Databricks-ML-Assoc ML Workflows Practice Question
A data scientist is using MLflow Tracking in Databricks to compare multiple runs of a hyperparameter tuning experiment. They want to quickly identify the run with the lowest validation loss and then register that model version in the MLflow Model Registry. Which MLflow UI feature allows sorting runs by a specific metric to find the best run?
⚠ Common exam trap
A common mix-up: candidates confuse the run comparison view with the runs table, as both show metrics but only the runs table supports sorting.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The runs table, where you can click on the metric column header to sort runs ascending or descending.
The runs table in the MLflow UI provides a sortable list of all runs, with columns for parameters and metrics. Clicking a metric column header sorts runs by that metric, making it easy to spot the run with the lowest validation loss. This is the standard workflow for selecting the best run to register.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The runs table, where you can click on the metric column header to sort runs ascending or descending.
Why this is correct
The runs table in the MLflow UI lists all runs and allows sorting by any metric column. Clicking the column header sorts runs by that metric, enabling quick identification of the run with the lowest validation loss. This is the most efficient way to find the best run for registration.
- ✗
The experiment notes field, where you can manually record the best run ID.
Why it's wrong here
The experiment notes field is a free-text area for documenting experiment details, not for sorting or identifying runs. It requires manual entry and does not scale or automatically track metrics. It does not provide any sorting capability and is not a reliable method for finding the best run.
- ✗
The model registry page, which automatically sorts models by their latest version's metrics.
Why it's wrong here
The model registry page manages model versions and stages but does not automatically sort models by metrics. It does not compare runs from an experiment. To find the best run, you must first identify it in the experiment's runs table before registering the model.
- ✗
The run comparison view, which displays all runs side-by-side with their metrics.
Why it's wrong here
The run comparison view allows side-by-side comparison of runs, but it does not provide sorting or filtering by a specific metric. It is useful for visual inspection but not for quickly identifying the best run based on a numeric metric. Sorting is a distinct feature available in the runs table.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-ML-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-ML-Assoc exam.