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How can a data engineer count all records updated in the source table using Delta Lake's Change Data Feed?
A
spark.read.format("delta") \ .option("readChangeFeed", "true") \ .option("startingVersion", 0) \ .table("source") \ .where(col('_change_type') == 'update_postimage') \ .count()
B
spark.read.format("delta") \ .option("readChangeFeed", "true") \ .option("startingVersion", 0) \ .table("source") \ .where(col('_change_type') == 'update_preimage') \ .count()
C
spark.read.format("delta") \ .option("readChangeFeed", "true") \ .option("startingVersion", 0) \ .table("source") \ .where(col('_change_type') == 'update') \ .count()
D
All of the above
E
Both A and B
