Operator Guide

10.5
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- 10.4.0

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Using Metadata Files to Create Topic Tables

You can load a metadata file to

Data Integration Hub

and create a topic table based on the structure of the file. You can use JSON, XLS, XLSX, and XML metadata files to create topic tables.

When you use a metadata file to create a topic table, you can define table attributes in the file before you load it to

Data Integration Hub

. For example, define column data type and precision, or define a column as a filter accelerator.

All the following fields are mandatory for XLS/XLSX files, some of the fields are optional for JSON and XML files:

columnName: Mandatory. Name of the table column. The name must begin with an alphabetic character or underscore and can contain only alphanumeric characters or underscores. The name cannot include server-reserved keywords. For a list of server-reserved keywords, see the Microsoft SQL Server or Oracle documentation. columnName can contain up to 80 characters. Any special characters and spaces in columnName are replaced with an underscore ( "_").
physicalColumnName: Mandatory. Special characters and spaces in physicalColumnName are replaced with an underscore ( "_"). physicalColumnName for Oracle and Hadoop can contain up to 30 characters. For SQL, it can contain up to 80 characters.
description: Optional. The description can contain up to 1024 characters. If a description exceeds the limit, Data Integration Hub truncates the value before saving it.
filterAccelerator: Optional. The column is used in subscription queries and requires performance-related handling by
Data Integration Hub
. Use this indicator with topics that you plan to use for unbound subscriptions. By default, the value is false.

When you use filter accelerators, consider the following guidelines:

Filter accelerators slow down the writing of publication data to the
Data Integration Hub
publication repository.
Filter accelerators have no impact on subscriptions that do not use filters.
Any change in the table resets the value of filterAccelerator.
datatype: Optional. Data type of the field. By default, the value is string.; The file can contain fields of the following data types:; string
decimal
double
int32
int64
date_time
text
precision: Optional. Applies to data types that support precision. The default precision value depends on the data type of the field:
String: 255
Decimal: 15
Text: 50000
scale: Optional. Applies to data types that support data scaling. The default scale value depends on the data type of the field:
Decimal: 0
All other data types: empty

Example table in a JSON file

The following example shows the table format in a JSON file:

[
    {"columnName":"id", "physicalColumnName": "id1", "description": "name_id", "filterAccelerator": "false", "dataType": "int32"},
    {"columnName":"name", "physicalColumnName": "name1", "description": "name_desc", "filterAccelerator": "false", "dataType": "string", "precision" : 100}
]

Example table in an XML file

The following example shows the table format in an XML file:

<table>
    <column>
      <columnName>id</columnName>
         <physicalColumnName>id</physicalColumnName>
         <description>id_desc</description>
         <dataType>int32</dataType>
         <filterAccelerator>true</filterAccelerator>
      </column>
</table>

Example table in an XLS or XLSX file

The following table shows a sample table structure in an XLS or XLSX file:

columnName	physicalColumnName	description	filterAccelerator	dataType	precision	scale
id	id	desc_id	TRUE	int32
name	name	desc_name	FALSE	String	255
salary	salary	desc_salary	FALSE	decimal	15	2

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Operator Guide

Operator Guide

Using Metadata Files to Create Topic Tables

Using Metadata Files to Create Topic Tables