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CERTIFIED-DATA-ENGINEER-PROFESSIONAL · Question #113

A data architect has heard about lake's built-in versioning and time travel capabilities. For auditing purposes they have a requirement to maintain a full of all valid street addresses as they…

The correct answer is A. Delta Lake time travel does not scale well in cost or latency to provide a long-term versioning. The critical information is that Delta Lake time travel does not scale well for long-term auditing. By default, Delta Lake retains transaction log history for only 30 days (configurable via delta.logRetentionDuration), and old data files are vacuumed away. Relying on it as a…

Data Lakehouse Design and Architecture

Question

A data architect has heard about lake's built-in versioning and time travel capabilities. For auditing purposes they have a requirement to maintain a full of all valid street addresses as they appear in the customers table. The architect is interested in implementing a Type 1 table, overwriting existing records with new values and relying on Delta Lake time travel to support long-term auditing. A data engineer on the project feels that a Type 2 table will provide better performance and scalability. Which piece of information is critical to this decision?

Options

  • ADelta Lake time travel does not scale well in cost or latency to provide a long-term versioning
  • BDelta Lake time travel cannot be used to query previous versions of these tables because Type 1
  • CShallow clones can be combined with Type 1 tables to accelerate historic queries for long-term
  • DData corruption can occur if a query fails in a partially completed state because Type 2 tables
  • EDelta Lake only supports Type 0 tables; once records are inserted to a Delta Lake table, they

How the community answered

(56 responses)
  • A
    77% (43)
  • B
    13% (7)
  • C
    2% (1)
  • D
    7% (4)
  • E
    2% (1)

Explanation

The critical information is that Delta Lake time travel does not scale well for long-term auditing. By default, Delta Lake retains transaction log history for only 30 days (configurable via delta.logRetentionDuration), and old data files are vacuumed away. Relying on it as a permanent audit log is architecturally unsound and becomes expensive at scale. This is why the data engineer's suggestion of a Type 2 table (which physically stores historical records as rows) is better for long-term, scalable auditing. Options B, C, D, and E contain inaccurate statements about Delta Lake's capabilities.

Topics

#Delta Lake#Time Travel#SCD (Slowly Changing Dimensions)#Data Auditing

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