Statement Types - Parallel Transporter

Teradata Parallel Transporter User Guide

Product
Parallel Transporter
Release Number
15.00
Language
English (United States)
Last Update
2018-09-27
dita:id
B035-2445
lifecycle
previous
Product Category
Teradata Tools and Utilities

Statement Types

A Teradata PT script consists of the following types of statements:

Object Definition Statements

In the declarative section of the script, definition statements define all of the Teradata PT objects referenced in the script. For detailed information on required syntax for each types of DEFINE statement, see Teradata Parallel Transporter Reference.

Definition statements include:

  • DEFINE JOB (required) - Names a Teradata PT job, but is not necessarily the same as the file name of the script. Also optionally identifies the character set being used. Contains the definitions of all job objects, as well as one or more processing statements.
  • DEFINE SCHEMA (required) - Defines the data structure for the data an operator will process. Each unique data structure addressed by the job script requires a separate DEFINE SCHEMA object.
  • DEFINE OPERATOR (required) - Defines an operator and specifies the operator attributes to which values can be assigned.
  • Processing Statements

    In the executable section of the script, APPLY statements specify all operations to be performed by the job and the objects that will perform them. For detailed information on APPLY, see Teradata Parallel Transporter Reference.

    Processing statement specifications include the following:

  • APPLY...TO to specify:
  • the operators that will be used to load or update the data
  • the number of instances to be used for the operators
  • operator attribute values (optional)
  • SELECT...FROM to specify:
  • the operators that will be used to acquire, and if necessary, filter the data
  • the number of instances to be used for the operator
  • the selected columns to be sent to the consumer operator
  • operator attribute values (optional)
  • WHERE clauses, CASE DML or CASE value expressions, and SELECT derived column values to filter data between source and destination. See “Data Filtering and Conditioning Options” on page 226.
  • Set the degree of processing parallelism to be used for each operator. See “Optimizing Job Performance with Sessions and Instances” on page 82.