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new 91263564ce64 [SPARK-57372][SQL] Remove the Types Framework feature flag
91263564ce64 is described below
commit 91263564ce649bbb3fc286a18e0ca323102dc2ce
Author: David Milicevic <[email protected]>
AuthorDate: Sat Jun 13 15:28:26 2026 +0200
[SPARK-57372][SQL] Remove the Types Framework feature flag
### What changes were proposed in this pull request?
Removes the `spark.sql.types.framework.enabled` configuration and makes the
Types Framework unconditionally active — it is the single path for the data
types it manages (`TimeType` and the nanosecond timestamp types), with no flag
gating it.
Two follow-on adjustments fall out of making the framework unconditional:
- The nanosecond timestamp types (SPARK-56822) gated their preview flag on
the framework flag ("can only be enabled when the framework is enabled"). With
the framework always on that requirement is always satisfied, so it is removed;
the nanosecond types remain gated by their own
`spark.sql.timestampNanosTypes.enabled` at the parser and schema entry points.
- The TIME-type-enabled check that lived on the legacy
serializer/deserializer path (reached only when the framework was off) moves
into the framework's `TimeType` operations, so disabling
`spark.sql.timeType.enabled` still rejects TIME exactly as before.
### Why are the changes needed?
The flag was only ever a release-rollout kill switch — on under tests, off
in production, never intended as a per-session toggle. Every framework dispatch
read the session config, and those dispatches sit on per-row hot paths
(columnar reads, projections, encoder building), where the lookup is a
measurable cost; the only way to make it cheap is to effectively pin it, at
which point it stops being a meaningful toggle. A permanently test-on/prod-off
switch also adds standing surface are [...]
### Does this PR introduce _any_ user-facing change?
No. `spark.sql.types.framework.enabled` is internal, defaulted on only
under tests and off in production, and never shipped in a released (GA)
version, so there is no migration concern and no `RemovedConfig` entry is
needed (cf. SPARK-49671, which removed the internal, already-on-by-default
`spark.sql.collation.trim.enabled` without one). Behavior for the managed types
is unchanged, and feature gates such as `spark.sql.timeType.enabled` /
`spark.sql.timestampNanosTypes.enabled` contin [...]
### How was this patch tested?
Existing encoder, type-conversion, Row-JSON, nanosecond-timestamp, and SQL
config-audit suites pass with the framework now unconditionally enabled
(already the default under tests); suites that toggled the flag were updated to
drop the now-impossible disabled-framework cases. A new `TimeTypeOpsSuite` pins
the relocated gate: building a TIME serializer/deserializer with
`spark.sql.timeType.enabled=false` is rejected with `UNSUPPORTED_TIME_TYPE`.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Opus 4.8 (claude-opus-4-8)
This pull request and its description were written by Isaac.
Closes #56439 from davidm-db/SPARK-57372-remove-types-framework-flag.
Authored-by: David Milicevic <[email protected]>
Signed-off-by: Max Gekk <[email protected]>
---
.../org/apache/spark/sql/internal/SqlApiConf.scala | 2 -
.../apache/spark/sql/types/ops/TypeApiOps.scala | 23 +++----
.../sql/catalyst/DeserializerBuildHelper.scala | 15 +----
.../spark/sql/catalyst/SerializerBuildHelper.scala | 14 +---
.../spark/sql/catalyst/types/ops/TimeTypeOps.scala | 15 +++++
.../spark/sql/catalyst/types/ops/TypeOps.scala | 23 +++----
.../org/apache/spark/sql/internal/SQLConf.scala | 25 +------
.../scala/org/apache/spark/sql/RowJsonSuite.scala | 47 ++++---------
.../sql/catalyst/types/ops/TimeTypeOpsSuite.scala | 76 ++++++++++++++++++++++
.../types/ops/TimestampNanosTypeOpsSuite.scala | 28 +-------
.../connect/common/types/ops/ConnectTypeOps.scala | 39 +++++------
.../spark/sql/SparkSessionBuilderSuite.scala | 1 -
.../configs-without-binding-policy-exceptions | 1 -
13 files changed, 142 insertions(+), 167 deletions(-)
diff --git
a/sql/api/src/main/scala/org/apache/spark/sql/internal/SqlApiConf.scala
b/sql/api/src/main/scala/org/apache/spark/sql/internal/SqlApiConf.scala
index 99f851829565..b101ee0563a1 100644
--- a/sql/api/src/main/scala/org/apache/spark/sql/internal/SqlApiConf.scala
+++ b/sql/api/src/main/scala/org/apache/spark/sql/internal/SqlApiConf.scala
@@ -53,7 +53,6 @@ private[sql] trait SqlApiConf {
def parserDfaCacheFlushRatio: Double
def legacyParameterSubstitutionConstantsOnly: Boolean
def legacyIdentifierClauseOnly: Boolean
- def typesFrameworkEnabled: Boolean
def timestampNanosTypesEnabled: Boolean
}
@@ -112,6 +111,5 @@ private[sql] object DefaultSqlApiConf extends SqlApiConf {
override def parserDfaCacheFlushRatio: Double = -1.0
override def legacyParameterSubstitutionConstantsOnly: Boolean = false
override def legacyIdentifierClauseOnly: Boolean = false
- override def typesFrameworkEnabled: Boolean = false
override def timestampNanosTypesEnabled: Boolean = SparkEnvUtils.isTesting
}
diff --git
a/sql/api/src/main/scala/org/apache/spark/sql/types/ops/TypeApiOps.scala
b/sql/api/src/main/scala/org/apache/spark/sql/types/ops/TypeApiOps.scala
index d7575976e1f5..ab46e34c91e3 100644
--- a/sql/api/src/main/scala/org/apache/spark/sql/types/ops/TypeApiOps.scala
+++ b/sql/api/src/main/scala/org/apache/spark/sql/types/ops/TypeApiOps.scala
@@ -162,16 +162,15 @@ trait TypeApiOps extends Serializable {
* Factory object for creating TypeApiOps instances.
*
* Returns Option to serve as both lookup and existence check - callers use
getOrElse to fall
- * through to legacy handling. The feature flag check is inside apply(), so
callers don't need to
- * check it separately.
+ * through to legacy handling for types the framework does not manage.
*/
object TypeApiOps {
/**
* Returns a TypeApiOps instance for the given DataType, if supported by the
framework.
*
- * Returns None if the type is not supported or the framework is disabled.
This is the single
- * registration point for all client-side type operations.
+ * Returns None if the type is not supported. This is the single
registration point for all
+ * client-side type operations.
*
* @param dt
* the DataType to get operations for
@@ -187,15 +186,12 @@ object TypeApiOps {
def apply(
dt: DataType,
zoneId: => ZoneId =
SparkDateTimeUtils.getZoneId(SqlApiConf.get.sessionLocalTimeZone))
- : Option[TypeApiOps] = {
- if (!SqlApiConf.get.typesFrameworkEnabled) return None
- dt match {
- case tt: TimeType => Some(new TimeTypeApiOps(tt))
- case t: TimestampNTZNanosType => Some(new TimestampNTZNanosTypeApiOps(t))
- case t: TimestampLTZNanosType => Some(new TimestampLTZNanosTypeApiOps(t,
zoneId))
- // Add new types here - single registration point
- case _ => None
- }
+ : Option[TypeApiOps] = dt match {
+ case tt: TimeType => Some(new TimeTypeApiOps(tt))
+ case t: TimestampNTZNanosType => Some(new TimestampNTZNanosTypeApiOps(t))
+ case t: TimestampLTZNanosType => Some(new TimestampLTZNanosTypeApiOps(t,
zoneId))
+ // Add new types here - single registration point
+ case _ => None
}
/**
@@ -203,7 +199,6 @@ object TypeApiOps {
*/
def fromArrowType(at: ArrowType): Option[DataType] = {
import org.apache.arrow.vector.types.TimeUnit
- if (!SqlApiConf.get.typesFrameworkEnabled) return None
at match {
case t: ArrowType.Time if t.getUnit == TimeUnit.NANOSECOND &&
t.getBitWidth == 8 * 8 =>
Some(TimeType(TimeType.MICROS_PRECISION))
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/DeserializerBuildHelper.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/DeserializerBuildHelper.scala
index 1fa7803006c4..b08804dccc67 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/DeserializerBuildHelper.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/DeserializerBuildHelper.scala
@@ -20,7 +20,7 @@ package org.apache.spark.sql.catalyst
import org.apache.spark.sql.catalyst.{expressions => exprs}
import org.apache.spark.sql.catalyst.analysis.{GetColumnByOrdinal,
UnresolvedExtractValue}
import org.apache.spark.sql.catalyst.encoders.{AgnosticEncoder,
AgnosticEncoders, AgnosticExpressionPathEncoder, Codec, JavaSerializationCodec,
KryoSerializationCodec}
-import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.{ArrayEncoder,
BoxedLeafEncoder, CharEncoder, DateEncoder, DayTimeIntervalEncoder,
GeographyEncoder, GeometryEncoder, InstantEncoder, IterableEncoder,
JavaBeanEncoder, JavaBigIntEncoder, JavaDecimalEncoder, JavaEnumEncoder,
LocalDateEncoder, LocalDateTimeEncoder, LocalTimeEncoder, MapEncoder,
OptionEncoder, PrimitiveBooleanEncoder, PrimitiveByteEncoder,
PrimitiveDoubleEncoder, PrimitiveFloatEncoder, PrimitiveIntEncoder, Primi [...]
+import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.{ArrayEncoder,
BoxedLeafEncoder, CharEncoder, DateEncoder, DayTimeIntervalEncoder,
GeographyEncoder, GeometryEncoder, InstantEncoder, IterableEncoder,
JavaBeanEncoder, JavaBigIntEncoder, JavaDecimalEncoder, JavaEnumEncoder,
LocalDateEncoder, LocalDateTimeEncoder, MapEncoder, OptionEncoder,
PrimitiveBooleanEncoder, PrimitiveByteEncoder, PrimitiveDoubleEncoder,
PrimitiveFloatEncoder, PrimitiveIntEncoder, PrimitiveLongEncoder, P [...]
import org.apache.spark.sql.catalyst.encoders.EncoderUtils.{dataTypeForClass,
externalDataTypeFor, isNativeEncoder}
import org.apache.spark.sql.catalyst.expressions.{Expression, GetStructField,
IsNull, Literal, MapKeys, MapValues, UpCast}
import org.apache.spark.sql.catalyst.expressions.objects.{AssertNotNull,
CreateExternalRow, DecodeUsingSerializer, InitializeJavaBean, Invoke,
NewInstance, StaticInvoke, UnresolvedCatalystToExternalMap,
UnresolvedMapObjects, WrapOption}
@@ -176,15 +176,6 @@ object DeserializerBuildHelper {
returnNullable = false)
}
- def createDeserializerForLocalTime(path: Expression): Expression = {
- StaticInvoke(
- DateTimeUtils.getClass,
- ObjectType(classOf[java.time.LocalTime]),
- "nanosToLocalTime",
- path :: Nil,
- returnNullable = false)
- }
-
def createDeserializerForJavaBigDecimal(
path: Expression,
returnNullable: Boolean): Expression = {
@@ -364,10 +355,6 @@ object DeserializerBuildHelper {
createDeserializerForInstant(path)
case LocalDateTimeEncoder =>
createDeserializerForLocalDateTime(path)
- case LocalTimeEncoder if !SQLConf.get.isTimeTypeEnabled =>
- throw
org.apache.spark.sql.errors.QueryCompilationErrors.unsupportedTimeTypeError()
- case LocalTimeEncoder =>
- createDeserializerForLocalTime(path)
case UDTEncoder(udt, udtClass) =>
val obj = NewInstance(udtClass, Nil, ObjectType(udtClass))
Invoke(obj, "deserialize", ObjectType(udt.userClass), path :: Nil)
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SerializerBuildHelper.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SerializerBuildHelper.scala
index 00a0d6ca2505..3531ebc77c98 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SerializerBuildHelper.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SerializerBuildHelper.scala
@@ -22,7 +22,7 @@ import scala.language.existentials
import org.apache.spark.sql.catalyst.{expressions => exprs}
import
org.apache.spark.sql.catalyst.DeserializerBuildHelper.expressionWithNullSafety
import org.apache.spark.sql.catalyst.encoders.{AgnosticEncoder,
AgnosticEncoders, AgnosticExpressionPathEncoder, Codec, JavaSerializationCodec,
KryoSerializationCodec}
-import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.{ArrayEncoder,
BoxedBooleanEncoder, BoxedByteEncoder, BoxedDoubleEncoder, BoxedFloatEncoder,
BoxedIntEncoder, BoxedLeafEncoder, BoxedLongEncoder, BoxedShortEncoder,
CharEncoder, DateEncoder, DayTimeIntervalEncoder, GeographyEncoder,
GeometryEncoder, InstantEncoder, IterableEncoder, JavaBeanEncoder,
JavaBigIntEncoder, JavaDecimalEncoder, JavaEnumEncoder, LocalDateEncoder,
LocalDateTimeEncoder, LocalTimeEncoder, MapEncoder, Opt [...]
+import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.{ArrayEncoder,
BoxedBooleanEncoder, BoxedByteEncoder, BoxedDoubleEncoder, BoxedFloatEncoder,
BoxedIntEncoder, BoxedLeafEncoder, BoxedLongEncoder, BoxedShortEncoder,
CharEncoder, DateEncoder, DayTimeIntervalEncoder, GeographyEncoder,
GeometryEncoder, InstantEncoder, IterableEncoder, JavaBeanEncoder,
JavaBigIntEncoder, JavaDecimalEncoder, JavaEnumEncoder, LocalDateEncoder,
LocalDateTimeEncoder, MapEncoder, OptionEncoder, Primit [...]
import
org.apache.spark.sql.catalyst.encoders.EncoderUtils.{externalDataTypeFor,
isNativeEncoder, lenientExternalDataTypeFor}
import org.apache.spark.sql.catalyst.expressions.{BoundReference,
CheckOverflow, CreateNamedStruct, Expression, IsNull, KnownNotNull, Literal,
UnsafeArrayData}
import org.apache.spark.sql.catalyst.expressions.objects._
@@ -118,15 +118,6 @@ object SerializerBuildHelper {
returnNullable = false)
}
- def createSerializerForLocalTime(inputObject: Expression): Expression = {
- StaticInvoke(
- DateTimeUtils.getClass,
- TimeType(),
- "localTimeToNanos",
- inputObject :: Nil,
- returnNullable = false)
- }
-
def createSerializerForScalaEnum(inputObject: Expression): Expression = {
createSerializerForString(
Invoke(
@@ -384,9 +375,6 @@ object SerializerBuildHelper {
case TimestampEncoder(false) => createSerializerForSqlTimestamp(input)
case InstantEncoder(false) => createSerializerForJavaInstant(input)
case LocalDateTimeEncoder => createSerializerForLocalDateTime(input)
- case LocalTimeEncoder if !SQLConf.get.isTimeTypeEnabled =>
- throw
org.apache.spark.sql.errors.QueryCompilationErrors.unsupportedTimeTypeError()
- case LocalTimeEncoder => createSerializerForLocalTime(input)
case UDTEncoder(udt, udtClass) =>
createSerializerForUserDefinedType(input, udt, udtClass)
case OptionEncoder(valueEnc) =>
createSerializer(valueEnc, UnwrapOption(externalDataTypeFor(valueEnc),
input))
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/ops/TimeTypeOps.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/ops/TimeTypeOps.scala
index 217a69ba4f9d..f4c4b6c5a543 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/ops/TimeTypeOps.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/ops/TimeTypeOps.scala
@@ -26,7 +26,9 @@ import org.apache.spark.sql.catalyst.expressions.{Expression,
Literal, MutableLo
import org.apache.spark.sql.catalyst.expressions.objects.StaticInvoke
import org.apache.spark.sql.catalyst.types.{PhysicalDataType, PhysicalLongType}
import org.apache.spark.sql.catalyst.util.DateTimeUtils
+import org.apache.spark.sql.errors.QueryCompilationErrors
import org.apache.spark.sql.execution.arrow.{ArrowFieldWriter, TimeWriter}
+import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types.{ObjectType, TimeType}
import org.apache.spark.sql.types.ops.TimeTypeApiOps
@@ -92,7 +94,19 @@ case class TimeTypeOps(override val t: TimeType) extends
TimeTypeApiOps(t) with
// ==================== Optional Operations ====================
+ // Building a TIME serializer/deserializer requires the TIME type to be
enabled. The framework
+ // dispatch at the head of Serializer/DeserializerBuildHelper routes
LocalTimeEncoder through
+ // these methods, so this is the single gate on the encoder path. Throw
rather than return None
+ // so the dispatch surfaces UNSUPPORTED_TIME_TYPE instead of falling through
to the default
+ // match, which does not handle LocalTimeEncoder.
+ private def checkTimeTypeEnabled(): Unit = {
+ if (!SQLConf.get.isTimeTypeEnabled) {
+ throw QueryCompilationErrors.unsupportedTimeTypeError()
+ }
+ }
+
override def createSerializer(input: Expression): Option[Expression] = {
+ checkTimeTypeEnabled()
Some(StaticInvoke(
DateTimeUtils.getClass,
t,
@@ -102,6 +116,7 @@ case class TimeTypeOps(override val t: TimeType) extends
TimeTypeApiOps(t) with
}
override def createDeserializer(path: Expression): Option[Expression] = {
+ checkTimeTypeEnabled()
Some(StaticInvoke(
DateTimeUtils.getClass,
ObjectType(classOf[java.time.LocalTime]),
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/ops/TypeOps.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/ops/TypeOps.scala
index 2313c22f1f51..f11a3bb07156 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/ops/TypeOps.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/ops/TypeOps.scala
@@ -26,7 +26,6 @@ import org.apache.spark.sql.catalyst.WalkedTypePath
import org.apache.spark.sql.catalyst.expressions.{Expression, Literal,
MutableValue}
import org.apache.spark.sql.catalyst.types.PhysicalDataType
import org.apache.spark.sql.execution.arrow.ArrowFieldWriter
-import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types.{DataType, TimestampLTZNanosType,
TimestampNTZNanosType, TimeType}
/**
@@ -220,8 +219,7 @@ trait TypeOps extends Serializable {
* Factory object for creating TypeOps instances.
*
* Returns Option to serve as both lookup and existence check - callers use
getOrElse to fall
- * through to legacy handling. The feature flag check is inside apply(), so
callers don't need to
- * check it separately.
+ * through to legacy handling for types the framework does not manage.
*
* Uses pattern matching (not Set enumeration) to support parameterized types
like
* TimeType(precision) or DecimalType(precision, scale).
@@ -231,22 +229,19 @@ object TypeOps {
/**
* Returns a TypeOps instance for the given DataType, if supported by the
framework.
*
- * Returns None if the type is not supported or the framework is disabled.
This is the single
- * registration point for all server-side type operations.
+ * Returns None if the type is not supported. This is the single
registration point for all
+ * server-side type operations.
*
* @param dt
* the DataType to get operations for
* @return
* Some(TypeOps) if supported, None otherwise
*/
- def apply(dt: DataType): Option[TypeOps] = {
- if (!SQLConf.get.typesFrameworkEnabled) return None
- dt match {
- case tt: TimeType => Some(TimeTypeOps(tt))
- case t: TimestampNTZNanosType => Some(TimestampNTZNanosTypeOps(t))
- case t: TimestampLTZNanosType => Some(TimestampLTZNanosTypeOps(t))
- // Add new types here - single registration point
- case _ => None
- }
+ def apply(dt: DataType): Option[TypeOps] = dt match {
+ case tt: TimeType => Some(TimeTypeOps(tt))
+ case t: TimestampNTZNanosType => Some(TimestampNTZNanosTypeOps(t))
+ case t: TimestampLTZNanosType => Some(TimestampLTZNanosTypeOps(t))
+ // Add new types here - single registration point
+ case _ => None
}
}
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
index abe8a9a59227..586f69fcf186 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
@@ -634,17 +634,6 @@ object SQLConf {
.booleanConf
.createWithDefault(true)
- val TYPES_FRAMEWORK_ENABLED =
- buildConf("spark.sql.types.framework.enabled")
- .internal()
- .doc("When true, use the Types Framework for supported types (currently
TimeType and the " +
- "nanosecond timestamp types TimestampNTZNanosType and
TimestampLTZNanosType). " +
- "The framework centralizes type-specific operations in Ops classes
instead of " +
- "scattered pattern matching. When false, use legacy scattered
implementation.")
- .version("4.2.0")
- .booleanConf
- .createWithDefaultFunction(() => Utils.isTesting)
-
val TIMESTAMP_NANOS_TYPES_ENABLED =
buildConf("spark.sql.timestampNanosTypes.enabled")
.internal()
@@ -656,9 +645,7 @@ object SQLConf {
"Unparameterized TIMESTAMP, TIMESTAMP_NTZ, and TIMESTAMP_LTZ remain
microsecond " +
"types. Enabling this flag does not guarantee full SQL support: casts,
Parquet read, " +
"typed literals, and other operations may still fail until their
respective features " +
- "are implemented. The nanosecond timestamp types are implemented
solely through the " +
- "Types Framework, so this flag only takes effect when " +
- s"${TYPES_FRAMEWORK_ENABLED.key} is also true.")
+ "are implemented.")
.version("4.3.0")
.withBindingPolicy(ConfigBindingPolicy.SESSION)
.booleanConf
@@ -7665,15 +7652,7 @@ class SQLConf extends Serializable with Logging with
SqlApiConf {
def geospatialEnabled: Boolean = getConf(GEOSPATIAL_ENABLED)
- def typesFrameworkEnabled: Boolean = getConf(TYPES_FRAMEWORK_ENABLED)
-
- // The nanos types are implemented solely through the Types Framework, so
the flag has no
- // effect without it. The requirement is enforced here instead of in a
checkValue of
- // TIMESTAMP_NANOS_TYPES_ENABLED: a validator must not call SQLConf.get,
because validators
- // run inside mergeSparkConf while the session's SQLConf is still being
constructed, and the
- // SQLConf.get lookup re-enters that construction (infinite recursion).
- def timestampNanosTypesEnabled: Boolean =
- getConf(TIMESTAMP_NANOS_TYPES_ENABLED) && getConf(TYPES_FRAMEWORK_ENABLED)
+ def timestampNanosTypesEnabled: Boolean =
getConf(TIMESTAMP_NANOS_TYPES_ENABLED)
def dataSourceV2JoinPushdown: Boolean = getConf(DATA_SOURCE_V2_JOIN_PUSHDOWN)
diff --git
a/sql/catalyst/src/test/scala/org/apache/spark/sql/RowJsonSuite.scala
b/sql/catalyst/src/test/scala/org/apache/spark/sql/RowJsonSuite.scala
index 183eefaa8d75..31d967f3da37 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/RowJsonSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/RowJsonSuite.scala
@@ -132,46 +132,26 @@ class RowJsonSuite extends SparkFunSuite with SQLHelper {
new GenericRowWithSchema(Array(value), new StructType().add("a",
TimeType(precision))).jsonValue
test("SPARK-57338: TIME column renders the external LocalTime in JSON") {
- withSQLConf(SQLConf.TYPES_FRAMEWORK_ENABLED.key -> "true") {
- assert(timeRowJson(LocalTime.of(12, 13, 14), TimeType.MICROS_PRECISION)
===
- JObject("a" -> JString("12:13:14")))
- // The fraction is rendered up to microsecond resolution with trailing
zeros trimmed.
- assert(timeRowJson(LocalTime.of(1, 2, 3, 123456000),
TimeType.MICROS_PRECISION) ===
- JObject("a" -> JString("01:02:03.123456")))
- assert(timeRowJson(LocalTime.of(10, 30, 0, 100000000),
TimeType.MICROS_PRECISION) ===
- JObject("a" -> JString("10:30:00.1")))
- assert(timeRowJson(LocalTime.MIDNIGHT, TimeType.MICROS_PRECISION) ===
- JObject("a" -> JString("00:00:00")))
- }
+ assert(timeRowJson(LocalTime.of(12, 13, 14), TimeType.MICROS_PRECISION) ===
+ JObject("a" -> JString("12:13:14")))
+ // The fraction is rendered up to microsecond resolution with trailing
zeros trimmed.
+ assert(timeRowJson(LocalTime.of(1, 2, 3, 123456000),
TimeType.MICROS_PRECISION) ===
+ JObject("a" -> JString("01:02:03.123456")))
+ assert(timeRowJson(LocalTime.of(10, 30, 0, 100000000),
TimeType.MICROS_PRECISION) ===
+ JObject("a" -> JString("10:30:00.1")))
+ assert(timeRowJson(LocalTime.MIDNIGHT, TimeType.MICROS_PRECISION) ===
+ JObject("a" -> JString("00:00:00")))
}
test("SPARK-57338: TIME column JSON rendering is independent of the column
precision") {
- withSQLConf(SQLConf.TYPES_FRAMEWORK_ENABLED.key -> "true") {
- val time = LocalTime.of(1, 2, 3, 123456000)
- (TimeType.MIN_PRECISION to TimeType.MAX_PRECISION).foreach { p =>
- assert(timeRowJson(time, p) === JObject("a" ->
JString("01:02:03.123456")))
- }
+ val time = LocalTime.of(1, 2, 3, 123456000)
+ (TimeType.MIN_PRECISION to TimeType.MAX_PRECISION).foreach { p =>
+ assert(timeRowJson(time, p) === JObject("a" ->
JString("01:02:03.123456")))
}
}
test("SPARK-57338: null TIME column renders as JSON null") {
- withSQLConf(SQLConf.TYPES_FRAMEWORK_ENABLED.key -> "true") {
- assert(timeRowJson(null, TimeType.MICROS_PRECISION) === JObject("a" ->
JNull))
- }
- }
-
- // With the Types Framework off (the production default), TypeApiOps returns
None and Row JSON
- // falls back to the legacy toJsonDefault, which must still render the
external LocalTime that a
- // public Row holds for a TIME column - matching HiveResult's legacy
fallback - rather than
- // failing with FAILED_ROW_TO_JSON.
- test("SPARK-57338: TIME column renders via the legacy path with the
framework disabled") {
- withSQLConf(SQLConf.TYPES_FRAMEWORK_ENABLED.key -> "false") {
- assert(timeRowJson(LocalTime.of(12, 13, 14), TimeType.MICROS_PRECISION)
===
- JObject("a" -> JString("12:13:14")))
- assert(timeRowJson(LocalTime.of(1, 2, 3, 123456000),
TimeType.MICROS_PRECISION) ===
- JObject("a" -> JString("01:02:03.123456")))
- assert(timeRowJson(null, TimeType.MICROS_PRECISION) === JObject("a" ->
JNull))
- }
+ assert(timeRowJson(null, TimeType.MICROS_PRECISION) === JObject("a" ->
JNull))
}
// With nanosecond cast-to-string now supported through the framework
(SPARK-57285), Row JSON
@@ -181,7 +161,6 @@ class RowJsonSuite extends SparkFunSuite with SQLHelper {
def nanosRowJson(value: Any, dt: DataType): JValue =
new GenericRowWithSchema(Array(value), new StructType().add("a",
dt)).jsonValue
withSQLConf(
- SQLConf.TYPES_FRAMEWORK_ENABLED.key -> "true",
SQLConf.TIMESTAMP_NANOS_TYPES_ENABLED.key -> "true",
SQLConf.SESSION_LOCAL_TIMEZONE.key -> "UTC") {
val ldt = LocalDateTime.of(2020, 1, 1, 12, 0, 0, 123456789)
diff --git
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/ops/TimeTypeOpsSuite.scala
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/ops/TimeTypeOpsSuite.scala
new file mode 100644
index 000000000000..c29faef09f5e
--- /dev/null
+++
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/ops/TimeTypeOpsSuite.scala
@@ -0,0 +1,76 @@
+/*
+ * 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.catalyst.types.ops
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.sql.AnalysisException
+import org.apache.spark.sql.catalyst.{DeserializerBuildHelper,
SerializerBuildHelper}
+import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.LocalTimeEncoder
+import org.apache.spark.sql.catalyst.plans.SQLHelper
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types.{ObjectType, TimeType}
+
+/**
+ * Tests for the Types Framework wiring of TimeType.
+ *
+ * The TIME-type-enabled gate lives in TimeTypeOps.createSerializer /
createDeserializer; the
+ * framework dispatch at the head of Serializer/DeserializerBuildHelper routes
LocalTimeEncoder
+ * through it. Disabling spark.sql.timeType.enabled must therefore still
reject building a TIME
+ * serializer/deserializer with UNSUPPORTED_TIME_TYPE, rather than silently
producing one. The
+ * enabled path is asserted too, so the gate is covered in both directions.
+ */
+class TimeTypeOpsSuite extends SparkFunSuite with SQLHelper {
+
+ test("building a TIME serializer is rejected when the TIME type is
disabled") {
+ withSQLConf(SQLConf.TIME_TYPE_ENABLED.key -> "false") {
+ checkError(
+ exception = intercept[AnalysisException] {
+ SerializerBuildHelper.createSerializer(LocalTimeEncoder)
+ },
+ condition = "UNSUPPORTED_TIME_TYPE",
+ parameters = Map.empty[String, String])
+ }
+ }
+
+ test("building a TIME deserializer is rejected when the TIME type is
disabled") {
+ withSQLConf(SQLConf.TIME_TYPE_ENABLED.key -> "false") {
+ checkError(
+ exception = intercept[AnalysisException] {
+ DeserializerBuildHelper.createDeserializer(LocalTimeEncoder)
+ },
+ condition = "UNSUPPORTED_TIME_TYPE",
+ parameters = Map.empty[String, String])
+ }
+ }
+
+ test("building a TIME serializer succeeds when the TIME type is enabled") {
+ withSQLConf(SQLConf.TIME_TYPE_ENABLED.key -> "true") {
+ // The gate passes and the framework builds a TIME serializer.
+ val serializer = SerializerBuildHelper.createSerializer(LocalTimeEncoder)
+ assert(serializer.dataType.isInstanceOf[TimeType])
+ }
+ }
+
+ test("building a TIME deserializer succeeds when the TIME type is enabled") {
+ withSQLConf(SQLConf.TIME_TYPE_ENABLED.key -> "true") {
+ // The gate passes and the framework builds a TIME deserializer
returning java.time.LocalTime.
+ val deserializer =
DeserializerBuildHelper.createDeserializer(LocalTimeEncoder)
+ assert(deserializer.dataType ===
ObjectType(classOf[java.time.LocalTime]))
+ }
+ }
+}
diff --git
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/ops/TimestampNanosTypeOpsSuite.scala
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/ops/TimestampNanosTypeOpsSuite.scala
index b31fe310755f..6633416a0645 100644
---
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/ops/TimestampNanosTypeOpsSuite.scala
+++
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/ops/TimestampNanosTypeOpsSuite.scala
@@ -38,8 +38,7 @@ import org.apache.spark.unsafe.types.{TimestampNanosVal,
UTF8String}
*
* Verifies that TimestampNTZNanosType and TimestampLTZNanosType route
physical representation,
* literals, row accessors, mutable values, codegen class selection,
conversions, and encoders
- * through TypeOps/TypeApiOps. The Types Framework is the sole integration
path for these types, so
- * the suite runs with spark.sql.types.framework.enabled = true (the default
under tests).
+ * through TypeOps/TypeApiOps. The Types Framework is the sole integration
path for these types.
*/
class TimestampNanosTypeOpsSuite extends SparkFunSuite with SQLHelper {
@@ -266,29 +265,4 @@ class TimestampNanosTypeOpsSuite extends SparkFunSuite
with SQLHelper {
OptionEncoder(InstantNanosEncoder(9)),
Seq(Some(Instant.parse("2019-02-26T16:56:00.123456789Z")), None))
}
-
- test("framework disabled leaves the nanos types unsupported (no legacy
fallback)") {
- withSQLConf(SQLConf.TYPES_FRAMEWORK_ENABLED.key -> "false") {
- allCases.foreach { case (dt, _, _) =>
- assert(TypeOps(dt).isEmpty, s"TypeOps should be empty for $dt when
disabled")
- assert(TypeApiOps(dt).isEmpty, s"TypeApiOps should be empty for $dt
when disabled")
- }
- }
- }
-
- test("the nanos types flag only takes effect when the Types Framework is
enabled") {
- // Setting the flag must always succeed (a checkValue consulting
SQLConf.get would recurse
- // into the session conf's own construction); the framework requirement is
enforced in the
- // effective getter instead.
- withSQLConf(
- SQLConf.TIMESTAMP_NANOS_TYPES_ENABLED.key -> "true",
- SQLConf.TYPES_FRAMEWORK_ENABLED.key -> "false") {
- assert(!SQLConf.get.timestampNanosTypesEnabled)
- }
- withSQLConf(
- SQLConf.TIMESTAMP_NANOS_TYPES_ENABLED.key -> "true",
- SQLConf.TYPES_FRAMEWORK_ENABLED.key -> "true") {
- assert(SQLConf.get.timestampNanosTypesEnabled)
- }
- }
}
diff --git
a/sql/connect/common/src/main/scala/org/apache/spark/sql/connect/common/types/ops/ConnectTypeOps.scala
b/sql/connect/common/src/main/scala/org/apache/spark/sql/connect/common/types/ops/ConnectTypeOps.scala
index 3390bf1d0659..7225bc05feef 100644
---
a/sql/connect/common/src/main/scala/org/apache/spark/sql/connect/common/types/ops/ConnectTypeOps.scala
+++
b/sql/connect/common/src/main/scala/org/apache/spark/sql/connect/common/types/ops/ConnectTypeOps.scala
@@ -24,7 +24,6 @@ import org.apache.spark.sql.catalyst.encoders.AgnosticEncoder
import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.LocalTimeEncoder
import org.apache.spark.sql.connect.client.arrow.{ArrowDeserializers,
ArrowSerializer, ArrowVectorReader}
import org.apache.spark.sql.connect.client.arrow.types.ops.TimeTypeConnectOps
-import org.apache.spark.sql.internal.SqlApiConf
import org.apache.spark.sql.types.{DataType, TimeType}
/**
@@ -89,50 +88,42 @@ trait ConnectTypeOps extends Serializable {
/**
* Factory object for ConnectTypeOps lookup.
*
- * Provides separate factory methods for proto (server-side,
feature-flag-gated) and Arrow
- * (client-side, no flag) dispatch.
+ * Provides separate factory methods for proto conversion and Arrow serde
dispatch.
*/
object ConnectTypeOps {
- // ==================== Proto Dispatch (server-side, flag-gated)
====================
+ // ==================== Proto Dispatch ====================
- /** DataType-keyed dispatch for proto conversions. Checks feature flag. */
- def apply(dt: DataType): Option[ConnectTypeOps] = {
- if (!SqlApiConf.get.typesFrameworkEnabled) return None
- dt match {
- case tt: TimeType => Some(new TimeTypeConnectOps(tt))
- // Add new framework types here
- case _ => None
- }
+ /** DataType-keyed dispatch for proto conversions. */
+ def apply(dt: DataType): Option[ConnectTypeOps] = dt match {
+ case tt: TimeType => Some(new TimeTypeConnectOps(tt))
+ // Add new framework types here
+ case _ => None
}
- /** Reverse lookup by value class for the generic literal builder. Checks
feature flag. */
+ /** Reverse lookup by value class for the generic literal builder. */
def toLiteralProtoForValue(
value: Any,
- builder: proto.Expression.Literal.Builder):
Option[proto.Expression.Literal.Builder] = {
- if (!SqlApiConf.get.typesFrameworkEnabled) return None
+ builder: proto.Expression.Literal.Builder):
Option[proto.Expression.Literal.Builder] =
value match {
case v: java.time.LocalTime =>
Some(new TimeTypeConnectOps(TimeType()).toLiteralProto(v, builder))
// Add new framework value types here
case _ => None
}
- }
/**
* Shared KindCase -> ConnectTypeOps lookup. All reverse lookups by proto
enum case dispatch
- * through this single registration point. Checks feature flag.
+ * through this single registration point.
*/
- private def opsForKindCase(kindCase: proto.DataType.KindCase):
Option[ConnectTypeOps] = {
- if (!SqlApiConf.get.typesFrameworkEnabled) return None
+ private def opsForKindCase(kindCase: proto.DataType.KindCase):
Option[ConnectTypeOps] =
kindCase match {
case proto.DataType.KindCase.TIME => Some(new
TimeTypeConnectOps(TimeType()))
// Add new framework proto kinds here - single registration for all
KindCase lookups
case _ => None
}
- }
- /** Reverse lookup: converts a proto DataType to a Spark DataType. Checks
feature flag. */
+ /** Reverse lookup: converts a proto DataType to a Spark DataType. */
def toCatalystType(t: proto.DataType): Option[DataType] =
opsForKindCase(t.getKindCase).map(_.toCatalystTypeFromProto(t))
@@ -155,9 +146,9 @@ object ConnectTypeOps {
case _ => proto.DataType.KindCase.KIND_NOT_SET
}
- // ==================== Arrow Dispatch (client-side, NO flag check)
====================
+ // ==================== Arrow Dispatch ====================
- /** Encoder-keyed dispatch for Arrow serialization. No feature flag check. */
+ /** Encoder-keyed dispatch for Arrow serialization. */
def forEncoder(enc: AgnosticEncoder[_]): Option[ConnectTypeOps] =
enc match {
case LocalTimeEncoder => Some(new TimeTypeConnectOps(TimeType()))
@@ -165,7 +156,7 @@ object ConnectTypeOps {
case _ => None
}
- /** DataType-keyed dispatch for ArrowVectorReader. No feature flag check. */
+ /** DataType-keyed dispatch for ArrowVectorReader. */
def forDataType(dt: DataType): Option[ConnectTypeOps] =
dt match {
case tt: TimeType => Some(new TimeTypeConnectOps(tt))
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/SparkSessionBuilderSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/SparkSessionBuilderSuite.scala
index a2ae074d981d..365ce3ddd01f 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/SparkSessionBuilderSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/SparkSessionBuilderSuite.scala
@@ -92,7 +92,6 @@ class SparkSessionBuilderSuite extends SparkFunSuite with
Eventually {
val session = SparkSession.builder()
.master("local")
.config(SQLConf.TIMESTAMP_NANOS_TYPES_ENABLED.key, value = true)
- .config(SQLConf.TYPES_FRAMEWORK_ENABLED.key, value = true)
.getOrCreate()
assert(session.conf.get(SQLConf.TIMESTAMP_NANOS_TYPES_ENABLED.key) ==
"true")
assert(session.sql("SELECT 1").collect() === Array(Row(1)))
diff --git
a/sql/hive/src/test/resources/conf/binding-policy-exceptions/configs-without-binding-policy-exceptions
b/sql/hive/src/test/resources/conf/binding-policy-exceptions/configs-without-binding-policy-exceptions
index a9d53bdb1036..75a905223e67 100644
---
a/sql/hive/src/test/resources/conf/binding-policy-exceptions/configs-without-binding-policy-exceptions
+++
b/sql/hive/src/test/resources/conf/binding-policy-exceptions/configs-without-binding-policy-exceptions
@@ -1102,7 +1102,6 @@ spark.sql.timestampType
spark.sql.transposeMaxValues
spark.sql.truncateTable.ignorePermissionAcl.enabled
spark.sql.tvf.allowMultipleTableArguments.enabled
-spark.sql.types.framework.enabled
spark.sql.ui.explainMode
spark.sql.ui.retainedExecutions
spark.sql.unionOutputPartitioning
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