Explanation:
In Delta Lake MERGE semantics, the operation only executes actions for the clauses provided.
WHEN NOT MATCHED clause. This clause triggers only when a source row does not find a corresponding event_id in the target table.event_id from new_events matches an event_id in events, the engine looks for a WHEN MATCHED clause. Since no such clause exists in this snippet, the target row remains unchanged and the source row is effectively ignored.WHEN MATCHED THEN UPDATE or WHEN MATCHED THEN DELETE clause.INSERT action is specifically nested under the NOT MATCHED condition.According to Databricks documentation: 'If none of the WHEN MATCHED conditions evaluate to true for a source and target row pair that matches the merge_condition, then the target row is left unchanged.'
Ultimate access to all questions.
A junior data engineer has implemented the following SQL code to update a Delta table named events using data from a source view called new_events:
MERGE INTO events
USING new_events
ON events.event_id = new_events.event_id
WHEN NOT MATCHED THEN
INSERT *
MERGE INTO events
USING new_events
ON events.event_id = new_events.event_id
WHEN NOT MATCHED THEN
INSERT *
Both the table and the view share the same schema and utilize event_id as a unique primary key. Given this code, what will happen to records in new_events that have an event_id already existing in the events table?
A
The existing records with matching event_id will be deleted and replaced with the new source data.
B
The existing records with matching event_id will be updated using the attributes from new_events.
C
The new records will be disregarded (ignored).
D
The new records will be merged with the existing ones into a nested structure.
E
The new records will be inserted as separate entries, resulting in duplicate event_id values in the target table.
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