hudi-agent commented on code in PR #18914:
URL: https://github.com/apache/hudi/pull/18914#discussion_r3368787285
##########
hudi-utilities/src/main/java/org/apache/hudi/utilities/transform/ErrorTableAwareChainedTransformer.java:
##########
@@ -55,8 +55,9 @@ public Dataset<Row> apply(JavaSparkContext jsc, SparkSession
sparkSession, Datas
for (TransformerInfo transformerInfo : transformers) {
Transformer transformer = transformerInfo.getTransformer();
dataset = transformer.apply(jsc, sparkSession, dataset,
transformerInfo.getProperties(properties, transformers));
- // validate in every stage to ensure ErrorRecordColumn not dropped by
one of the transformer and added by next transformer.
- ErrorTableUtils.validate(dataset);
+ // Re-inject _corrupt_record if the transformer dropped it (e.g. custom
JAR transformers
+ // that do column projection like ColumnFilter with mode=include).
+ dataset =
ErrorTableUtils.addNullValueErrorTableCorruptRecordColumn(dataset);
Review Comment:
🤖 If an earlier transformer in the chain populates `_corrupt_record` with
actual error rows and a later transformer drops it, this silently re-injects it
as a null column — the previously captured error data is lost without warning.
Previously `validate()` would have surfaced this as an exception. Is that an
acceptable tradeoff for the column-projection use case, or worth at least
logging a warn when the column was dropped after being non-null? @yihua
<sub><i>- AI-generated; verify before applying. React 👍/👎 to flag
quality.</i></sub>
##########
hudi-utilities/src/test/java/org/apache/hudi/utilities/functional/TestErrorTableAwareChainedTransformer.java:
##########
@@ -86,7 +87,45 @@ public void testForErrorRecordColumn() {
TypedProperties properties = new TypedProperties();
properties.setProperty(ERROR_TABLE_ENABLED.key(), "true");
ErrorTableAwareChainedTransformer transformer = new
ErrorTableAwareChainedTransformer(Arrays.asList(t1, t2, t3));
- assertThrows(HoodieValidationException.class, () ->
transformer.apply(jsc(), spark(), original, properties));
+ Dataset<Row> transformed = transformer.apply(jsc(), spark(), original,
properties);
+
+ assertArrayEquals(new String[]{"foo",
ERROR_TABLE_CURRUPT_RECORD_COL_NAME}, transformed.columns());
+ assertEquals(2, transformed.count());
+ }
+
+ @Test
+ void testCustomColumnProjectionPreservesCorruptRecord() {
+ // Single custom transformer doing column projection — drops
_corrupt_record.
+ Dataset<Row> original = getTestDataset();
+
+ Transformer columnFilter = (jsc, sparkSession, dataset, props) ->
dataset.select("foo");
+ TypedProperties properties = new TypedProperties();
+ properties.setProperty(ERROR_TABLE_ENABLED.key(), "true");
+ ErrorTableAwareChainedTransformer transformer =
+ new ErrorTableAwareChainedTransformer(Arrays.asList(columnFilter));
+ Dataset<Row> transformed = transformer.apply(jsc(), spark(), original,
properties);
+
+ assertArrayEquals(new String[]{"foo",
ERROR_TABLE_CURRUPT_RECORD_COL_NAME}, transformed.columns());
+ assertEquals(2, transformed.count());
+ assertEquals(2, transformed.filter(new
Column(ERROR_TABLE_CURRUPT_RECORD_COL_NAME).isNull()).count());
+ }
+
+ @Test
+ void testTransformerPreservingCorruptRecordIsNoOp() {
+ // Transformer that keeps all columns — re-injection is a no-op.
+ Dataset<Row> original = getTestDataset();
+
+ Transformer keepAll = (jsc, sparkSession, dataset, properties) ->
dataset.withColumn("foo",
+ dataset.col("foo").cast(IntegerType));
+ TypedProperties properties = new TypedProperties();
Review Comment:
🤖 nit: the lambda parameter here is named `properties`, while the sibling
test `testCustomColumnProjectionPreservesCorruptRecord` uses `props` for the
same position — could you use `props` here too for consistency? It also avoids
the visual confusion with `TypedProperties properties` declared two lines below.
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quality.</i></sub>
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