1 Introduction

Prerequisites, disclaimers, and guide overview

Keywords

snowflake, R, RStudio, Posit, VS Code, workspace notebooks, snowflakeR, RSnowflake, mlops

Introduction

1.1 Overview

This guide is for R users who want to run data analysis, statistical modeling, forecasting, and ML workflows on Snowflake — from RStudio, Posit, VS Code, or Workspace Notebooks (and optionally ML Jobs and SPCS) — without maintaining a separate R server or rewriting models in Python.

It covers three open-source packages, platform concepts for newcomers to Snowflake, local/IDE setup, notebook bootstrap, DBI connectivity, and the full ML platform (Feature Store, Model Registry, experiments, monitoring, and parallel R).

New to Snowflake? Start with Snowflake Platform Primer and the Glossary.

1.2 How this guide is organized

Repo folders vs rendered chapter numbers

Chapter sources live in prefixed folders (01_snowflake_platform/, 07_network_and_eai/, …). Quarto assigns chapter numbers in reading order from _quarto.yml, so a folder name like 07_ is not the same as “Chapter 7” in the built book — for example, Network & EAI usually renders as Chapter 8 after Introduction, platform/IDE chapters, and Workspace bootstrap.

Cross-references in this guide use chapter titles, not folder prefixes (folder names like 07_ are for repo layout only).

1.3 Two paths into this guide

If you start from…	Read first
RStudio, Posit, or VS Code on your laptop	Local R Setup → RStudio, Posit & VS Code
Snowflake Workspace Notebooks (in Snowsight)	Snowflake Platform Primer → Workspaces overview

Workspace-specific setup (bootstrap cells, org runtime images) is in Part II — not needed on day one if you only use a local IDE.

1.4 What’s covered in this guide

Ch	Topic	Description
00	Introduction	Prerequisites, disclaimers, roadmap
01	Snowflake primer	Platform concepts for R users
02	Architecture	Three packages, rpy2, auth
03–04	R from your IDE	Local setup, RStudio, Posit, VS Code
05–09	Workspace	Notebooks, bootstrap, EAI, `%%R`, CRE
10	Beyond R	Julia, Scala, Java (optional)
11–14	RSnowflake	SQL API, DBI, dbplyr
15–23	snowflakeR	MLOps, Feature Store, Registry, scale-out
F	Glossary	Terms and acronyms

1.5 Learning Objectives

After completing this chapter, you will be able to:

Explain who this guide is for and what problems it solves
List prerequisites for Workspace and local development
Locate the three package repositories and companion notebooks

1.6 Important disclaimers

Community packages (Snowflake-Labs)

These open-source packages are developed to help customers use R in Workspaces and containers and to gather feedback. They are not officially supported Snowflake product offerings; APIs may change as they evolve.

Package	Role
snowflake-notebook-multilang	Bootstrap R/`%%R`, EAI helpers, CRE tooling in Workspace
RSnowflake	DBI over the SQL REST API (+ optional ADBC)
snowflakeR	R interface to `snowflake-ml-python` (Feature Store, Registry, SPCS, …)

snowflakeR depends on Snowflake’s supported snowflake-ml-python SDK on the Python side; the R wrapper itself remains community-maintained.

Pre-built package tarballs in Workspace

Configure pre-built .tar.gz tarballs for snowflakeR and RSnowflake in your notebook YAML when you reach Workspace Bootstrap. Installing from source inside Workspace is slow (minutes) and brittle. See also Appendix B.

1.7 Prerequisites

1.7.1 Snowflake access

Snowflake account with Workspace Notebooks (or ML Container Runtime for ML Jobs)
Role with warehouse usage and notebook execution
For automatic EAI creation: CREATE INTEGRATION (or an admin-run script from the bootstrap step)

1.7.2 R and Python (local development)

Component	Version
R	4.2+
Python	3.10+ (for `snowflake-ml-python` bridge)
Optional	`connections.toml` or key-pair auth for local connect

See Appendix A: Setup and Local R Setup.

1.7.3 Skills

Comfortable writing R and reading SQL
Basic familiarity with notebooks (cells, kernels) if using Workspace
ML concepts (features, training, inference) for snowflakeR chapters

1.8 Companion artifacts

Artifact	Location
Workspace notebooks	snowflakeR `inst/notebooks`
Multilang smoke test	sfnb `examples/r_smoke_test`
Feature Store concepts	Feature Store Implementation Guide

1.9 Next steps

Snowflake Platform Primer if you are new to Snowflake, then Architecture.

--- title: "Introduction" subtitle: "Prerequisites, disclaimers, and guide overview" --- # Introduction {.unnumbered} *Author: [Simon Field](https://www.linkedin.com/in/fieldy6961/)* ## Overview This guide is for R users who want to run data analysis, statistical modeling, forecasting, and ML workflows **on Snowflake** — from **RStudio, Posit, VS Code**, or **Workspace Notebooks** (and optionally ML Jobs and SPCS) — without maintaining a separate R server or rewriting models in Python. It covers three open-source packages, platform concepts for newcomers to Snowflake, local/IDE setup, notebook bootstrap, DBI connectivity, and the full ML platform (Feature Store, Model Registry, experiments, monitoring, and parallel R). **New to Snowflake?** Start with [Snowflake Platform Primer](../01_snowflake_platform/index.qmd) and the [Glossary](../appendices/F_glossary/index.qmd). ## How this guide is organized {#sec-guide-structure} ::: {.callout-note} ## Repo folders vs rendered chapter numbers Chapter sources live in **prefixed folders** (`01_snowflake_platform/`, `07_network_and_eai/`, …). Quarto assigns chapter numbers **in reading order** from `_quarto.yml`, so a folder name like `07_` is **not** the same as “Chapter 7” in the built book — for example, [Network & EAI](../07_network_and_eai/index.qmd) usually renders as **Chapter 8** after Introduction, platform/IDE chapters, and Workspace bootstrap. **Cross-references in this guide use chapter titles**, not folder prefixes (folder names like `07_` are for repo layout only). ::: ## Two paths into this guide {#sec-two-paths} | If you start from… | Read first | |--------------------|------------| | **RStudio, Posit, or VS Code** on your laptop | [Local R Setup](../03_local_r_setup/index.qmd) → [RStudio, Posit & VS Code](../04_rstudio_posit_vscode/index.qmd) | | **Snowflake Workspace Notebooks** (in Snowsight) | [Snowflake Platform Primer](../01_snowflake_platform/index.qmd) → [Workspaces overview](../05_workspaces_overview/index.qmd) | Workspace-specific setup (bootstrap cells, org runtime images) is in Part II — not needed on day one if you only use a local IDE. ## What's covered in this guide | Ch | Topic | Description | |----|-------|-------------| | [**00**](index.qmd) | Introduction | Prerequisites, disclaimers, roadmap | | [**01**](../01_snowflake_platform/index.qmd) | Snowflake primer | Platform concepts for R users | | [**02**](../02_architecture/index.qmd) | Architecture | Three packages, rpy2, auth | | [**03–04**](../03_local_r_setup/index.qmd) | R from your IDE | Local setup, RStudio, Posit, VS Code | | [**05–09**](../05_workspaces_overview/index.qmd) | Workspace | Notebooks, bootstrap, EAI, `%%R`, CRE | | [**10**](../10_multilang_beyond_r/index.qmd) | Beyond R | Julia, Scala, Java (optional) | | [**11–14**](../11_rsnowflake_sql_api/index.qmd) | RSnowflake | SQL API, DBI, dbplyr | | [**15–23**](../15_mlops_on_snowflake/index.qmd) | snowflakeR | MLOps, Feature Store, Registry, scale-out | | [**F**](../appendices/F_glossary/index.qmd) | Glossary | Terms and acronyms | ## Learning Objectives After completing this chapter, you will be able to: - Explain who this guide is for and what problems it solves - List prerequisites for Workspace and local development - Locate the three package repositories and companion notebooks --- ## Important disclaimers {#sec-disclaimers} ::: {.callout-important} ## Community packages (Snowflake-Labs) These open-source packages are developed to help customers use R in Workspaces and containers and to gather feedback. They are **not officially supported Snowflake product offerings**; APIs may change as they evolve. | Package | Role | |---------|------| | **snowflake-notebook-multilang** | Bootstrap R/`%%R`, EAI helpers, CRE tooling in Workspace | | **RSnowflake** | DBI over the SQL REST API (+ optional ADBC) | | **snowflakeR** | R interface to `snowflake-ml-python` (Feature Store, Registry, SPCS, …) | snowflakeR depends on Snowflake's **supported** `snowflake-ml-python` SDK on the Python side; the R wrapper itself remains community-maintained. ::: ::: {.callout-warning} ## Pre-built package tarballs in Workspace Configure **pre-built `.tar.gz`** tarballs for `snowflakeR` and `RSnowflake` in your notebook YAML when you reach [Workspace Bootstrap](../06_workspace_bootstrap/index.qmd). Installing from source inside Workspace is slow (minutes) and brittle. See also [Appendix B](../appendices/B_config_reference/index.qmd). ::: ## Prerequisites {#sec-prerequisites} ### Snowflake access - Snowflake account with [Workspace Notebooks](https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks) (or ML Container Runtime for ML Jobs) - Role with warehouse usage and notebook execution - For automatic EAI creation: `CREATE INTEGRATION` (or an admin-run script from the bootstrap step) ### R and Python (local development) | Component | Version | |-----------|---------| | R | 4.2+ | | Python | 3.10+ (for `snowflake-ml-python` bridge) | | Optional | `connections.toml` or key-pair auth for local connect | See [Appendix A: Setup](../appendices/A_setup/index.qmd) and [Local R Setup](../03_local_r_setup/index.qmd). ### Skills - Comfortable writing R and reading SQL - Basic familiarity with notebooks (cells, kernels) if using Workspace - ML concepts (features, training, inference) for snowflakeR chapters ## Companion artifacts {#sec-companions} | Artifact | Location | |----------|----------| | Workspace notebooks | [snowflakeR `inst/notebooks`](https://github.com/Snowflake-Labs/snowflakeR/tree/main/inst/notebooks) | | Multilang smoke test | [sfnb `examples/r_smoke_test`](https://github.com/Snowflake-Labs/snowflake-notebook-multilang/tree/main/examples/r_smoke_test) | | Feature Store concepts | [Feature Store Implementation Guide](https://snowflake-labs.github.io/snowflake-featurestore-imp-guide/) | ## Next steps {#sec-next} [Snowflake Platform Primer](../01_snowflake_platform/index.qmd) if you are new to Snowflake, then [Architecture](../02_architecture/index.qmd).