From 52cf2428bd9b68c82d4f2930314e395101c1ccc5 Mon Sep 17 00:00:00 2001 From: "Leona B. Campbell" <3880403+runleonarun@users.noreply.github.com> Date: Wed, 11 Oct 2023 13:13:50 -0700 Subject: [PATCH] Revert "Update contract.md to include specific rules" --- website/docs/reference/resource-configs/contract.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/contract.md b/website/docs/reference/resource-configs/contract.md index 33dd0b9b815..e8ea6d82287 100644 --- a/website/docs/reference/resource-configs/contract.md +++ b/website/docs/reference/resource-configs/contract.md @@ -27,7 +27,7 @@ The `data_type` defined in your YAML file must match a data type your data platf When dbt is comparing data types, it will not compare granular details such as size, precision, or scale. We don't think you should sweat the difference between `varchar(256)` and `varchar(257)`, because it doesn't really affect the experience of downstream queriers. If you need a more-precise assertion, it's always possible to accomplish by [writing or using a custom test](/guides/best-practices/writing-custom-generic-tests). -Just remember, you need to specify a varchar size or numeric scale, otherwise dbt relies on default values. For example, if a `numeric` type defaults to a precision of 38 and a scale of 0, then the numeric column stores 0 digits to the right of the decimal (it only stores whole numbers), which might cause it to fail contract enforcement. To avoid this implicit coercion, specify your `data_type` with a nonzero scale, like `numeric(38, 6)`. dbt Core 1.7 and higher provides an error if you don't specify precision and scale when providing a numeric data type. +That said, on certain data platforms, you will need to specify a varchar size or numeric scale if you do not want it to revert to the default. This is most relevant for the `numeric` type on Snowflake, which defaults to a precision of 38 and a scale of 0 (zero digits after the decimal, such as rounded to an integer). To avoid this implicit coercion, specify your `data_type` with a nonzero scale, like `numeric(38, 6)`. ## Example