Databricks Certified Data Engineer - Associate
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A data engineer is designing a data pipeline. The source system generates files in a shared directory that is also used by other processes. As a result, the files should be kept as is and will accumulate in the directory. The data engineer needs to identify which files are new since the previous run in the pipeline, and set up the pipeline to only ingest those new files with each run. Which of the following tools can the data engineer use to solve this problem?
Real Exam
Community
KKeng
A
Unity Catalog
B
Delta Lake
C
Databricks SQL
D
Data Explorer
E
Auto Loader
Explanation:
Auto Loader is specifically designed to incrementally and efficiently process new data files as they arrive in cloud storage without any additional setup. It automatically tracks which files have been processed and only ingests new files in subsequent runs, making it ideal for scenarios where files accumulate in a directory and need to be processed incrementally.
Key features of Auto Loader:
- Incremental processing: Automatically detects and processes only new files
- Efficient file tracking: Uses a checkpoint mechanism to track processed files
- No file movement required: Files can remain in their original location
- Scalable: Can handle large volumes of incoming files
- Cloud storage optimized: Works with various cloud storage systems
Why other options are incorrect:
- Unity Catalog: A governance and metadata management tool, not for incremental file processing
- Delta Lake: A storage format with ACID transactions, but doesn't inherently track new files
- Databricks SQL: A SQL analytics service, not for incremental file ingestion
- Data Explorer: A tool for exploring data, not for incremental pipeline processing
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