A Vertex AI pipeline with two steps (data preprocessing and model training) needs optimization to reduce execution time and cost while enabling testing of different algorithms. The preprocessing step takes an hour for 10 TB of data.
The suggested answer is D. Enabling caching for the pipeline job allows reuse of the preprocessed data, avoiding repeated processing. Disabling caching for model training ensures the use of the latest algorithm version.
You have created a Vertex AI pipeline that includes two steps. The first step preprocesses 10 TB data completes in about 1 hour, and saves the result in a Cloud Storage bucket. The second step uses the processed data to train a model. You need to update the model’s code to allow you to test different algorithms. You want to reduce pipeline execution time and cost while also minimizing pipeline changes. What should you do?
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