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Databricks Certified Data Engineer Associate — Practice

por Jude · 14/05/2026 · 208 vistas · 1 compartido

Practice questions on Databricks Lakehouse: Delta Lake, Unity Catalog, Auto Loader, Structured Streaming, and pipelines. Original wording.
12
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🇬🇧 English
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Las preguntas del cuestionario

  1. 1. Which storage layer provides ACID transactions on top of cloud object storage in Databricks?
    1. Parquet
    2. Delta Lake
    3. ORC
    4. Avro
  2. 2. Which Databricks feature continuously ingests new files from cloud storage as they arrive?
    1. COPY INTO
    2. Auto Loader (cloudFiles)
    3. Structured Streaming from Kafka
    4. DBFS mount
  3. 3. Which command efficiently merges a CDC source into a Delta table?
    1. INSERT OVERWRITE
    2. MERGE INTO ... WHEN MATCHED THEN UPDATE WHEN NOT MATCHED THEN INSERT
    3. DELETE then INSERT
    4. Schema evolution alone
  4. 4. What does Delta Lake's 'time travel' allow you to do?
    1. Query data as of a previous version or timestamp
    2. Replicate data across regions
    3. Encrypt data at rest
    4. Compact small files automatically
  5. 5. Which Databricks feature provides unified governance, lineage, and fine-grained access control across workspaces?
    1. Hive Metastore
    2. Unity Catalog
    3. Workspace ACLs alone
    4. Table ACLs only
  6. 6. Which command physically rewrites a Delta table's files to optimize layout and reduce small files?
    1. OPTIMIZE
    2. VACUUM
    3. ANALYZE TABLE
    4. REPAIR TABLE
  7. 7. What is the purpose of VACUUM on a Delta table?
    1. Compact small files into larger ones
    2. Remove files no longer referenced and older than the retention threshold
    3. Update statistics
    4. Rename a table
  8. 8. Which Structured Streaming output mode appends only new rows to the sink?
    1. Complete
    2. Update
    3. Append
    4. Replace
  9. 9. What does the Bronze/Silver/Gold medallion architecture describe?
    1. A three-tier authentication model
    2. Progressive data refinement: raw → cleaned/conformed → aggregated/business-ready
    3. Three SLA classes
    4. Cluster sizing tiers
  10. 10. Which Databricks product orchestrates multi-step data pipelines as DAGs with task dependencies and scheduling?
    1. Databricks Jobs (Workflows)
    2. DBFS
    3. Repos
    4. MLflow
  11. 11. Which file format does Delta Lake use to store table data on disk?
    1. JSON
    2. Parquet
    3. CSV
    4. Avro
  12. 12. How can you enable schema evolution on a Delta MERGE operation?
    1. Set spark.databricks.delta.schema.autoMerge.enabled = true or use WITH SCHEMA EVOLUTION
    2. Drop and recreate the table
    3. Use Hive's ALTER TABLE syntax
    4. It's not supported
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