aokolnychyi commented on code in PR #12058:
URL: https://github.com/apache/iceberg/pull/12058#discussion_r1926221855
##########
spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/data/vectorized/ColumnarBatchUtil.java:
##########
@@ -31,10 +31,13 @@ public class ColumnarBatchUtil {
private ColumnarBatchUtil() {}
+ // spotless:off
/**
Review Comment:
I just realized the example actually doesn't fit anymore as we only compute
the mapping, not the isDeleted array. Also, what if we use `<pre>` blocks to
avoid disabling Spotless?
```
/**
* Builds a row ID mapping inside a batch to skip deleted rows.
*
* <pre>
* Initial state
* Data values: [v0, v1, v2, v3, v4, v5, v6, v7]
* Row ID mapping: [0, 1, 2, 3, 4, 5, 6, 7]
*
* Apply position deletes
* Position deletes: 2, 6
* Row ID mapping: [0, 1, 3, 4, 5, 7, -, -] (6 live records)
*
* Apply equality deletes
* Equality deletes: v1, v2, v3
* Row ID mapping: [0, 4, 5, 7, -, -, -, -] (4 live records)
* </pre>
*
* @param columnVectors the array of column vectors for the batch
* @param deletes the delete filter containing delete information
* @param rowStartPosInBatch the starting position of the row in the batch
* @param batchSize the size of the batch
* @return the mapping array and the number of live rows, or {@code null} if
nothing is deleted
*/
```
I think this example would be more descriptive as it is clear what the data
values are and which records are removed by equality deletes.
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