Int, key: String): LTable

Read/create the linked-table with the given name into memory loading its columns with data from the CSV file named fileName. The attribute names are read from the FIRST LINE. Use a short-cut (not reliable) to determines the column domains, by applying the 'tuple2type' method to the SECOND LINE. Note: safer to pull a row without missing or zero values from the middle of the dataset

Read/create the linked-table with the given name into memory loading its columns with data from the CSV file named fileName. The attribute names are read from the FIRST LINE. Use a short-cut (not reliable) to determines the column domains, by applying the 'tuple2type' method to the SECOND LINE. Note: safer to pull a row without missing or zero values from the middle of the dataset

Value parameters

fileName

the file name (or file-path) of the data file

key

the attributes forming the primary key

mumCol

the number of columns

name

the name of the table

Attributes

See also

tableTest3

scalation.readFileIntoArray