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RAN-DBDEA-00055
Ranvier · DBDEA

Exam DBDEA Topics: transformation Difficulty: hard

JSON event files land continuously in cloud storage. The gold table catalog.analytics.gold_site_events must be built incrementally inside a Lakeflow Spark Declarative Pipeline: every refresh must process only the newly arrived files, exactly once, with the pipeline tracking how far it has read. Which declaration meets these requirements?

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  1. A. CREATE MATERIALIZED VIEW catalog.analytics.gold_site_events AS SELECT * FROM STREAM(read_files('s3://company-raw/site_events/', format => 'json'));
  2. B. CREATE VIEW catalog.analytics.gold_site_events AS SELECT * FROM STREAM(read_files('s3://company-raw/site_events/', format => 'json'));
  3. C. CREATE TABLE catalog.analytics.gold_site_events AS SELECT * FROM read_files('s3://company-raw/site_events/', format => 'json'); — then a scheduled job runs INSERT INTO ... SELECT * FROM read_files(...) to append new files
  4. D. CREATE OR REFRESH STREAMING TABLE catalog.analytics.gold_site_events AS SELECT * FROM STREAM(read_files('s3://company-raw/site_events/', format => 'json'));
Reveal answer

Correct answer: CREATE OR REFRESH STREAMING TABLE catalog.analytics.gold_site_events AS SELECT * FROM STREAM(read_files('s3://company-raw/site_events/', format => 'json'));

Reference: https://docs.databricks.com/aws/en/ldp/concepts/streaming-tables

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Official Answer (D): CREATE OR REFRESH STREAMING TABLE catalog.analytics.gold_site_events AS SELECT * FROM STREAM(read_files('s3://company-raw/site_events/', format => 'json'));

Ranvier · DBDEA

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