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Google Cloud Professional Data Engineer · Free practice question 7 of 12

Search indexes for log lookups

Security analysts at Penwortham Bank search a 200 TB BigQuery table of application logs for rare values such as a specific IP address or request ID across many text columns. Each lookup scans most of the table. Which feature makes these needle-in-a-haystack lookups much cheaper and faster?

  1. A.A materialized view that selects all columns
  2. B.Clustering the table by every searched column
  3. C.A search index on the relevant columns, queried with the SEARCH function
  4. D.BI Engine for the project
Show answer and explanation

Correct answer: C. A search index on the relevant columns, queried with the SEARCH function

Why: Search indexes let BigQuery locate the rows that contain specific tokens across text columns, so the SEARCH function reads far less data for point lookups. A materialized view of all columns duplicates the table without helping lookups. Clustering helps with at most four columns used as filters, and BI Engine speeds up aggregations for BI tools rather than token searches.

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