8000 [SPARK-53598][SQL] Check the existence of numParts before reading large table property by pan3793 · Pull Request #52355 · apache/spark · GitHub
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[SPARK-53598][SQL] Check the existence of numParts before reading large table property #52355

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@pan3793 pan3793 commented Sep 16, 2025 •
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What changes were proposed in this pull request?

This PR proposes to fix a regression caused by SPARK-33812 (de234ee 3.2.0).

We hit an error when upgrading Spark from 3.1 to 3.3, the table is a Hive SerDe Parquet table, which TBLPROPERTIES looks like malformed (not sure how this happen), the table can be read and write normally with Spark 3.1, but fails on reading with Spark 3.3.

-- Hive DDL
CREATE EXTERNAL TABLE `foo`.`bar`(
  `id` bigint,
  ...
) PARTITIONED BY (`dt` string)
ROW FORMAT SERDE 
  'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe' 
STORED AS INPUTFORMAT
  'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat' 
OUTPUTFORMAT 
  'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat'
LOCATION
  'hdfs://...'
TBLPROPERTIES (
  ...
  'spark.sql.sources.schema.partCol.0'='dt',
  'transient_lastDdlTime'='1727333678')

org.apache.spark.sql.AnalysisException: Cannot read table property 'spark.sql.sources.schema' as it's corrupted.
	at org.apache.spark.sql.errors.QueryCompilationErrors$.cannotReadCorruptedTablePropertyError(QueryCompilationErrors.scala:840) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.CatalogTable$.$anonfun$readLargeTableProp$1(interface.scala:502) ~[spark-catalyst_2
8000
.12-3.3.4.104.jar:3.3.4.104]
	at scala.Option.orElse(Option.scala:447) ~[scala-library-2.12.18.jar:?]
	at org.apache.spark.sql.catalyst.catalog.CatalogTable$.readLargeTableProp(interface.scala:497) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.getSchemaFromTableProperties(HiveExternalCatalog.scala:839) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.restoreHiveSerdeTable(HiveExternalCatalog.scala:809) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.restoreTableMetadata(HiveExternalCatalog.scala:765) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$getTable$1(HiveExternalCatalog.scala:734) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:101) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.getTable(HiveExternalCatalog.scala:734) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.getTable(ExternalCatalogWithListener.scala:138) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableRawMetadata(SessionCatalog.scala:544) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableMetadata(SessionCatalog.scala:529) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	...

Before SPARK-33812, it skipped reading the schema from table properties if spark.sql.sources.schema.numParts was missing for a Hive SerDe table.

Why are the changes needed?

Restore behavior before Spark 3.2.

Does this PR introduce any user-facing change?

Yes, restores behavior before Spark 3.2.

How was this patch tested?

UT is added.

Was this patch authored or co-authored using generative AI tooling?

No.

@github-actions github-actions bot added the SQL label Sep 16, 2025
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pan3793 commented Sep 16, 2025

cc @cloud-fan as you are the author of SPARK-33812(de234ee)

@pan3793 pan3793 changed the title [SPARK-53598][SQL] Check numParts field for Hive tables before reading data source schema [SPARK-53598][SQL] Check numParts field for Hive tables before reading schema Sep 16, 2025
cloud-fan
cloud-fan reviewed Sep 17, 2025
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/interface.scala Outdated
def readLargeTableProp(
props: Map[String, String],
key: String,
failIfNumPartsMissing: Boolean = true): Option[String] = {
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when it's needed to be true? I think it's fine to always be more lenient, as the consequence is simply doing a schema inference, which is better than failing.

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@pan3793 pan3793 Sep 17, 2025 •
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Before SPARK-33812, it performs true for the DS table on schema reading, but false for the Hive SerDe table, I'm trying to restore such behavior.

SPARK-33812 introduces another case - ColumStats histogram, when numParts is missing, it fails here and the exception will be caught at

spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/interface.scala

Lines 1009 to 1032 in f2e9c68

def fromMap(
table: String,
colName: String,
map: Map[String, String]): Option[CatalogColumnStat] = {
try {
Some(CatalogColumnStat(
distinctCount = map.get(s"${colName}.${KEY_DISTINCT_COUNT}").map(v => BigInt(v.toLong)),
min = map.get(s"${colName}.${KEY_MIN_VALUE}"),
max = map.get(s"${colName}.${KEY_MAX_VALUE}"),
nullCount = map.get(s"${colName}.${KEY_NULL_COUNT}").map(v => BigInt(v.toLong)),
avgLen = map.get(s"${colName}.${KEY_AVG_LEN}").map(_.toLong),
maxLen = map.get(s"${colName}.${KEY_MAX_LEN}").map(_.toLong),
histogram = CatalogTable.readLargeTableProp(map, s"$colName.$KEY_HISTOGRAM")
.map(HistogramSerializer.deserialize),
version = map(s"${colName}.${KEY_VERSION}").toInt
))
} catch {
case NonFatal(e) =>
logWarning(log"Failed to parse column statistics for column " +
log"${MDC(COLUMN_NAME, colName)} in table ${MDC(RELATION_NAME, table)}", e)
None
}
}

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@cloud-fan I updated the code as you suggested, could you take another look?

@pan3793 pan3793 changed the title [SPARK-53598][SQL] Check numParts field for Hive tables before reading schema [SPARK-53598][SQL] Check the existence of numParts before reading large table property Sep 17, 2025
vrozov
vrozov reviewed Sep 17, 2025
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sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala
Seq(true, false).foreach { isHiveTable =>
try {
val schema = StructType(StructField("int", IntegerType) :: Nil)
val hiveTableWithoutNumPartsProp = CatalogTable(
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Can construction of CatalogTable be refactored to a separate method that takes 3 parameters (table name, table type and num of part) to avoid code duplication here and on line 1405?

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this requires parameterizing more things, I prefer to keep it as-is unless you strongly disagree

@pan3793 pan3793 mentioned this pull request Sep 18, 2025
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@pan3793 pan3793 requested a review from cloud-fan September 18, 2025 03:56
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thanks, merging to master/4.0!

@cloud-fan cloud-fan closed this in 4b93d4c Sep 18, 2025
cloud-fan pushed a commit that referenced this pull request Sep 18, 2025
@pan3793 @cloud-fan
[SPARK-53598][SQL] Check the existence of numParts before reading lar…
7e7b10e 
…ge table property

### What changes were proposed in this pull request?

This PR proposes to fix a regression caused by SPARK-33812 (de234ee 3.2.0).

We hit an error when upgrading Spark from 3.1 to 3.3, the table is a Hive SerDe Parquet table, which TBLPROPERTIES looks like malformed (not sure how this happen), the table can be read and write normally with Spark 3.1, but fails on reading with Spark 3.3.

```
-- Hive DDL
CREATE EXTERNAL TABLE `foo`.`bar`(
  `id` bigint,
  ...
) PARTITIONED BY (`dt` string)
ROW FORMAT SERDE
  'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
STORED AS INPUTFORMAT
  'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat'
OUTPUTFORMAT
  'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat'
LOCATION
  'hdfs://...'
TBLPROPERTIES (
  ...
  'spark.sql.sources.schema.partCol.0'='dt',
  'transient_lastDdlTime'='1727333678')
```

```
org.apache.spark.sql.AnalysisException: Cannot read table property 'spark.sql.sources.schema' as it's corrupted.
	at org.apache.spark.sql.errors.QueryCompilationErrors$.cannotReadCorruptedTablePropertyError(QueryCompilationErrors.scala:840) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.CatalogTable$.$anonfun$readLargeTableProp$1(interface.scala:502) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at scala.Option.orElse(Option.scala:447) ~[scala-library-2.12.18.jar:?]
	at org.apache.spark.sql.catalyst.catalog.CatalogTable$.readLargeTableProp(interface.scala:497) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.getSchemaFromTableProperties(HiveExternalCatalog.scala:839) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.restoreHiveSerdeTable(HiveExternalCatalog.scala:809) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.restoreTableMetadata(HiveExternalCatalog.scala:765) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$getTable$1(HiveExternalCatalog.scala:734) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:101) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.getTable(HiveExternalCatalog.scala:734) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.getTable(ExternalCatalogWithListener.scala:138) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableRawMetadata(SessionCatalog.scala:544) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableMetadata(SessionCatalog.scala:529) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	...
```

Before SPARK-33812, it skipped reading the schema from table properties if `spark.sql.sources.schema.numParts` was missing for a Hive SerDe table.

### Why are the changes needed?

Restore behavior before Spark 3.2.

### Does this PR introduce _any_ user-facing change?

Yes, restores behavior before Spark 3.2.

### How was this patch tested?

UT is added.

### Was this patch authored or co-authored using generative AI tooling?

No.

Closes #52355 from pan3793/SPARK-53598.

Authored-by: Cheng Pan <chengpan@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
(cherry picked from commit 4b93d4c)
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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please open new PRs if you want to backport further.

pan3793 added a commit to pan3793/spark that referenced this pull request Sep 18, 2025
@pan3793
[SPARK-53598][SQL][3.5] Check the existence of numParts before readin…
1ba5082 
…g large table property

This PR proposes to fix a regression caused by SPARK-33812 (apache@de234ee 3.2.0).

We hit an error when upgrading Spark from 3.1 to 3.3, the table is a Hive SerDe Parquet table, which TBLPROPERTIES looks like malformed (not sure how this happen), the table can be read and write normally with Spark 3.1, but fails on reading with Spark 3.3.

```
-- Hive DDL
CREATE EXTERNAL TABLE `foo`.`bar`(
  `id` bigint,
  ...
) PARTITIONED BY (`dt` string)
ROW FORMAT SERDE
  'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
STORED AS INPUTFORMAT
  'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat'
OUTPUTFORMAT
  'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat'
LOCATION
  'hdfs://...'
TBLPROPERTIES (
  ...
  'spark.sql.sources.schema.partCol.0'='dt',
  'transient_lastDdlTime'='1727333678')
```

```
org.apache.spark.sql.AnalysisException: Cannot read table property 'spark.sql.sources.schema' as it's corrupted.
	at org.apache.spark.sql.errors.QueryCompilationErrors$.cannotReadCorruptedTablePropertyError(QueryCompilationErrors.scala:840) ~[spark-catalyst_2.12-3.3.4.104.ja
8000
r:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.CatalogTable$.$anonfun$readLargeTableProp$1(interface.scala:502) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at scala.Option.orElse(Option.scala:447) ~[scala-library-2.12.18.jar:?]
	at org.apache.spark.sql.catalyst.catalog.CatalogTable$.readLargeTableProp(interface.scala:497) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.getSchemaFromTableProperties(HiveExternalCatalog.scala:839) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.restoreHiveSerdeTable(HiveExternalCatalog.scala:809) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.restoreTableMetadata(HiveExternalCatalog.scala:765) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$getTable$1(HiveExternalCatalog.scala:734) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:101) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.getTable(HiveExternalCatalog.scala:734) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.getTable(ExternalCatalogWithListener.scala:138) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableRawMetadata(SessionCatalog.scala:544) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableMetadata(SessionCatalog.scala:529) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	...
```

Before SPARK-33812, it skipped reading the schema from table properties if `spark.sql.sources.schema.numParts` was missing for a Hive SerDe table.

Restore behavior before Spark 3.2.

Yes, restores behavior before Spark 3.2.

UT is added.

No.

Closes apache#52355 from pan3793/SPARK-53598.

Authored-by: Cheng Pan <chengpan@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
@pan3793 pan3793 mentioned this pull request Sep 18, 2025
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pan3793 commented Sep 18, 2025

@cloud-fan thanks, I opened #52385 for 3.5

cloud-fan pushed a commit that referenced this pull request Sep 19, 2025
@yeshengm @cloud-fan
[SPARK-53623][SQL] improve reading large table properties performance
4f10262 
### What changes were proposed in this pull request?
The CatalogColumnStat.readLargeTableProp is an O(N) operation. Considering a table can have a lot of table properties, this effectively becomes an O(N^2) operation, which can be very slow for tables with a lot of table properties.

This PR improves the algorithmic complexity to O(N) by only constructing the large table properties if numParts exists.

### Why are the changes needed?
For fixing a performance issue unintentionally introduced before.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Existing unit tests. A previous patch already tested the side effect of this change #52355

### Was this patch authored or co-authored using generative AI tooling?
No

Closes #52374 from yeshengm/improve-read-large-prop.

Authored-by: Yesheng Ma <yesheng.ma@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
dongjoon-hyun pushed a commit that referenced this pull request Sep 24, 2025
@pan3793 @dongjoon-hyun
[SPARK-53598][SQL][3.5] Check the existence of numParts before readin…
22d4d3d 
…g large table property

Backport #52355 to branch-3.5

### What changes were proposed in this pull request?

This PR proposes to fix a regression caused by SPARK-33812 (de234ee 3.2.0).

We hit an error when upgrading Spark from 3.1 to 3.3, the table is a Hive SerDe Parquet table, which TBLPROPERTIES looks like malformed (not sure how this happen), the table can be read and write normally with Spark 3.1, but fails on reading with Spark 3.3.

```
-- Hive DDL
CREATE EXTERNAL TABLE `foo`.`bar`(
  `id` bigint,
  ...
) PARTITIONED BY (`dt` string)
ROW FORMAT SERDE
  'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
STORED AS INPUTFORMAT
  'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat'
OUTPUTFORMAT
  'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat'
LOCATION
  'hdfs://...'
TBLPROPERTIES (
  ...
  'spark.sql.sources.schema.partCol.0'='dt',
  'transient_lastDdlTime'='1727333678')
```

```
org.apache.spark.sql.AnalysisException: Cannot read table property 'spark.sql.sources.schema' as it's corrupted.
	at org.apache.spark.sql.errors.QueryCompilationErrors$.cannotReadCorruptedTablePropertyError(QueryCompilationErrors.scala:840) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.CatalogTable$.$anonfun$readLargeTableProp$1(interface.scala:502) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at scala.Option.orElse(Option.scala:447) ~[scala-library-2.12.18.jar:?]
	at org.apache.spark.sql.catalyst.catalog.CatalogTable$.readLargeTableProp(interface.scala:497) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.getSchemaFromTableProperties(HiveExternalCatalog.scala:839) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.restoreHiveSerdeTable(HiveExternalCatalog.scala:809) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.restoreTableMetadata(HiveExternalCatalog.scala:765) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$getTable$1(HiveExternalCatalog.scala:734) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:101) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.hive.HiveExternalCatalog.getTable(HiveExternalCatalog.scala:734) ~[spark-hive_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.getTable(ExternalCatalogWithListener.scala:138) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableRawMetadata(SessionCatalog.scala:544) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableMetadata(SessionCatalog.scala:529) ~[spark-catalyst_2.12-3.3.4.104.jar:3.3.4.104]
	...
```

Before SPARK-33812, it skipped reading the schema from table properties if `spark.sql.sources.schema.numParts` was missing for a Hive SerDe table.

### Why are the changes needed?

Restore behavior before Spark 3.2.

### Does this PR introduce _any_ user-facing change?

Yes, restores behavior before Spark 3.2.

### How was this patch tested?

UT is added.

### Was this patch authored or co-authored using generative AI tooling?

No.

Closes #52385 from pan3793/SPARK-53598-3.5.

Authored-by: Cheng Pan <chengpan@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
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