A data engineer enables Delta Change Data Feed on a table and reads the feed using `spark.read.format(\delta\).option( eadChangeFeed\, rue\)`. Which column is added to each output row to indicate the type of change?

Question

A data engineer enables Delta Change Data Feed on a table and reads the feed using `spark.read.format(\delta\).option(eadChangeFeed\, 	rue\)`. Which column is added to each output row to indicate the type of change?

Accepted Answer

C. `_change_type`. When reading Delta Change Data Feed, each row in the output includes a `_change_type` column. Values include: `insert` (newly inserted rows), `update_preimage` (the row before an update), `update_postimage` (the row after an update), and `delete`. Two additional metadata columns `_commit_version` and `_commit_timestamp` are also included.

A data engineer enables Delta Change Data Feed on a table and reads the feed using `spark.read.format(\delta\).option(\readChangeFeed\, \true\)`. Which column is added to each output row to indicate the type of change?

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A data engineer enables Delta Change Data Feed on a table and reads the feed using spark.read.format(\delta\).option(\readChangeFeed\, \true\). Which column is added to each output row to indicate the type of change?

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A data engineer enables Delta Change Data Feed on a table and reads the feed using `spark.read.format(\delta\).option(\readChangeFeed\, \true\)`. Which column is added to each output row to indicate the type of change?