kevinjqliu opened a new issue, #18601:
URL: https://github.com/apache/iceberg/issues/18601
### Apache Iceberg version
1.12.0 (latest release)
### Query engine
Spark
### Please describe the bug 🐞
Vectorized reads of a projected shredded VARIANT fail when `SparkBatch`
can't detect shredding at plan time. Detection relies on the
`write.parquet.shred-variants` table property and per-file variant lower
bounds. Shredding can be enabled via session conf or write option, and shredded
arrays never get variant bounds.
**Repro** (Spark 4.1, main):
```sql
CREATE TABLE t (id BIGINT, v VARIANT) USING iceberg TBLPROPERTIES
('format-version'='3');
SET spark.sql.iceberg.shred-variants=true;
INSERT INTO t VALUES (1, parse_json('{"a": [1, 2]}')), (2, parse_json('{"a":
[3]}'));
SELECT id, v FROM t; -- fails
SET spark.sql.iceberg.vectorization.enabled=false;
SELECT id, v FROM t; -- OK
```
```
java.lang.UnsupportedOperationException: Unsupported variant: shredded
typed_value primitive
at
org.apache.iceberg.arrow.vectorized.VectorizedVariantVisitor.primitive(VectorizedVariantVisitor.java:97)
...
at
org.apache.iceberg.spark.data.vectorized.VectorizedSparkParquetReaders.buildReader(VectorizedSparkParquetReaders.java:61)
```
Originally raised in #17736 (closed unmerged). Related to #18430, which
covers the unprojected case; its fix #18434 doesn't address this one.
### Willingness to contribute
- [ ] I can contribute a fix for this bug independently
- [ ] I would be willing to contribute a fix for this bug with guidance from
the Iceberg community
- [ ] I cannot contribute a fix for this bug at this time
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