Cinchy Platform Documentation
Cinchy v5.0 - v5.5
Cinchy v5.0 - v5.5
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        • Deployment Prerequisites
          • Single Sign-On (SSO) Integration
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        • Disabling your Kubernetes Applications
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      • Upgrading from v4 to v5
  • Guides for Using Cinchy
    • User Guides
      • Overview of the Data Browser
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        • Personal Access Tokens
      • Table Features
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      • Version Management
        • Versioning Best Practices
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    • Builder Guides
      • Best Practices
      • Creating Tables
        • Attaching Files
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        • Restoring Tables, Columns, and Rows
        • Formatting Rules
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        • Linking Data
        • Table and Column GUIDs
        • System Tables
      • Saved Queries
      • CinchyDXD Utility
        • Building the Data Experience (CinchyDXD)
        • Packaging the Data Experience (CinchyDXD)
        • Installing the Data Experience (CinchyDXD)
        • Updating the Data Experience (CinchyDXD)
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        • Reinstalling the Data Experience (CinchyDXD)
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  • API Guide
    • API Overview
      • API Authentication
      • API Saved Queries
      • ExecuteCQL
      • Webhook Ingestion
  • CQL
    • The Basics of CQL
      • CQL Examples
      • CQL Functions Master List
      • CQL Statements Overview
        • Cinchy DML Statements
        • Cinchy DDL Statements
      • Cinchy Supported Functions
        • Cinchy Functions
        • Cinchy System Values
        • Cinchy User Defined Functions
          • Table-Valued Functions
          • Scalar-Valued Functions
        • Conversion Functions
        • Date and Time Types and Functions
          • Return System Date and Time Values
          • Return Date and Time Parts
          • Return Date and Time Values From Their Parts
          • Return Date and Time Difference Values
          • Modify Date and Time Values
          • Validate Date and Time Values
        • Logical Functions
        • Mathematical Functions
        • String Functions
        • Geometry and Geography Data Type and Functions
          • OGC Methods on Geometry & Geography Instances
          • Extended Methods on Geometry & Geography Instances
        • Full Text Search Functions
        • Connections Functions
        • JSON Functions
  • Meta Forms
    • Introduction to Meta-Forms
    • Meta-Forms Deployment Installation Guide
      • Deploying Meta-Forms (Kubernetes)
      • Deploying Meta-Forms (IIS)
    • Creating a Dynamic Meta-Form (Using Tables)
    • Creating a Dynamic Meta-Form Example (Using Form Designer)
    • Forms Data Types
    • Adding Links to a Form
    • Rich Text Editing in Forms
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On this page
  • 1. Overview
  • 2. Using a Table Valued UDF in CQL
  • 3. Creating a Table in a UDF

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  1. CQL
  2. The Basics of CQL
  3. Cinchy Supported Functions
  4. Cinchy User Defined Functions

Table-Valued Functions

1. Overview

Similar to the SQL construct of table-valued functions, a Cinchy User Defined Function can be SELECTED or CROSS JOINED from -- as if it is a table.

2. Using a Table Valued UDF in CQL

The SELECT and FROM clause work the same for a table-valued UDF as they would for a regular Cinchy table.

SELECT u.*
FROM tableUDF() u

3. Creating a Table in a UDF

To generate a table within a UDF for use in CQL, a dataTable will need to be created in the same format as the default Cinchy JSON Saved Query response (Image 1).

function tableUDF()
{
  var result = {};
  result['schema'] = [
    {
      "columnName": "Text Column",
      "type": "String"
    },
    {
      "columnName": "Number Column",
      "type": "Double"
    },
    {
      "columnName": "Date Column",
      "type": "DateTime"
    },
    {
      "columnName": "Yes/No Column",
      "type": "Boolean"
    }
  ];
  result['data'] = [];
  result['data'].push(['Record 1',1,'01/01/2020',false]);
  result['data'].push(['Record 2',2.0,'February 2, 2020',true]);
  result['data'].push(['Record 3',-3,'Mar 03, 2020 12:00:00 AM',false]);
  return JSON.stringify(result);
}
PreviousCinchy User Defined FunctionsNextScalar-Valued Functions

Last updated 2 years ago

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Image 1: Table Valued Function