amogh-jahagirdar commented on code in PR #13555:
URL: https://github.com/apache/iceberg/pull/13555#discussion_r2217975460
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spark/v4.0/spark/src/main/java/org/apache/iceberg/spark/source/SparkWriteBuilder.java:
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@@ -120,12 +120,15 @@ public WriteBuilder overwrite(Filter[] filters) {
@Override
public Write build() {
// The write schema should only include row lineage in the output if it's
an overwrite
- // operation.
+ // operation or if it's a compaction.
// In any other case, only null row IDs and sequence numbers would be
produced which
// means the row lineage columns can be excluded from the output files
- boolean writeIncludesRowLineage = TableUtil.supportsRowLineage(table) &&
overwriteFiles;
+ boolean writeIncludesRowLineage =
+ TableUtil.supportsRowLineage(table)
+ && (overwriteFiles || writeConf.rewrittenFileSetId() != null);
StructType sparkWriteSchema = dsSchema;
- if (writeIncludesRowLineage) {
+ if (writeIncludesRowLineage
+ && !dsSchema.exists(field ->
field.name().equals(MetadataColumns.ROW_ID.name()))) {
Review Comment:
Since we're hijacking the Spark table schema to include the row lineage
fields, the output schema Spark hands back to the writer will naturally have
the row lineage fields as well. The check is required to prevent adding to the
spark output schema twice. I separated this into two booleans
`writeRequiresRowLineage` and `writeAlreadyIncludesRowLineage` for more clarity
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