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Posted to commits@hudi.apache.org by "linliu-code (via GitHub)" <gi...@apache.org> on 2026/08/12 22:58:04 UTC
[PR] [WIP][HUDI] MERGE INTO silently no-ops when the source omits the partition column [hudi]
linliu-code opened a new pull request, #19610:
URL: https://github.com/apache/hudi/pull/19610
### Change Logs
**Draft / placeholder** — opened to track the issue upstream and to serve as the companion PR for an internal one. **The fix approach in this branch is known to be incomplete; see "Status" below.**
`MERGE INTO` against a **partitioned** table whose source query does not project the partition column **reports success while writing an empty commit** — 0 bytes, 0 files, 0 records, 0 errors. The target data is left untouched, with no error and no warning.
Reproduced on Spark 3.5, on `hoodie.table.version` both 6 and 9.
```sql
CREATE TABLE t (id BIGINT, name STRING, amount DOUBLE, ts BIGINT, dt STRING)
USING hudi PARTITIONED BY (dt)
TBLPROPERTIES (type='cow', primaryKey='id', preCombineField='ts');
INSERT INTO t VALUES (1,'a',10.0,1,'2026-08-11');
-- source projects the record key and ordering field, but NOT `dt`
MERGE INTO t AS tgt
USING (SELECT 1L AS id, 15.0 AS amount, 200L AS ts) AS s
ON tgt.id = s.id
WHEN MATCHED THEN UPDATE SET tgt.amount = s.amount, tgt.ts = s.ts;
-- statement succeeds; id=1 is still amount=10.0 / ts=1
```
`show_commits` afterwards:
```
commit_time action total_bytes files_added files_updated partitions records errors
20260811073208749 commit 0 0 0 0 0 0
```
Adding `dt` to the **source projection** alone — leaving the `ON` clause matching on the record key only — makes the merge apply correctly. The same statement on a **non-partitioned** table works unmodified. So the trigger is the source projection, not the join condition.
### Impact
Data-correctness / silent-no-op. A user's `MERGE INTO` reports success and changes nothing; there is no diagnostic distinguishing it from a legitimate no-match.
Note the asymmetry that makes this surprising: omitting the **ordering** field from the source raises a clear `MergeIntoFieldResolutionException`, whereas omitting the **partition** field is silent. In `MergeIntoHoodieTableCommand.checkSchemaMergeIntoCompatibility` the partition-column resolution is wrapped in a `try/catch` that discards `MergeIntoFieldResolutionException`, while the identical failure for the primary key is allowed to propagate.
### Status — why this is a draft
The change in this branch makes the partition column a hard error, mirroring the primary key. Internal CI shows that is **too strict**: it also rejects the *documented, supported* partial-update pattern, where the source omits the partition column and the update clause does not assign it, e.g. the existing test `Test merge into Allowed-patterns of assignment clauses` (table partitioned by `value`, `USING (SELECT 1 AS id, 1003 AS ts)`, `UPDATE SET h0.id = s0.id`) which runs with `hoodie.datasource.write.merge.into.partial.updates=true`.
So there are evidently (at least) two paths through this code — one where a missing partition column is handled by taking the partition from the matched target record, and one where it silently produces an empty commit. **Which condition separates them is still being investigated**; the partial-updates flag is the leading candidate, since the passing upstream test enables it and the failing production case did not.
Repointing this PR once that is settled. The likely shape is either narrowing the validation to the configuration where the no-op actually occurs, or fixing the write path so the partition is resolved from the target in that configuration too.
### Impact
Behaviour change for `MERGE INTO` on partitioned tables — currently silent data loss becomes either a clear error or a correct write, depending on the final approach.
### Risk level: medium
Touches `MergeIntoHoodieTableCommand` analysis-time validation on both the `hudi-spark3-common` and `hudi-spark4-common` copies. Existing `TestMergeIntoTable*` suites are the guard; internal CI has already surfaced one over-strictness regression, which is being addressed.
### Documentation Update
None required.
### Contributor's checklist
- [x] Read through [contributor's guide](https://hudi.apache.org/contribute/how-to-contribute)
- [x] Change Logs and Impact were stated clearly
- [ ] Adequate tests were added if applicable — tests added (`TestMergeIntoPartitionFieldResolution`, CoW + MOR) but **not yet green**; see Status
- [ ] CI passed
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "linliu-code (via GitHub)" <gi...@apache.org>.
linliu-code commented on code in PR #19610:
URL: https://github.com/apache/hudi/pull/19610#discussion_r3788854529
##########
hudi-spark-datasource/hudi-spark3-common/src/main/scala/org/apache/spark/sql/hudi/command/MergeIntoHoodieTableCommand.scala:
##########
@@ -266,6 +266,74 @@ case class MergeIntoHoodieTableCommand(mergeInto: MergeIntoTable) extends Hoodie
"ordering fields",
updatingActions.flatMap(_.assignments))
+ /**
+ * Mapping of the target table's partition columns onto the [[sourceTable]] expression that
+ * supplies each one, resolved the same way as the record-key and ordering fields.
+ *
+ * This is required, not optional. For a target table bearing a record key the incoming batch is
+ * written from the [[sourceTable]] alone (see [[getProcessedInputDf]]) and Hudi's index tagging
+ * is what identifies updates - tagging keys off `(recordKey, partitionPath)`. When the partition
+ * column reaches the writer unset, the key generator resolves it to the default partition, so
+ * tagging looks in the wrong partition, finds nothing, and treats every incoming record as
+ * not-matched. That is silently destructive rather than merely wrong:
+ *
+ * - with only `WHEN MATCHED` clauses the record falls through to [[HoodieRecord.SENTINEL]] in
+ * `ExpressionPayload#processNotMatchedRecord` and is dropped - the statement reports success
+ * and writes an *empty commit*;
+ * - with a `WHEN NOT MATCHED ... INSERT` clause the record is instead inserted into the default
+ * partition, **duplicating the primary key across two partitions** while the intended update
+ * is lost.
+ *
+ * Resolving the column here means the merge places records in the right partition whenever the
+ * value is derivable. Three sources are consulted, in order:
+ *
+ * 1. the `ON` condition, via [[recordKeyAttributeToConditionExpression]], which already
+ * enumerates partition fields but leaves them optional (see the "allow partition path to be
+ * part of the merge condition but not required" note there) - reused as-is so a column
+ * matched under a different source name (`ON t.dt = s.event_dt`) keeps working, and so the
+ * same target attribute is never contributed twice;
+ * 2. the source-table output and the MERGE assignments, via
+ * [[resolveFieldAssociationsBetweenSourceAndTarget]];
+ * 3. otherwise the statement is rejected, rather than letting the write silently corrupt the
+ * table.
+ *
+ * NOTE: this applies only to tables bearing a record key. A primary-keyless target takes the
+ * other branch of [[getProcessedInputDf]], where the source is left-outer-joined with the
+ * target and the meta columns are projected, and [[MergeIntoKeyGenerator.getPartitionPath]]
+ * reads `_hoodie_partition_path` off that meta - so a matched row is already placed in the
+ * right partition without the source carrying the column at all.
+ */
+ private lazy val partitionFieldsAssociatedExpressions: Seq[(Attribute, Expression)] =
+ if (!hasPrimaryKey() || hoodieCatalogTable.partitionFields.isEmpty) {
+ Seq.empty
+ } else {
+ val resolver = sparkSession.sessionState.conf.resolver
+ // Associations the ON-condition path has already produced; anything covered there needs no
+ // further resolution, and re-adding it would put two aliases for one column in the projection.
+ val resolvedFromCondition = recordKeyAttributeToConditionExpression
+ hoodieCatalogTable.partitionFields.toSeq.flatMap { partitionField =>
+ if (resolvedFromCondition.exists { case (attr, _) => resolver(attr.name, partitionField) }) {
+ Seq.empty
+ } else {
+ try {
+ resolveFieldAssociationsBetweenSourceAndTarget(
+ resolver,
+ mergeInto.targetTable,
+ mergeInto.sourceTable,
+ Seq(partitionField),
+ "partition fields",
+ updatingActions.flatMap(_.assignments) ++ insertingActions.flatMap(_.assignments))
Review Comment:
An assignment gives the record's *new* partition, not its current one — so for a partition-changing update on a non-global index (`update set t.dt = s.new_dt` where `new_dt` differs from the row's partition), tagging looks in `new_dt`, misses, and the record is dropped as `SENTINEL`: the empty commit this PR is fixing. The assignment test passes because `src_dt` equals the existing partition value; could we add a case with a differing value to pin down what actually happens there?
Relatedly, `orderingFieldsAssociatedExpressions` (`:267`) uses only `updatingActions` — with `insertingActions` in the union here, a merge whose INSERT clause alone names the partition column will tag *matched* records from it. Same applies to the spark4-common copy.
##########
hudi-spark-datasource/hudi-spark3-common/src/main/scala/org/apache/spark/sql/hudi/command/MergeIntoHoodieTableCommand.scala:
##########
@@ -266,6 +266,74 @@ case class MergeIntoHoodieTableCommand(mergeInto: MergeIntoTable) extends Hoodie
"ordering fields",
updatingActions.flatMap(_.assignments))
+ /**
+ * Mapping of the target table's partition columns onto the [[sourceTable]] expression that
+ * supplies each one, resolved the same way as the record-key and ordering fields.
+ *
+ * This is required, not optional. For a target table bearing a record key the incoming batch is
+ * written from the [[sourceTable]] alone (see [[getProcessedInputDf]]) and Hudi's index tagging
+ * is what identifies updates - tagging keys off `(recordKey, partitionPath)`. When the partition
+ * column reaches the writer unset, the key generator resolves it to the default partition, so
+ * tagging looks in the wrong partition, finds nothing, and treats every incoming record as
+ * not-matched. That is silently destructive rather than merely wrong:
+ *
+ * - with only `WHEN MATCHED` clauses the record falls through to [[HoodieRecord.SENTINEL]] in
+ * `ExpressionPayload#processNotMatchedRecord` and is dropped - the statement reports success
+ * and writes an *empty commit*;
+ * - with a `WHEN NOT MATCHED ... INSERT` clause the record is instead inserted into the default
+ * partition, **duplicating the primary key across two partitions** while the intended update
+ * is lost.
+ *
+ * Resolving the column here means the merge places records in the right partition whenever the
+ * value is derivable. Three sources are consulted, in order:
+ *
+ * 1. the `ON` condition, via [[recordKeyAttributeToConditionExpression]], which already
+ * enumerates partition fields but leaves them optional (see the "allow partition path to be
+ * part of the merge condition but not required" note there) - reused as-is so a column
+ * matched under a different source name (`ON t.dt = s.event_dt`) keeps working, and so the
+ * same target attribute is never contributed twice;
+ * 2. the source-table output and the MERGE assignments, via
+ * [[resolveFieldAssociationsBetweenSourceAndTarget]];
+ * 3. otherwise the statement is rejected, rather than letting the write silently corrupt the
+ * table.
+ *
+ * NOTE: this applies only to tables bearing a record key. A primary-keyless target takes the
+ * other branch of [[getProcessedInputDf]], where the source is left-outer-joined with the
+ * target and the meta columns are projected, and [[MergeIntoKeyGenerator.getPartitionPath]]
+ * reads `_hoodie_partition_path` off that meta - so a matched row is already placed in the
+ * right partition without the source carrying the column at all.
+ */
+ private lazy val partitionFieldsAssociatedExpressions: Seq[(Attribute, Expression)] =
+ if (!hasPrimaryKey() || hoodieCatalogTable.partitionFields.isEmpty) {
Review Comment:
Should this be gated on the index being global? For `hoodie.index.type = RECORD_INDEX` (global, and `hoodie.record.index.update.partition.path` defaults to false), `tagGlobalLocationBackToRecords` takes the branch at `HoodieIndexUtils:656-663` and re-keys the incoming record to the existing location's partition, so
```sql
MERGE INTO t USING (select 1L as id, 15.0 as amount) s
ON t.id = s.id
WHEN MATCHED THEN UPDATE SET t.amount = s.amount
```
on a partitioned table updates correctly today and would now be rejected. Same for `GLOBAL_SIMPLE`/`GLOBAL_BLOOM` with `update.partition.path=false`.
Worth noting `useGlobalIndex` (`:1199`) returns the value of `update.partition.path`, so it's true precisely when the guard *isn't* needed — the check would need "is global AND !updatePartitionPath". The existing global-index merge test (`TestMergeIntoTable.scala:242`) projects the partition column, so CI wouldn't flag this. Same applies to the spark4-common copy.
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/dml/others/TestMergeIntoPartitionFieldResolution.scala:
##########
@@ -0,0 +1,387 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.spark.sql.hudi.dml.others
+
+import org.apache.hudi.common.table.timeline.TimelineUtils
+import org.apache.hudi.testutils.HoodieClientTestUtils.createMetaClient
+
+import org.apache.spark.sql.hudi.common.HoodieSparkSqlTestBase
+
+/**
+ * Regression coverage for MERGE INTO partition-column resolution.
+ *
+ * For a target table bearing a record key, the incoming batch is written from the source alone
+ * and Hudi's index tagging identifies updates, keying off `(recordKey, partitionPath)`. Before the
+ * fix, a partition column the source did not carry was never back-filled into the source
+ * projection (only record-key and ordering columns were), so the key generator resolved it to the
+ * default partition and tagging looked in the wrong place. Every incoming record came back
+ * not-matched, which is silently destructive in two different ways depending on the clauses:
+ *
+ * - `WHEN MATCHED` only: the record falls through to HoodieRecord.SENTINEL in
+ * `ExpressionPayload#processNotMatchedRecord` and is dropped - the statement reports success and
+ * writes an EMPTY COMMIT, leaving the target untouched.
+ * - `WHEN NOT MATCHED ... INSERT` present: the record is inserted into the default partition
+ * instead, DUPLICATING THE PRIMARY KEY across two partitions while the intended update is lost.
+ *
+ * The assertions below deliberately check the resulting rows AND their `_hoodie_partition_path`,
+ * not merely that the data is unchanged. "Unchanged" is exactly what the dropped-record bug
+ * produces, so a test asserting only that passes vacuously in the presence of this defect.
+ */
+class TestMergeIntoPartitionFieldResolution extends HoodieSparkSqlTestBase {
+
+ private val expectedError = "Failed to resolve partition fields"
+
+ private def createPartitionedTable(tableName: String, tableType: String, location: String): Unit =
+ spark.sql(
+ s"""
+ |create table $tableName (
+ | id bigint,
+ | name string,
+ | amount double,
+ | ts bigint,
+ | dt string
+ |) using hudi
+ | partitioned by (dt)
+ | tblproperties (
+ | type = '$tableType',
+ | primaryKey = 'id',
+ | preCombineField = 'ts'
+ | )
+ | location '$location'
+ """.stripMargin)
+
+ Seq("cow", "mor").foreach { tableType =>
+ test(s"Test MergeInto rejects an update whose source omits the partition column ($tableType)") {
+ withTempDir { tmp =>
+ val tableName = generateTableName
+ createPartitionedTable(tableName, tableType, s"${tmp.getCanonicalPath}/$tableName")
+ spark.sql(s"insert into $tableName values (1, 'a', 10.0, 1, '2026-08-11')")
+
+ // `dt` appears in neither the source output, the ON condition, nor the assignments.
+ // Before the fix this reported success and wrote an empty commit.
+ checkExceptionContain(
+ s"""
+ |merge into $tableName as t
+ |using (
+ | select 1L as id, 15.0 as amount, 200L as ts
+ |) as s
+ |on t.id = s.id
+ |when matched then update set t.amount = s.amount, t.ts = s.ts
+ """.stripMargin)(expectedError)
+
+ // Target untouched, and still a single row in its original partition.
+ checkAnswer(s"select id, amount, ts, dt, _hoodie_partition_path from $tableName")(
+ Seq(1L, 10.0, 1L, "2026-08-11", "dt=2026-08-11")
+ )
+ }
+ }
+ }
+
+ Seq("cow", "mor").foreach { tableType =>
+ test(s"Test MergeInto with an INSERT clause cannot duplicate the key into the default partition ($tableType)") {
+ withTempDir { tmp =>
+ val tableName = generateTableName
+ createPartitionedTable(tableName, tableType, s"${tmp.getCanonicalPath}/$tableName")
+ spark.sql(s"insert into $tableName values (1, 'a', 10.0, 1, '2026-08-11')")
+
+ // The most damaging shape: with a NOT MATCHED clause the mis-partitioned record used to be
+ // INSERTED into the default partition, yielding two rows with id=1 in different partitions
+ // (name/dt null on the new one) while the intended update never landed.
+ checkExceptionContain(
+ s"""
+ |merge into $tableName as t
+ |using (
+ | select 1L as id, 99.0 as amount, 9L as ts
+ |) as s
+ |on t.id = s.id
+ |when matched then update set t.amount = s.amount, t.ts = s.ts
+ |when not matched then insert (id, amount, ts) values (s.id, s.amount, s.ts)
+ """.stripMargin)(expectedError)
+
+ // Exactly one row, in the right partition - no duplicate key, no default-partition row.
+ checkAnswer(s"select count(*) from $tableName")(Seq(1L))
+ checkAnswer(s"select id, amount, dt, _hoodie_partition_path from $tableName")(
+ Seq(1L, 10.0, "2026-08-11", "dt=2026-08-11")
+ )
+ }
+ }
+ }
+
+ Seq("cow", "mor").foreach { tableType =>
+ test(s"Test MergeInto applies when the source projects the partition column ($tableType)") {
Review Comment:
Could we add a `when matched then delete` case? `DeleteAction` carries no assignments, so a delete-only merge whose source omits the partition column now hits the new throw via a path none of the nine cases exercise. Previously it wrote an empty commit and deleted nothing, so rejecting looks right — just untested, and it's the common CDC shape.
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5277981570
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5321029580
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5278928941
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* e9e95021e62fc801573b3dad17c01db0beaae336 Azure: [SUCCESS](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16268)
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5301804315
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## CI report:
* 52ec953970d2cc96397d8a470a4061077b8bce60 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16315)
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5277929010
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## CI report:
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* e9e95021e62fc801573b3dad17c01db0beaae336 UNKNOWN
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5401708110
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5320052067
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua merged PR #19610:
URL: https://github.com/apache/hudi/pull/19610
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5401775209
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5402782328
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* b5a27d33b863db30e9bddf140292eaabfa190b00 Azure: [SUCCESS](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16513)
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Re: [PR] fix(spark-sql): MERGE INTO silently no-ops when source omits the partition column [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5273819726
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5503554459
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5296613394
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5301644261
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5285567247
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5503512842
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5301731831
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5297402790
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## CI report:
* 4360211cf8f43518d035dea5d6b547de0bcc2ce0 Azure: [SUCCESS](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16310)
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5303105881
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## CI report:
* 599553917efb5156fbaea576080d597624d5e2bf Azure: [SUCCESS](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16318)
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Re: [PR] fix(spark-sql): MERGE INTO silently no-ops when source omits the partition column [hudi]
Posted by "codecov-commenter (via GitHub)" <gi...@apache.org>.
codecov-commenter commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5273894552
## [Codecov](https://app.codecov.io/gh/apache/hudi/pull/19610?dropdown=coverage&src=pr&el=h1&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache) Report
:white_check_mark: All modified and coverable lines are covered by tests.
:white_check_mark: Project coverage is 77.50%. Comparing base ([`b2174b6`](https://app.codecov.io/gh/apache/hudi/commit/b2174b6f9ea30235cabf39d8269f179e9f670a87?dropdown=coverage&el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache)) to head ([`ada5def`](https://app.codecov.io/gh/apache/hudi/commit/ada5def7bff7bb6b8fe01e6248ff2148439e3269?dropdown=coverage&el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache)).
<details><summary>Additional details and impacted files</summary>
```diff
@@ Coverage Diff @@
## master #19610 +/- ##
=========================================
Coverage 77.50% 77.50%
Complexity 32862 32862
=========================================
Files 2524 2524
Lines 139355 139355
Branches 16747 16747
=========================================
Hits 108002 108002
Misses 23781 23781
Partials 7572 7572
```
| [Components](https://app.codecov.io/gh/apache/hudi/pull/19610/components?src=pr&el=components&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache) | Coverage Δ | |
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| [hudi-hadoop](https://app.codecov.io/gh/apache/hudi/pull/19610/components?src=pr&el=component&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache) | `68.94% <ø> (ø)` | |
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| [hudi-cloud](https://app.codecov.io/gh/apache/hudi/pull/19610/components?src=pr&el=component&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache) | `64.06% <ø> (ø)` | |
| [hudi-kafka-connect](https://app.codecov.io/gh/apache/hudi/pull/19610/components?src=pr&el=component&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache) | `53.20% <ø> (ø)` | |
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| [hadoop-mr-java-client](https://app.codecov.io/gh/apache/hudi/pull/19610/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache) | `43.83% <ø> (-0.02%)` | :arrow_down: |
Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache#carryforward-flags-in-the-pull-request-comment) to find out more.
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Re: [PR] fix(spark-sql): MERGE INTO silently no-ops when source omits the partition column [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5274177102
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## CI report:
* ada5def7bff7bb6b8fe01e6248ff2148439e3269 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16258)
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "linliu-code (via GitHub)" <gi...@apache.org>.
linliu-code commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5401664515
Re-synced with the internal copy after the latest review round — both are now `+944/-29` over the same 4 files.
Changes in this push, per review on onehouseinc/hudi-internal#2197 (keeping the detailed discussion on that thread, as agreed):
- `globalIndexTypes` and `isGlobalIndexEnabled` folded into a single map keyed by index type, so an index cannot be recorded as global without also recording the `update.partition.path` config that decides the re-keying exemption. Semantics unchanged — unmapped still yields `false`.
- Comments cut by about half (-94 lines net across both spark copies), keeping only what is not visible in the code.
- `w/in` -> `within` in the resolution error.
- New CoW test covering the accepting half of `update.partition.path=true`: a source that carries a *new* partition value must relocate the record. It does; mutation-checked. Plus a value assertion in the dedupe test and an ENG ref where MOR is excluded.
31 tests, 31 passed locally.
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5286550581
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* 5bba57821f5dca899765df85c87d5a50a0d4e56b Azure: [SUCCESS](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16281)
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5319996439
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* 599553917efb5156fbaea576080d597624d5e2bf Azure: [SUCCESS](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16318)
* f07accea1351e6050b5fa552f29970f7be3a1164 UNKNOWN
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Re: [PR] fix(spark-sql): MERGE INTO silently no-ops when source omits the partition column [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5273875662
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## CI report:
* ada5def7bff7bb6b8fe01e6248ff2148439e3269 Azure: [PENDING](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16258)
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5296561039
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* 5bba57821f5dca899765df85c87d5a50a0d4e56b Azure: [SUCCESS](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16281)
* 4360211cf8f43518d035dea5d6b547de0bcc2ce0 UNKNOWN
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5302744900
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5302723674
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## CI report:
* 52ec953970d2cc96397d8a470a4061077b8bce60 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=16315)
* 599553917efb5156fbaea576080d597624d5e2bf UNKNOWN
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5285724916
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Re: [PR] fix(spark-sql): resolve MERGE INTO partition columns so records are not mis-partitioned [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on PR #19610:
URL: https://github.com/apache/hudi/pull/19610#issuecomment-5286167154
The diagnosis looks right to me, and I agree the existing checks don't cover this shape. But there are already two places in this file that resolve partition columns, and the new lazy val is unaware of both. I think that leaves a regression and a duplicate-projection case, and the consolidation opportunity is with the second one.
**Existing check 1: `recordKeyAttributeToConditionExpression`.** It already enumerates partition fields (`partitionAndKeyFields ++ partitionPathFields...`) and already feeds them into `requiredAttributesMap`, but only from the `ON` condition, and the throw is gated on `rk._1.equals("primaryKey")` so partition columns stay optional (see the `//allow partition path to be part of the merge condition but not required` note).
**Existing check 2: `checkSchemaMergeIntoCompatibility`.** It resolves each partition field with the same helper this PR calls, purely to type-check it, and then discards the failure:
```scala
} catch {
case _: MergeIntoFieldResolutionException =>
}
```
That swallow is what let this bug survive. It's also where I'd consolidate: have `checkSchemaMergeIntoCompatibility` consume the new `partitionFieldsAssociatedExpressions` for its `validateDataTypes` call instead of re-resolving per field, and drop the try/catch, which becomes dead once resolution fails earlier. That removes the duplicated resolution and the trap.
I don't think the fix can move wholesale into `validate()`, for what it's worth: the association is consumed by `requiredAttributesMap` to back-fill the column, and `checkSchemaMergeIntoCompatibility` returns `Unit`, so putting it there would reduce this to "reject instead of corrupt" and lose the assignment-derived case. Keeping it next to `orderingFieldsAssociatedExpressions` seems right.
Two things worth checking before/while consolidating, both from concatenating the new lazy val at `requiredAttributesMap` without reconciling against check 1:
1. **Regression.** `resolveFieldAssociationsBetweenSourceAndTarget` looks at source output, then assignments. It never consults the merge condition. So `ON t.id = s.id AND t.dt = s.date_col` with no `dt` assignment resolves today via check 1 and would now be rejected. The description lists the `ON` condition as a derivation source, but the helper doesn't read it. Suggest falling back to the associations check 1 already produced before throwing, and adding a test for the differently-named-source-column shape.
2. **Duplicate projection.** When a partition column is derivable from an assignment and also named in the `ON` condition, both paths emit an entry for the same target attribute. `requiredAttributesMap` does no `distinct`, and the `missingAttributesMap.flatMap` below adds one `Alias(..., "dt")` per entry, so the projection can end up with two `dt` columns. Suggest deduping `requiredAttributesMap` by target attribute.
Minor: the error message is quite long for a thrown exception. The remedy sentence ("project the partition column(s) [...] in the source query") is the actionable part; the two failure modes read more like a code comment than something a user needs at the prompt, and they're already captured in the javadoc.
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