[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1095704158
##
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala:
##
@@ -49,24 +49,28 @@ import org.apache.spark.sql.types._
* @param caseSensitive Whether use case sensitive analysis when comparing
Spark catalyst read
* schema with Parquet schema.
* @param inferTimestampNTZ Whether TimestampNTZType type is enabled.
+ * @param nanosAsLong Whether timestamps with nanos are converted to long.
*/
class ParquetToSparkSchemaConverter(
assumeBinaryIsString: Boolean =
SQLConf.PARQUET_BINARY_AS_STRING.defaultValue.get,
assumeInt96IsTimestamp: Boolean =
SQLConf.PARQUET_INT96_AS_TIMESTAMP.defaultValue.get,
caseSensitive: Boolean = SQLConf.CASE_SENSITIVE.defaultValue.get,
inferTimestampNTZ: Boolean =
SQLConf.PARQUET_INFER_TIMESTAMP_NTZ_ENABLED.defaultValue.get) {
+nanosAsLong: Boolean =
SQLConf.LEGACY_PARQUET_NANOS_AS_LONG.defaultValue.get) {
Review Comment:
```suggestion
inferTimestampNTZ: Boolean =
SQLConf.PARQUET_INFER_TIMESTAMP_NTZ_ENABLED.defaultValue.get,
nanosAsLong: Boolean =
SQLConf.LEGACY_PARQUET_NANOS_AS_LONG.defaultValue.get) {
```
##
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala:
##
@@ -65,12 +68,14 @@ abstract class ParquetSchemaTest extends ParquetTest with
SharedSparkSession {
caseSensitive: Boolean = false,
inferTimestampNTZ: Boolean = true,
sparkReadSchema: Option[StructType] = None,
- expectedParquetColumn: Option[ParquetColumn] = None): Unit = {
+ expectedParquetColumn: Option[ParquetColumn] = None,
+ nanosAsLong: Boolean = false): Unit = {
val converter = new ParquetToSparkSchemaConverter(
assumeBinaryIsString = binaryAsString,
assumeInt96IsTimestamp = int96AsTimestamp,
caseSensitive = caseSensitive,
inferTimestampNTZ = inferTimestampNTZ)
+ nanosAsLong = nanosAsLong)
Review Comment:
```suggestion
inferTimestampNTZ = inferTimestampNTZ,
nanosAsLong = nanosAsLong)
```
##
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala:
##
@@ -454,13 +459,15 @@ object ParquetFileFormat extends Logging {
val assumeBinaryIsString =
sparkSession.sessionState.conf.isParquetBinaryAsString
val assumeInt96IsTimestamp =
sparkSession.sessionState.conf.isParquetINT96AsTimestamp
val inferTimestampNTZ =
sparkSession.sessionState.conf.parquetInferTimestampNTZEnabled
+val nanosAsLong = sparkSession.sessionState.conf.legacyParquetNanosAsLong
val reader = (files: Seq[FileStatus], conf: Configuration,
ignoreCorruptFiles: Boolean) => {
// Converter used to convert Parquet `MessageType` to Spark SQL
`StructType`
val converter = new ParquetToSparkSchemaConverter(
assumeBinaryIsString = assumeBinaryIsString,
assumeInt96IsTimestamp = assumeInt96IsTimestamp,
inferTimestampNTZ = inferTimestampNTZ)
+nanosAsLong = nanosAsLong)
Review Comment:
```suggestion
inferTimestampNTZ = inferTimestampNTZ,
nanosAsLong = nanosAsLong)
```
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1095651650
##
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
##
@@ -4946,6 +4953,8 @@ class SQLConf extends Serializable with Logging {
def parquetInferTimestampNTZEnabled: Boolean =
getConf(PARQUET_INFER_TIMESTAMP_NTZ_ENABLED)
+ def parquetTimestampNTZEnabled: Boolean =
getConf(PARQUET_TIMESTAMP_NTZ_ENABLED)
+
Review Comment:
Looks like this sneaked in while rebasing...
Renamed recently here:
https://github.com/apache/spark/commit/ae24327e8984e7ee8ba948e3be0b6b2f28df68d0#diff-13c5b65678b327277c68d17910ae93629801af00117a0e3da007afd95b6c6764L4946-R4947
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1025422089
##
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala:
##
@@ -1040,6 +1040,14 @@ class ParquetSchemaSuite extends ParquetSchemaTest {
}
}
+ test("SPARK-40819 - ability to read parquet file with TIMESTAMP(NANOS,
true)") {
+val testDataPath =
getClass.getResource("/test-data/timestamp-nanos.parquet")
+val data = spark.read.parquet(testDataPath.toString).select("birthday")
+
+assert(data.schema.fields.head.dataType == LongType)
+assert(data.take(1).head.getAs[Long](0) == 16685371290L)
Review Comment:
Can we have true nano second values to be sure they are not zeroed by the
loader but loaded as in the file, e.g. `1665532812012345678L`.
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1025413969
##
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala:
##
@@ -1040,6 +1040,14 @@ class ParquetSchemaSuite extends ParquetSchemaTest {
}
}
+ test("SPARK-40819 - ability to read parquet file with TIMESTAMP(NANOS,
true)") {
Review Comment:
nit: other tests in this file follow the naming convention "SPARK-X: ..."
```suggestion
test("SPARK-40819: ability to read parquet file with TIMESTAMP(NANOS,
true)") {
```
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1025407302
##
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala:
##
@@ -1040,6 +1040,14 @@ class ParquetSchemaSuite extends ParquetSchemaTest {
}
}
+ test("SPARK-40819 - ability to read parquet file with TIMESTAMP(NANOS,
true)") {
+val testDataPath =
getClass.getResource("/test-data/timestamp-nanos.parquet")
+val data = spark.read.parquet(testDataPath.toString).select("birthday")
+
+assert(data.schema.fields.head.dataType == LongType)
+assert(data.take(1).head.getAs[Long](0) == 16685371290L)
Review Comment:
Shall we sort the read dataframe to be guarantee we compare the first row
(Unless all rows have the same timestamp)?
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1017736181
##
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala:
##
@@ -198,6 +205,31 @@ abstract class ParquetSchemaTest extends ParquetTest with
SharedSparkSession {
}
class ParquetSchemaInferenceSuite extends ParquetSchemaTest {
+ testSchemaInference[Tuple1[Long]](
Review Comment:
@cloud-fan moving Parquet from `1.10.1` to `1.12.3` introduced this
regression where Spark 3.1 returned `LongType` and Spark 3.2 fails on illegal
type.
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1002966819
##
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala:
##
@@ -271,6 +271,10 @@ class ParquetToSparkSchemaConverter(
} else {
TimestampNTZType
}
+ // SPARK-40819: NANOS are not supported as a Timestamp, convert to
LongType without
+ // timezone awareness to address behaviour regression introduced by
SPARK-34661
Review Comment:
Yes, the mere purpose of this exercise is to get access to the nano
precision.
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1002966819
##
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala:
##
@@ -271,6 +271,10 @@ class ParquetToSparkSchemaConverter(
} else {
TimestampNTZType
}
+ // SPARK-40819: NANOS are not supported as a Timestamp, convert to
LongType without
+ // timezone awareness to address behaviour regression introduced by
SPARK-34661
Review Comment:
Yes, the main purpose of the nano timestamp is the nano precision.
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1001531184
##
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala:
##
@@ -271,6 +271,8 @@ class ParquetToSparkSchemaConverter(
} else {
TimestampNTZType
}
+ case timestamp: TimestampLogicalTypeAnnotation if timestamp.getUnit
== TimeUnit.NANOS =>
Review Comment:
So this is not a valid workaround. @sunchao how is your feeling about
restoring earlier useful behaviour?
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[GitHub] [spark] EnricoMi commented on a diff in pull request #38312: [SPARK-40819][SQL] Timestamp nanos behaviour regression
EnricoMi commented on code in PR #38312:
URL: https://github.com/apache/spark/pull/38312#discussion_r1001088325
##
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala:
##
@@ -271,6 +271,8 @@ class ParquetToSparkSchemaConverter(
} else {
TimestampNTZType
}
+ case timestamp: TimestampLogicalTypeAnnotation if timestamp.getUnit
== TimeUnit.NANOS =>
Review Comment:
Yes, the (earlier) existing behaviour was useful and should be restored
until properly supported as typed nano timestamp. Unless a workaround can be
found that restores the earlier behaviour.
Does providing a schema (`spark.read.schema(...)`) with long type override
the parquet timestamp type from the parquet file? Would that be a workaround?
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