docs: [branch-1.1] regenerate release docs for 1.1.0-rc2

docs/source/user-guide/latest/compatibility/expressions/spark-3.4/aggregate.md

@@ -97,4 +97,34 @@ The following cases are not supported by Comet and always fall back to Spark, re
 - Descending order in `WITHIN GROUP (ORDER BY ... DESC)` is not supported.
 - Only numeric input types are supported.
 
+## RegrIntercept
+
+The following incompatibilities cause `RegrIntercept` to fall back to Spark by default. Set `spark.comet.expression.RegrIntercept.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_intercept` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrR2
+
+The following incompatibilities cause `RegrR2` to fall back to Spark by default. Set `spark.comet.expression.RegrR2.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_r2` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrReplacement
+
+The following incompatibilities cause `RegrReplacement` to fall back to Spark by default. Set `spark.comet.expression.RegrReplacement.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_sxx` and `regr_syy` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrSXY
+
+The following incompatibilities cause `RegrSXY` to fall back to Spark by default. Set `spark.comet.expression.RegrSXY.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_sxy` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrSlope
+
+The following incompatibilities cause `RegrSlope` to fall back to Spark by default. Set `spark.comet.expression.RegrSlope.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_slope` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
 <!--END:EXPR_COMPAT-->

docs/source/user-guide/latest/compatibility/expressions/spark-3.4/array.md

@@ -27,6 +27,12 @@ By default, `ArrayContains` is evaluated in the JVM using Spark's own code-gener
 
 - Spark compares array elements with ordering.equiv, so -0.0 matches +0.0 and all NaNs match each other; Comet's native array_contains compares the raw Arrow values bitwise
 
+## ArrayDistinct
+
+The following incompatibilities cause `ArrayDistinct` to fall back to Spark by default. Set `spark.comet.expression.ArrayDistinct.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Floating-point elements match Spark's signed-zero and NaN semantics natively only on Spark 4.2.0, whose optimizer normalizes the arguments (SPARK-54918)
+
 ## ArrayExcept
 
 By default, `ArrayExcept` is evaluated in the JVM using Spark's own code-generated implementation (run inside the Comet pipeline), which matches Spark exactly. Set `spark.comet.expression.ArrayExcept.allowIncompatible=true` to opt into Comet's native implementation instead, which has the following differences from Spark:
@@ -47,6 +53,12 @@ By default, `ArrayJoin` is evaluated in the JVM using Spark's own code-generated
 - array_join does not propagate non-UTF8_BINARY collations to the output string (https://github.com/apache/datafusion-comet/issues/2190)
 - array_join evaluates its delimiter and null replacement eagerly, while Spark short-circuits past them (https://github.com/apache/datafusion-comet/issues/3178)
 
+## ArrayUnion
+
+The following incompatibilities cause `ArrayUnion` to fall back to Spark by default. Set `spark.comet.expression.ArrayUnion.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Floating-point elements match Spark's signed-zero and NaN semantics natively only on Spark 4.2.0, whose optimizer normalizes the arguments (SPARK-54918)
+
 ## ArraysZip
 
 The following cases are not supported by Comet and always fall back to Spark, regardless of any `allowIncompatible` setting:

docs/source/user-guide/latest/compatibility/expressions/spark-3.5/aggregate.md

@@ -97,4 +97,34 @@ The following cases are not supported by Comet and always fall back to Spark, re
 - Descending order in `WITHIN GROUP (ORDER BY ... DESC)` is not supported.
 - Only numeric input types are supported.
 
+## RegrIntercept
+
+The following incompatibilities cause `RegrIntercept` to fall back to Spark by default. Set `spark.comet.expression.RegrIntercept.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_intercept` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrR2
+
+The following incompatibilities cause `RegrR2` to fall back to Spark by default. Set `spark.comet.expression.RegrR2.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_r2` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrReplacement
+
+The following incompatibilities cause `RegrReplacement` to fall back to Spark by default. Set `spark.comet.expression.RegrReplacement.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_sxx` and `regr_syy` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrSXY
+
+The following incompatibilities cause `RegrSXY` to fall back to Spark by default. Set `spark.comet.expression.RegrSXY.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_sxy` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrSlope
+
+The following incompatibilities cause `RegrSlope` to fall back to Spark by default. Set `spark.comet.expression.RegrSlope.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_slope` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
 <!--END:EXPR_COMPAT-->

docs/source/user-guide/latest/compatibility/expressions/spark-3.5/array.md

@@ -27,6 +27,12 @@ By default, `ArrayContains` is evaluated in the JVM using Spark's own code-gener
 
 - Spark compares array elements with ordering.equiv, so -0.0 matches +0.0 and all NaNs match each other; Comet's native array_contains compares the raw Arrow values bitwise
 
+## ArrayDistinct
+
+The following incompatibilities cause `ArrayDistinct` to fall back to Spark by default. Set `spark.comet.expression.ArrayDistinct.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Floating-point elements match Spark's signed-zero and NaN semantics natively only on Spark 4.2.0, whose optimizer normalizes the arguments (SPARK-54918)
+
 ## ArrayExcept
 
 By default, `ArrayExcept` is evaluated in the JVM using Spark's own code-generated implementation (run inside the Comet pipeline), which matches Spark exactly. Set `spark.comet.expression.ArrayExcept.allowIncompatible=true` to opt into Comet's native implementation instead, which has the following differences from Spark:
@@ -47,6 +53,12 @@ By default, `ArrayJoin` is evaluated in the JVM using Spark's own code-generated
 - array_join does not propagate non-UTF8_BINARY collations to the output string (https://github.com/apache/datafusion-comet/issues/2190)
 - array_join evaluates its delimiter and null replacement eagerly, while Spark short-circuits past them (https://github.com/apache/datafusion-comet/issues/3178)
 
+## ArrayUnion
+
+The following incompatibilities cause `ArrayUnion` to fall back to Spark by default. Set `spark.comet.expression.ArrayUnion.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Floating-point elements match Spark's signed-zero and NaN semantics natively only on Spark 4.2.0, whose optimizer normalizes the arguments (SPARK-54918)
+
 ## ArraysZip
 
 The following cases are not supported by Comet and always fall back to Spark, regardless of any `allowIncompatible` setting:

docs/source/user-guide/latest/compatibility/expressions/spark-4.0/aggregate.md

@@ -106,4 +106,34 @@ The following cases are not supported by Comet and always fall back to Spark, re
 - Descending order in `WITHIN GROUP (ORDER BY ... DESC)` is not supported.
 - Only numeric input types are supported.
 
+## RegrIntercept
+
+The following incompatibilities cause `RegrIntercept` to fall back to Spark by default. Set `spark.comet.expression.RegrIntercept.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_intercept` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrR2
+
+The following incompatibilities cause `RegrR2` to fall back to Spark by default. Set `spark.comet.expression.RegrR2.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_r2` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrReplacement
+
+The following incompatibilities cause `RegrReplacement` to fall back to Spark by default. Set `spark.comet.expression.RegrReplacement.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_sxx` and `regr_syy` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrSXY
+
+The following incompatibilities cause `RegrSXY` to fall back to Spark by default. Set `spark.comet.expression.RegrSXY.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_sxy` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrSlope
+
+The following incompatibilities cause `RegrSlope` to fall back to Spark by default. Set `spark.comet.expression.RegrSlope.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_slope` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
 <!--END:EXPR_COMPAT-->

docs/source/user-guide/latest/compatibility/expressions/spark-4.0/array.md

@@ -27,6 +27,12 @@ By default, `ArrayContains` is evaluated in the JVM using Spark's own code-gener
 
 - Spark compares array elements with ordering.equiv, so -0.0 matches +0.0 and all NaNs match each other; Comet's native array_contains compares the raw Arrow values bitwise
 
+## ArrayDistinct
+
+The following incompatibilities cause `ArrayDistinct` to fall back to Spark by default. Set `spark.comet.expression.ArrayDistinct.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Floating-point elements match Spark's signed-zero and NaN semantics natively only on Spark 4.2.0, whose optimizer normalizes the arguments (SPARK-54918)
+
 ## ArrayExcept
 
 By default, `ArrayExcept` is evaluated in the JVM using Spark's own code-generated implementation (run inside the Comet pipeline), which matches Spark exactly. Set `spark.comet.expression.ArrayExcept.allowIncompatible=true` to opt into Comet's native implementation instead, which has the following differences from Spark:
@@ -47,6 +53,12 @@ By default, `ArrayJoin` is evaluated in the JVM using Spark's own code-generated
 - array_join does not propagate non-UTF8_BINARY collations to the output string (https://github.com/apache/datafusion-comet/issues/2190)
 - array_join evaluates its delimiter and null replacement eagerly, while Spark short-circuits past them (https://github.com/apache/datafusion-comet/issues/3178)
 
+## ArrayUnion
+
+The following incompatibilities cause `ArrayUnion` to fall back to Spark by default. Set `spark.comet.expression.ArrayUnion.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Floating-point elements match Spark's signed-zero and NaN semantics natively only on Spark 4.2.0, whose optimizer normalizes the arguments (SPARK-54918)
+
 ## ArraysZip
 
 The following cases are not supported by Comet and always fall back to Spark, regardless of any `allowIncompatible` setting:

docs/source/user-guide/latest/compatibility/expressions/spark-4.1/aggregate.md

@@ -106,4 +106,34 @@ The following cases are not supported by Comet and always fall back to Spark, re
 - Descending order in `WITHIN GROUP (ORDER BY ... DESC)` is not supported.
 - Only numeric input types are supported.
 
+## RegrIntercept
+
+The following incompatibilities cause `RegrIntercept` to fall back to Spark by default. Set `spark.comet.expression.RegrIntercept.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_intercept` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrR2
+
+The following incompatibilities cause `RegrR2` to fall back to Spark by default. Set `spark.comet.expression.RegrR2.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_r2` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrReplacement
+
+The following incompatibilities cause `RegrReplacement` to fall back to Spark by default. Set `spark.comet.expression.RegrReplacement.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_sxx` and `regr_syy` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrSXY
+
+The following incompatibilities cause `RegrSXY` to fall back to Spark by default. Set `spark.comet.expression.RegrSXY.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_sxy` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
+## RegrSlope
+
+The following incompatibilities cause `RegrSlope` to fall back to Spark by default. Set `spark.comet.expression.RegrSlope.allowIncompatible=true` to enable Comet acceleration despite these differences.
+
+- Comet merges the partial aggregates of `regr_slope` in a different floating-point operation order from Spark. When a group's rows come from more than one partial aggregate and a variable is constant at a value that binary floating point cannot represent exactly, such as 0.1, Comet returns a wrong value where Spark returns NULL, 0.0 or 1.0 (https://github.com/apache/datafusion-comet/issues/6423)
+
 <!--END:EXPR_COMPAT-->