![]() The delete action deletes the matched row.Įach whenMatched clause can have an optional condition. The update action in merge only updates the specified columns (similar to the update operation) of the matched target row. WhenMatched clauses can have at most one update and one delete action. These clauses have the following semantics. WhenMatched clauses are executed when a source row matches a target table row based on the match condition. There can be any number of whenMatched and whenNotMatched clauses. Here is a detailed description of the merge programmatic operation. Caching the source data may not address this issue, as cache invalidation can cause the source data to be recomputed partially or completely (for example when a cluster loses some of it executors when scaling down). If you cannot avoid using non-deterministic functions, consider saving the source data to storage, for example as a temporary Delta table. Some common examples of nondeterministic expressions include the current_date and current_timestamp functions. If your source data contains nondeterministic expressions, multiple passes on the source data can produce different rows causing incorrect results. See the Delta Lake APIs for Scala, Java, and Python syntax details.ĭelta Lake merge operations typically require two passes over the source data. as ( "updates" ), "people.id = updates.id" ). load ( "/tmp/delta/people-10m-updates" ) deltaTable. forPath ( spark, "/tmp/delta/people-10m" ) Dataset dfUpdates = spark. Import io.delta.tables.* import .functions import DeltaTable deltaTable = DeltaTable. insertExpr ( Map ( "id" -> "updates.id", "firstName" -> "updates.firstName", "middleName" -> "updates.middleName", "lastName" -> "updates.lastName", "gender" -> "updates.gender", "birthDate" -> "updates.birthDate", "ssn" -> "updates.ssn", "salary" -> "updates.salary" )). updateExpr ( Map ( "id" -> "updates.id", "firstName" -> "updates.firstName", "middleName" -> "updates.middleName", "lastName" -> "updates.lastName", "gender" -> "updates.gender", "birthDate" -> "updates.birthDate", "ssn" -> "updates.ssn", "salary" -> "updates.salary" )). forPath ( spark, "tmp/delta/people-10m-updates" ) val dfUpdates = deltaTablePeopleUpdates. forPath ( spark, "/tmp/delta/people-10m" ) val deltaTablePeopleUpdates = DeltaTable.
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