Parameters

Introduction to Parameters

Parameters can be used to create global constants. A parameter can be used with a $ sign, like $status in this parameterized filtered metric:

orders.count FILTER (WHERE orders.status = $status)

Parameters are defined either per workspace, per domain, or per dynamic dataset. The definition includes parameter name and default value. Parameter values can be overridden based on the following hierarchy:

Global value (per workspace)
In a domain
In a query (when using the SQL interface) or in a dynamic dataset

Using parameterized semantics in a dynamic dataset deployed as a VIEW allows to create parameterized views

Parameterized Dynamic Datasets

Dynamic datasets can include calculations with parameters. The value of the parameter when in a user query is by this order:

Value set in real-time by user with a SET command.
Default value set in the dynamic dataset
Default value set in the domain
Default value set in the workspace

A dynamic dataset parameter default value can override a domain parameter or a workspace parameter of the same name.

Deploying to VIEWs

When a dynamic dataset is deployed as a Snowflake VIEW, parameters can be set using the Snowflake SET statement:

-- run in Snowflake, on a view that uses the $status parameter

SET status='O';
SELECT * FROM [Honeydew Dataset Deployed View];

Deploying to TABLEs

When a dynamic dataset is deployed as a Snowflake TABLE (regular or dynamic) the default values of parameters are used, as set in the dynamic dataset configuration.

Using parameters within a SQL interface connection

If there is a SQL interface table or domain called world, and a parameter called param, set it as:

SELECT ...
FROM (
  SELECT *, 12 as "$param" from world
)

The statement above selects from world with 12 as the value of parameter param.

Dynamic parameters using UDFs

Parameter values can be computed using user defined functions (UDF) in Snowflake, by using the UDF in the parameter expression:

SELECT ...
FROM (
  SELECT *, my_udf(12) as "$param" from world
)

The statement above selects from world with parameter param set to the result of UDF my_udf(12). This approach allows complex computation of parameters, using other functions or data in Snowflake. For example, a user parameter can be used to extract value from a lookup table:

-- A user defined function that maps keys to value
CREATE OR REPLACE FUNCTION my_udf (key number)
RETURNS varchar
AS 'select value from lookup_table where key = lookup_table.key limit 1';

YAML Schema

Each parameter is defined by a YAML file in Git, which also tracks and preserves the full history of every change. The schema for parameter is:

type: parameter
name: <name>
display_name: <display name>
owner: <owner>
description: |-
  <description>
labels: [label1, label2, ...]
tags:
  - key: <key>
    value: <value>
    source: <snowflake/databricks/bigquery/honeydew/other>
  - ...
folder: <folder>
hidden: <True/False/Yes/No>
value: |-
  <value statement>

Fields:

name: Name of parameter (global)
value: SQL constant expression (i.e. a number or a string)
display_name, owner, description, labels, tags, folder, hidden: Metadata

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Release Notes

Introduction to Parameters

Parameterized Dynamic Datasets

Deploying to VIEWs

Deploying to TABLEs

Using parameters within a SQL interface connection

Dynamic parameters using UDFs

YAML Schema

​Introduction to Parameters

​Parameterized Dynamic Datasets

​Deploying to VIEWs

​Deploying to TABLEs

​Using parameters within a SQL interface connection

​Dynamic parameters using UDFs

​YAML Schema

Introduction to Parameters

Parameterized Dynamic Datasets

Deploying to VIEWs

Deploying to TABLEs

Using parameters within a SQL interface connection

Dynamic parameters using UDFs

YAML Schema