aokolnychyi commented on code in PR #5665:
URL: https://github.com/apache/iceberg/pull/5665#discussion_r960111505
##########
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/SparkDataFile.java:
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@@ -84,10 +93,31 @@ public SparkDataFile(Types.StructType type, StructType
sparkType) {
sortOrderIdPosition = positions.get("sort_order_id");
}
+ private void wrapPartitionSpec(GenericRowWithSchema specRow) {
+ // We get all the partition fields, but want to project to the current one
+ StructType wrappedPartitionStruct = specRow.schema();
+
+ if (!wrappedPartitionStruct.equals(currentWrappedPartitionStruct)) {
+ this.currentWrappedPartitionStruct = wrappedPartitionStruct;
+
+ // The original IDs are lost in translation, therefore we apply the ones
that we know
Review Comment:
Yeah, we need something closer to what we have in `SparkPositionDeltaWrite`,
where we essentially solve the same problem (the incoming partition tuple may
have more columns that the spec we are trying to write).
We can pass `Broadcast<Table> table` to `writeManifest`, which would allow
us to construct the union partition type as well as have access to the spec we
are trying to write to.
I am not yet sure where the projection should be. We could either change the
constructor of `SparkDataFile` and init it there.
```
public SparkDataFile(PartitionSpec spec, Types.StructType partitionType,
StructType sparkType) {
...
this.partitionWrapper = new SparkStructLike(partitionType);
this.partitionProjection = StructProjection.create(partitionType,
spec.partitionType());
...
}
```
Or pass a precomputed `StructProjection partitionProjection`, which we would
build in `writeManifest`.
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