Slim CI with state comparison in dbt - Deep Dive

Overview - Slim CI with state comparison

What is it?

Slim CI with state comparison is a method in dbt that speeds up continuous integration by only running tests and builds on models that have changed since the last run. Instead of rebuilding everything, it compares the current state of your project with the previous state to find differences. This makes testing and deployment faster and more efficient.

Why it matters

Without slim CI, every change triggers a full rebuild and test of the entire project, which can take a long time and slow down development. Slim CI saves time and computing resources by focusing only on what changed. This means faster feedback for data teams, quicker fixes, and more reliable data pipelines in production.

Where it fits

Before learning slim CI, you should understand basic dbt concepts like models, tests, and how dbt runs projects. After mastering slim CI, you can explore advanced dbt features like incremental models, snapshots, and deployment automation.

Mental Model

Core Idea

Slim CI works by comparing the current project state to the last known state and only running tests and builds on changed parts.

Think of it like...

It's like checking your packed suitcase before a trip and only repacking the clothes you actually used or changed, instead of repacking everything every time.

┌─────────────────────────────┐
│ Previous Project State      │
│ (Last CI run snapshot)      │
└─────────────┬───────────────┘
              │
              ▼
┌─────────────────────────────┐
│ Current Project State       │
│ (New code and models)       │
└─────────────┬───────────────┘
              │
      Compare states (diff)  
              │
              ▼
┌─────────────────────────────┐
│ Changed Models & Tests      │
│ (Only these run in CI)      │
└─────────────────────────────┘

Build-Up - 7 Steps

1

Foundation

Understanding dbt Project Basics

Concept: Learn what a dbt project is and how models and tests work.

A dbt project contains SQL models that transform raw data into clean tables. Tests check data quality and correctness. Normally, dbt runs all models and tests every time you build.

Result

You know how dbt organizes data transformations and validations.

Understanding the basic structure of dbt projects is essential before optimizing how builds run.

2

Foundation

What is Continuous Integration (CI)?

Concept: CI is a process that automatically tests and builds your project when you make changes.

In data projects, CI runs dbt commands to check if changes break anything. It helps catch errors early by running tests on every code update.

Result

You understand why CI is important for reliable data pipelines.

Knowing CI basics helps you appreciate why speeding it up with slim CI matters.

3

Intermediate

The Problem with Full CI Runs

🤔Before reading on: Do you think running all models every time is fast or slow? Commit to your answer.

Concept: Running all models and tests on every change wastes time and resources.

When projects grow, full CI runs take longer because dbt rebuilds everything, even if only one model changed. This delays feedback and slows development.

Result

You see why full CI is inefficient for large projects.

Recognizing inefficiency in full CI motivates the need for smarter approaches like slim CI.

4

Intermediate

How State Comparison Works

🤔Before reading on: Do you think comparing project states means checking file sizes or content? Commit to your answer.

Concept: State comparison checks the content and metadata of models and tests to find changes.

dbt saves a snapshot of the last run's project state, including model hashes and test definitions. It compares this to the current state to detect which parts changed.

Result

You understand that state comparison is a smart diff of project components.

Knowing that state comparison looks at content, not just timestamps, explains why slim CI is accurate and reliable.

5

Intermediate

Configuring Slim CI in dbt

Concept: Learn how to set up dbt to use slim CI with state comparison.

You enable slim CI by adding flags like --state and --select in your dbt commands. For example, dbt run --state path/to/previous/run --select state:modified runs only changed models.

Result

You can run dbt commands that only build and test changed parts.

Understanding configuration empowers you to speed up your CI pipelines effectively.

6

Advanced

Handling Dependencies in Slim CI

🤔Before reading on: If model A changes, do you think dependent model B also needs to run? Commit to your answer.

Concept: Slim CI also runs models that depend on changed models to keep data consistent.

dbt tracks dependencies between models. When a model changes, slim CI runs it plus all downstream models that rely on it, ensuring correctness.

Result

You see that slim CI respects model relationships to avoid stale data.

Knowing dependency handling prevents data errors and builds trust in slim CI results.

7

Expert

Limitations and Edge Cases of Slim CI

🤔Before reading on: Do you think slim CI always runs faster than full CI? Commit to your answer.

Concept: Slim CI can be slower or less effective if many models change or state snapshots are missing.

If many models change, slim CI runs almost like full CI. Also, if the previous state snapshot is lost or corrupted, slim CI cannot compare states and falls back to full runs.

Result

You understand when slim CI might not improve speed and how to handle those cases.

Knowing slim CI's limits helps you choose the right CI strategy and avoid surprises.

Under the Hood

dbt stores metadata about each model and test after a run, including checksums of SQL files and compiled SQL. When slim CI runs, it loads this metadata from the previous run and compares it to the current project files. It identifies which models or tests have changed by comparing checksums. Then, it uses the dependency graph to find all affected downstream models. Finally, it runs only those models and tests, skipping unchanged parts.

Why designed this way?

This design balances accuracy and speed. Comparing checksums ensures precise detection of changes, avoiding false positives from timestamps. Using the dependency graph maintains data correctness by rebuilding affected models. Alternatives like timestamp checks were less reliable, and full rebuilds were too slow for large projects.

┌───────────────┐       ┌───────────────┐
│ Previous Run  │       │ Current State │
│ Metadata      │       │ Project Files │
└──────┬────────┘       └──────┬────────┘
       │                       │
       │ Load metadata         │ Read files
       │                       │
       ▼                       ▼
┌─────────────────────────────────────┐
│ Compare checksums of models & tests │
└──────────────┬──────────────────────┘
               │
               ▼
┌─────────────────────────────┐
│ Identify changed models/tests│
└──────────────┬──────────────┘
               │
               ▼
┌─────────────────────────────┐
│ Use dependency graph to find │
│ downstream affected models   │
└──────────────┬──────────────┘
               │
               ▼
┌─────────────────────────────┐
│ Run only changed + dependent │
│ models and tests             │
└─────────────────────────────┘

Myth Busters - 4 Common Misconceptions

Quick: Does slim CI run only the changed models or all models every time? Commit to your answer.

Common Belief: Slim CI runs all models but just skips tests on unchanged ones.

Reality: Slim CI runs only the changed models and their dependent models, skipping everything else.

Why it matters: Believing this causes people to expect no speedup and miss the real efficiency gains.

Quick: Do you think slim CI compares file timestamps or content? Commit to your answer.

Common Belief: Slim CI uses file timestamps to detect changes.

Reality: Slim CI compares file content checksums, which is more accurate than timestamps.

Why it matters: Relying on timestamps can cause missed changes or unnecessary rebuilds, leading to errors or wasted time.

Quick: Does slim CI always speed up CI runs regardless of project size? Commit to your answer.

Common Belief: Slim CI always makes CI faster no matter what.

Reality: If many models change or state snapshots are missing, slim CI may run almost as long as full CI.

Why it matters: Expecting constant speedup can lead to frustration and misdiagnosis of CI issues.

Quick: Can slim CI run correctly without a previous state snapshot? Commit to your answer.

Common Belief: Slim CI can run without any previous state information.

Reality: Slim CI requires a previous state snapshot to compare; otherwise, it falls back to full runs.

Why it matters: Not preserving state snapshots breaks slim CI, causing slower builds and confusion.

Expert Zone

1

Slim CI's accuracy depends on consistent state snapshot storage; ephemeral or missing snapshots reduce benefits.

2

Dependency graph traversal in slim CI can be customized to include or exclude certain models for fine-tuned builds.

3

Slim CI integrates with dbt Cloud and other CI tools differently, requiring careful configuration to maximize speed.

When NOT to use

Avoid slim CI when your project changes extensively in every commit or when state snapshots cannot be reliably stored. In such cases, full CI runs or incremental model builds may be better alternatives.

Production Patterns

Teams use slim CI in automated pipelines triggered by pull requests to get fast feedback. They combine it with incremental models and selective test runs to optimize resource use and maintain data quality.

Connections

Incremental Model Builds

Builds-on

Both slim CI and incremental builds aim to reduce work by focusing only on changed data or models, improving efficiency.

Version Control Diffing

Same pattern

Slim CI's state comparison is like how git detects file changes by comparing snapshots, enabling selective updates.

Cache Invalidation in Web Browsers

Similar principle

Just as browsers only reload changed resources to save time, slim CI only rebuilds changed models to save compute.

Common Pitfalls

#1 Not providing the previous state snapshot path in slim CI commands.

Wrong approach:

dbt run --select state:modified

Correct approach:

dbt run --state path/to/previous/run --select state:modified

Root cause:

Without the --state flag pointing to the previous run, dbt cannot compare states and defaults to full runs.

#2 Ignoring dependencies and running only changed models without their downstream models.

Wrong approach:

dbt run --select state:modified --exclude state:modified+

Correct approach:

dbt run --state path/to/previous/run --select state:modified+

Root cause:

Skipping dependent models breaks data consistency because downstream models rely on upstream changes.

#3 Deleting or not saving the artifacts folder that contains state snapshots between CI runs.

Wrong approach:

Cleaning all build artifacts before every CI run.

Correct approach:

Preserving the artifacts folder or caching it between runs to keep state snapshots.

Root cause:

State comparison depends on previous run metadata; losing it disables slim CI.

Key Takeaways

Slim CI with state comparison speeds up dbt continuous integration by running only changed models and their dependencies.

It works by comparing checksums of project files between runs, not just timestamps, ensuring accurate detection of changes.

Proper configuration and preserving state snapshots are essential for slim CI to work effectively.

Understanding dependencies is critical to avoid data errors when selectively running models.

Slim CI is a powerful tool but has limits when many changes occur or state data is missing.