jose-torres commented on code in PR #57490:
URL: https://github.com/apache/spark/pull/57490#discussion_r3648940929
##########
sql/pipelines/src/main/scala/org/apache/spark/sql/pipelines/autocdc/Scd2BatchProcessor.scala:
##########
@@ -1410,6 +1395,44 @@ object Scd2BatchProcessor {
AutoCdcReservedNames.cdcMetadataColName
)
+ /**
+ * Resolve [[ChangeArgs.trackHistorySelection]] against `schema` and return
the field names of
+ * the history-tracking columns: the eligible user-data columns (those that
are neither
+ * [[ChangeArgs.keys]] nor framework reserved columns) filtered through the
selection.
+ *
+ * This is the single source of truth for which columns define an SCD2 run.
It is called both
+ * per-microbatch (against the reconciled dataframe's schema) and at
+ * [[org.apache.spark.sql.pipelines.graph.AutoCdcMergeFlow]] construction
time (against the
+ * user-selected source schema), so an unresolvable or ineligible selection
fails fast with a
+ * user-actionable [[org.apache.spark.sql.AnalysisException]] instead of
surfacing mid-stream
+ * (SPARK-58313).
Review Comment:
nit: spark ticket comment as per other PR
##########
sql/pipelines/src/main/scala/org/apache/spark/sql/pipelines/autocdc/Scd2BatchProcessor.scala:
##########
@@ -922,28 +923,12 @@ case class Scd2BatchProcessor(
* the eligible user-data columns (those not in [[ChangeArgs.keys]] or the
framework
* reserved set) filtered through [[ChangeArgs.trackHistorySelection]].
*/
- private def computeTrackedHistoryColumns(df: DataFrame): Seq[String] = {
- val conf = df.sparkSession.sessionState.conf
- val resolver = conf.resolver
-
- val keyColNames = changeArgs.keys.map(_.name)
- val reservedColNames = Scd2BatchProcessor.reservedFrameworkColNames
-
- val eligibleSchema = StructType(df.schema.fields.filterNot { field =>
- reservedColNames.exists(resolver(_, field.name)) ||
- keyColNames.exists(resolver(_, field.name))
- })
-
- ColumnSelection
- .applyToSchema(
- schemaName = "trackHistorySelection",
- schema = eligibleSchema,
- columnSelection = changeArgs.trackHistorySelection,
- caseSensitive = conf.caseSensitiveAnalysis
- )
- .fieldNames
- .toImmutableArraySeq
- }
+ private def computeTrackedHistoryColumns(df: DataFrame): Seq[String] =
+ Scd2BatchProcessor.computeTrackedHistoryColumns(
+ schema = df.schema,
+ changeArgs = changeArgs,
+ caseSensitive = df.sparkSession.sessionState.conf.caseSensitiveAnalysis
Review Comment:
I guess I'm OK with this, it's unlikely we'll introduce some third
resolution mode all of the sudden.
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