PMLE The most likely cause of the error? Practice Question

Exhibit

Refer to the exhibit.

```
CREATE OR REPLACE MODEL `mydataset.housing_model`
OPTIONS
  (model_type='linear_reg',
   input_label_cols=['price'],
   data_split_method='custom',
   data_split_col='split_flag')
AS
SELECT * FROM `mydataset.housing_data`
```

The table `housing_data` has 1000 rows. The `split_flag` column contains only NULL values. The model creation fails with the error: "Invalid state: The number of training data rows is 0."

What is the most likely cause of the error?

⚠ Common exam trap

Google Cloud often tests the subtle distinction between missing values in the label column (which are handled gracefully) versus missing values in the data split column (which can cause a complete failure), leading candidates to incorrectly blame missing values in the target column.

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 data split column contains only NULL values, so no rows are assigned to the training set

When the data split column contains only NULL values, BigQuery ML cannot assign any rows to the training set. The `DATA_SPLIT_METHOD` using a custom column requires non-NULL values in that column to partition data into training and evaluation sets; if all values are NULL, the training set receives zero rows, causing the model creation to fail with an error about insufficient training data.

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 data split column contains only NULL values, so no rows are assigned to the training set
Why this is correct
AutoML splits data using the designated split column; if every value is NULL, no row is assigned to the training, validation, or test sets, so training cannot proceed and the job fails with this error.
✗
The model type 'linear_reg' is incompatible with the column 'price' because of missing values
Why it's wrong here
Vertex AI accepts missing values for linear regression, so nulls in 'price' do not cause a type incompatibility; the error concerns the column's data type. This is tempting because missing-value handling genuinely blocks some model types, but not linear_reg.
✗
The model creation does not have permission to read the dataset in BigQuery
Why it's wrong here
Permission errors surface as access-denied or permission-denied messages, not the reported error. Checking BigQuery dataset permissions is tempting because Vertex AI training reads data through the BigQuery API, and insufficient IAM roles genuinely block training jobs.
✗
The model creation did not specify a training budget, so default is insufficient
Why it's wrong here
Vertex AI applies a default training budget when none is specified, so omitting it does not trigger this error. Specifying a budget is tempting because it controls training cost and duration, and is relevant when tuning custom training jobs, not for this failure.

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PMLE The most likely cause of the error? Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

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