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RAN-DBDEA-00218
Ranvier · DBDEA

Exam DBDEA Topics: transformation Difficulty: medium

Phone numbers arrive in the bronze table in five different formats — '(11) 98888-7777', '5511988887777', '+55 11 98888-7777', among others. The silver contract requires every number normalized to E.164, such as +5511988887777. The transformation must run as native Spark expressions in the pipeline, with no custom code registered on the cluster. Which function fits this requirement?

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  1. A. A Python UDF — regex-based reformatting always requires custom code registered on the cluster before the pipeline can run it
  2. B. regexp_extract() — Spark's regex functions can only pull matching groups out of a string; rewriting the full value is not supported
  3. C. regexp_replace() — it matches a pattern with capture groups and rebuilds the string in the normalized form in one native call
  4. D. split() with a limit — cutting on every non-digit character resolves any phone format in a single pass of the expression
Reveal answer

Correct answer: regexp_replace() — it matches a pattern with capture groups and rebuilds the string in the normalized form in one native call

Reference: https://docs.databricks.com/aws/en/sql/language-manual/sql-ref-functions

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Official Answer (C): regexp_replace() — it matches a pattern with capture groups and rebuilds the string in the normalized form in one native call

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