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Posted to reviews@spark.apache.org by "majdyz (via GitHub)" <gi...@apache.org> on 2023/10/19 08:09:43 UTC
[PR] [SPARK-45604] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader [spark]
majdyz opened a new pull request, #43451:
URL: https://github.com/apache/spark/pull/43451
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### What changes were proposed in this pull request?
Currently, the read logical type is not checked while converting physical types INT64 into DateTime. One valid scenario where this can break is where the physical type is `timestamp_ntz`, and the logical type is `array<timestamp_ntz>`, since the logical type check does not happen, this conversion is allowed. However, the vectorized reader does not support this and will produce NPE on on-heap memory mode and SEGFAULT on off-heap memory mode (segfault can be prevented by having an explicit boundary check on OffHeapColumnVector, but this is outside of the scope of this PR).
### Why are the changes needed?
Prevent NPE or Segfault from happening.
### Does this PR introduce _any_ user-facing change?
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No.
### How was this patch tested?
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A new test is added in `ParquetSchemaSuite`.
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No.
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Re: [PR] [SPARK-45604] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on code in PR #43451:
URL: https://github.com/apache/spark/pull/43451#discussion_r1365590894
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala:
##########
@@ -1087,6 +1087,27 @@ class ParquetSchemaSuite extends ParquetSchemaTest {
}
}
+ test("SPARK-45604: schema mismatch failure error on timestamp_nz to array<timestamp_nz>") {
+ import testImplicits._
+
+ withTempPath { dir =>
+ val path = dir.getCanonicalPath
+ val timestamp = java.time.LocalDateTime.of(1, 2, 3, 4, 5)
+ val df1 = Seq((1, timestamp)).toDF()
+ val df2 = Seq((2, Array(timestamp))).toDF()
+ df1.write.mode("overwrite").parquet(s"$path/parquet")
+ df2.write.mode("append").parquet(s"$path/parquet")
+
+ withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "true") {
+ val e = intercept[SparkException] {
+ spark.read.schema(df2.schema).parquet(s"$path/parquet").collect()
+ }
+ assert(e.getCause.isInstanceOf[SparkException])
+ assert(e.getCause.getCause.isInstanceOf[SchemaColumnConvertNotSupportedException])
Review Comment:
This exception should be migrated to `SparkThrowable`, and we should throw an exception with proper error class. Please, add a follow up ticket to https://issues.apache.org/jira/browse/SPARK-37935
##########
sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/ParquetVectorUpdaterFactory.java:
##########
@@ -109,15 +109,17 @@ public ParquetVectorUpdater getUpdater(ColumnDescriptor descriptor, DataType spa
// For unsigned int64, it stores as plain signed int64 in Parquet when dictionary
// fallbacks. We read them as decimal values.
return new UnsignedLongUpdater();
- } else if (isTimestampTypeMatched(LogicalTypeAnnotation.TimeUnit.MICROS)) {
+ } else if (sparkType instanceof DatetimeType &&
Review Comment:
`DatetimeType` also includes the `DATE` type. Does this `if` handle the date types too?
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Re: [PR] [SPARK-45604][SQL] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader [spark]
Posted by "majdyz (via GitHub)" <gi...@apache.org>.
majdyz commented on PR #43451:
URL: https://github.com/apache/spark/pull/43451#issuecomment-1772218760
@MaxGekk yes, and I believe the previous branches too.
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Re: [PR] [SPARK-45604][SQL] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on PR #43451:
URL: https://github.com/apache/spark/pull/43451#issuecomment-1772159682
@majdyz Does Spark 3.4.x have the same issue?
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Re: [PR] [SPARK-45604][SQL] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on PR #43451:
URL: https://github.com/apache/spark/pull/43451#issuecomment-1774003072
+1, LGTM. Merging to master/3.5/3.4.
Thank you, @majdyz.
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Re: [PR] [SPARK-45604] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader [spark]
Posted by "majdyz (via GitHub)" <gi...@apache.org>.
majdyz commented on code in PR #43451:
URL: https://github.com/apache/spark/pull/43451#discussion_r1365683194
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala:
##########
@@ -1087,6 +1087,27 @@ class ParquetSchemaSuite extends ParquetSchemaTest {
}
}
+ test("SPARK-45604: schema mismatch failure error on timestamp_nz to array<timestamp_nz>") {
+ import testImplicits._
+
+ withTempPath { dir =>
+ val path = dir.getCanonicalPath
+ val timestamp = java.time.LocalDateTime.of(1, 2, 3, 4, 5)
+ val df1 = Seq((1, timestamp)).toDF()
+ val df2 = Seq((2, Array(timestamp))).toDF()
+ df1.write.mode("overwrite").parquet(s"$path/parquet")
+ df2.write.mode("append").parquet(s"$path/parquet")
+
+ withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "true") {
+ val e = intercept[SparkException] {
+ spark.read.schema(df2.schema).parquet(s"$path/parquet").collect()
+ }
+ assert(e.getCause.isInstanceOf[SparkException])
+ assert(e.getCause.getCause.isInstanceOf[SchemaColumnConvertNotSupportedException])
Review Comment:
Added a subtask here: https://issues.apache.org/jira/browse/SPARK-45608
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Re: [PR] [SPARK-45604] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader [spark]
Posted by "majdyz (via GitHub)" <gi...@apache.org>.
majdyz commented on code in PR #43451:
URL: https://github.com/apache/spark/pull/43451#discussion_r1365780160
##########
sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/ParquetVectorUpdaterFactory.java:
##########
@@ -109,15 +109,17 @@ public ParquetVectorUpdater getUpdater(ColumnDescriptor descriptor, DataType spa
// For unsigned int64, it stores as plain signed int64 in Parquet when dictionary
// fallbacks. We read them as decimal values.
return new UnsignedLongUpdater();
- } else if (isTimestampTypeMatched(LogicalTypeAnnotation.TimeUnit.MICROS)) {
+ } else if (sparkType instanceof DatetimeType &&
Review Comment:
Good point. I've limited this check only to Timestamp & TimestampNtz now.
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Re: [PR] [SPARK-45604][SQL] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk closed pull request #43451: [SPARK-45604][SQL] Add LogicalType checking on INT64 -> DateTime conversion on Parquet Vectorized Reader
URL: https://github.com/apache/spark/pull/43451
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