A data engineer is configuring a Databricks databricks video
data-engineer-associate video for a data engineer is configuring a Databricks Auto Loader stream to ingest JSON data from an S3 bucket. The pipeline should fail
Full Certification Question
A data engineer is configuring a Databricks Auto Loader stream to ingest JSON data from an S3 bucket. The pipeline should fail when new columns are detected in the incoming data, but those new columns should still be added to the schema so that subsequent runs can resume successfully with the updated schema. Existing columns must retain their data types. spark . readStream . format ( "cloudFiles" ) . option ( "cloudFiles.format" , "json" ) . option ( "cloudFiles.schemaLocation" , "s3://checkpoints/orders" ) . option ( "cloudFiles.schemaEvolutionMode" , "_______________" ) . load ( "s3://shop/raw/orders/json/" ) . writeStream . option ( "checkpointLocation" , "s3://checkpoints/orders" ) . start ( "orders_table" ) Which option correctly fills in the blank to meet the specified requirement ?