fix: regressions in CometToPrettyStringSuite

.github/workflows/pr_build_linux.yml

@@ -149,6 +149,9 @@ jobs:
               org.apache.comet.CometBitwiseExpressionSuite
               org.apache.comet.CometMapExpressionSuite
               org.apache.comet.objectstore.NativeConfigSuite
+          - name: "sql"
+            value: |
+              ${{ matrix.profile.maven_opts != 'Spark 3.4, JDK 11, Scala 2.12' && 'org.apache.spark.sql.CometToPrettyStringSuite' || ''}}
       fail-fast: false
     name: ${{ matrix.os }}/${{ matrix.profile.name }} [${{ matrix.suite.name }}]
     runs-on: ${{ matrix.os }}

.github/workflows/pr_build_macos.yml

@@ -114,6 +114,9 @@ jobs:
               org.apache.comet.CometBitwiseExpressionSuite
               org.apache.comet.CometMapExpressionSuite
               org.apache.comet.objectstore.NativeConfigSuite
+          - name: "sql"
+            value: |
+              ${{ matrix.profile.maven_opts != 'Spark 3.4, JDK 11, Scala 2.12' && 'org.apache.spark.sql.CometToPrettyStringSuite' || ''}}
       fail-fast: false
     name: ${{ matrix.os }}/${{ matrix.profile.name }} [${{ matrix.suite.name }}]
     runs-on: ${{ matrix.os }}

dev/ci/check-suites.py

@@ -36,10 +36,7 @@ def file_to_class_name(path: Path) -> str | None:
         "org.apache.comet.parquet.ParquetReadFromS3Suite", # manual test suite
         "org.apache.spark.sql.comet.CometPlanStabilitySuite", # abstract
         "org.apache.spark.sql.comet.ParquetDatetimeRebaseSuite", # abstract
-        "org.apache.comet.exec.CometColumnarShuffleSuite", # abstract
-        # TODO add CometToPrettyStringSuite to PR worklows
-        # https://github.com/apache/datafusion-comet/issues/2307
-        "org.apache.spark.sql.CometToPrettyStringSuite"
+        "org.apache.comet.exec.CometColumnarShuffleSuite" # abstract
     ]
 
     for workflow_filename in [".github/workflows/pr_build_linux.yml", ".github/workflows/pr_build_macos.yml"]:

docs/source/user-guide/latest/compatibility.md

@@ -210,6 +210,7 @@ The following cast operations are generally compatible with Spark except for the
 | string | long |  |
 | string | binary |  |
 | string | date | Only supports years between 262143 BC and 262142 AD |
+| binary | string |  |
 | date | string |  |
 | timestamp | long |  |
 | timestamp | string |  |
@@ -233,7 +234,6 @@ The following cast operations are not compatible with Spark for all inputs and a
 | string | double  | Does not support inputs ending with 'd' or 'f'. Does not support 'inf'. Does not support ANSI mode. |
 | string | decimal  | Does not support inputs ending with 'd' or 'f'. Does not support 'inf'. Does not support ANSI mode. Returns 0.0 instead of null if input contains no digits |
 | string | timestamp  | Not all valid formats are supported |
-| binary | string  | Only works for binary data representing valid UTF-8 strings |
 <!--END:INCOMPAT_CAST_TABLE-->
 
 ### Unsupported Casts

native/core/src/execution/planner.rs

@@ -62,8 +62,8 @@ use datafusion::{
     prelude::SessionContext,
 };
 use datafusion_comet_spark_expr::{
-    create_comet_physical_fun, create_modulo_expr, create_negate_expr, BloomFilterAgg,
-    BloomFilterMightContain, EvalMode, SparkHour, SparkMinute, SparkSecond,
+    create_comet_physical_fun, create_modulo_expr, create_negate_expr, BinaryOutputStyle,
+    BloomFilterAgg, BloomFilterMightContain, EvalMode, SparkHour, SparkMinute, SparkSecond,
 };
 
 use crate::execution::operators::ExecutionError::GeneralError;
@@ -809,6 +809,8 @@ impl PhysicalPlanner {
                     SparkCastOptions::new(EvalMode::Try, &expr.timezone, true);
                 let null_string = "NULL";
                 spark_cast_options.null_string = null_string.to_string();
+                spark_cast_options.binary_output_style =
+                    from_protobuf_binary_output_style(expr.binary_output_style).ok();
                 let child = self.create_expr(expr.child.as_ref().unwrap(), input_schema)?;
                 let cast = Arc::new(Cast::new(
                     Arc::clone(&child),
@@ -2693,6 +2695,18 @@ fn create_case_expr(
     }
 }
 
+fn from_protobuf_binary_output_style(
+    value: i32,
+) -> Result<BinaryOutputStyle, prost::UnknownEnumValue> {
+    match spark_expression::BinaryOutputStyle::try_from(value)? {
+        spark_expression::BinaryOutputStyle::Utf8 => Ok(BinaryOutputStyle::Utf8),
+        spark_expression::BinaryOutputStyle::Basic => Ok(BinaryOutputStyle::Basic),
+        spark_expression::BinaryOutputStyle::Base64 => Ok(BinaryOutputStyle::Base64),
+        spark_expression::BinaryOutputStyle::Hex => Ok(BinaryOutputStyle::Hex),
+        spark_expression::BinaryOutputStyle::HexDiscrete => Ok(BinaryOutputStyle::HexDiscrete),
+    }
+}
+
 fn literal_to_array_ref(
     data_type: DataType,
     list_literal: ListLiteral,

native/proto/src/proto/expr.proto

@@ -269,9 +269,18 @@ message ToJson {
   bool ignore_null_fields = 6;
 }
 
+enum BinaryOutputStyle {
+  UTF8 = 0;
+  BASIC = 1;
+  BASE64 = 2;
+  HEX = 3;
+  HEX_DISCRETE = 4;
+}
+
 message ToPrettyString {
   Expr child = 1;
   string timezone = 2;
+  BinaryOutputStyle binaryOutputStyle = 3;
 }
 
 message Hour {

native/spark-expr/Cargo.toml

@@ -37,6 +37,8 @@ thiserror = { workspace = true }
 futures = { workspace = true }
 twox-hash = "2.1.2"
 rand = { workspace = true }
+hex = "0.4.3"
+base64 = "0.22.1"
 
 [dev-dependencies]
 arrow = {workspace = true}

native/spark-expr/src/conversion_funcs/cast.rs

@@ -15,13 +15,15 @@
 // specific language governing permissions and limitations
 // under the License.
 
-use crate::timezone;
 use crate::utils::array_with_timezone;
+use crate::{timezone, BinaryOutputStyle};
 use crate::{EvalMode, SparkError, SparkResult};
 use arrow::array::builder::StringBuilder;
-use arrow::array::{DictionaryArray, StringArray, StructArray};
+use arrow::array::{DictionaryArray, GenericByteArray, StringArray, StructArray};
 use arrow::compute::can_cast_types;
-use arrow::datatypes::{ArrowDictionaryKeyType, ArrowNativeType, DataType, Schema};
+use arrow::datatypes::{
+    ArrowDictionaryKeyType, ArrowNativeType, DataType, GenericBinaryType, Schema,
+};
 use arrow::{
     array::{
         cast::AsArray,
@@ -60,6 +62,8 @@ use std::{
     sync::Arc,
 };
 
+use base64::prelude::*;
+
 static TIMESTAMP_FORMAT: Option<&str> = Some("%Y-%m-%d %H:%M:%S%.f");
 
 const MICROS_PER_SECOND: i64 = 1000000;
@@ -260,11 +264,7 @@ fn can_cast_to_string(from_type: &DataType, options: &SparkCastOptions) -> bool
             // scientific notation where Comet does not
             true
         }
-        Binary => {
-            // https://github.com/apache/datafusion-comet/issues/377
-            // Only works for binary data representing valid UTF-8 strings
-            options.allow_incompat
-        }
+        Binary => true,
         Struct(fields) => fields
             .iter()
             .all(|f| can_cast_to_string(f.data_type(), options)),
@@ -816,6 +816,8 @@ pub struct SparkCastOptions {
     pub is_adapting_schema: bool,
     /// String to use to represent null values
     pub null_string: String,
+    /// SparkSQL's binaryOutputStyle
+    pub binary_output_style: Option<BinaryOutputStyle>,
 }
 
 impl SparkCastOptions {
@@ -827,6 +829,7 @@ impl SparkCastOptions {
             allow_cast_unsigned_ints: false,
             is_adapting_schema: false,
             null_string: "null".to_string(),
+            binary_output_style: None,
         }
     }
 
@@ -838,6 +841,7 @@ impl SparkCastOptions {
             allow_cast_unsigned_ints: false,
             is_adapting_schema: false,
             null_string: "null".to_string(),
+            binary_output_style: None,
         }
     }
 }
@@ -1027,6 +1031,7 @@ fn cast_array(
         {
             Ok(cast_with_options(&array, to_type, &CAST_OPTIONS)?)
         }
+        (Binary, Utf8) => Ok(cast_binary_to_string::<i32>(&array, cast_options)?),
         _ if cast_options.is_adapting_schema
             || is_datafusion_spark_compatible(from_type, to_type, cast_options.allow_incompat) =>
         {
@@ -1045,6 +1050,74 @@ fn cast_array(
     Ok(spark_cast_postprocess(cast_result?, from_type, to_type))
 }
 
+fn cast_binary_to_string<O: OffsetSizeTrait>(
+    array: &dyn Array,
+    spark_cast_options: &SparkCastOptions,
+) -> Result<ArrayRef, ArrowError> {
+    let input = array
+        .as_any()
+        .downcast_ref::<GenericByteArray<GenericBinaryType<O>>>()
+        .unwrap();
+
+    fn binary_formatter(value: &[u8], spark_cast_options: &SparkCastOptions) -> String {
+        match spark_cast_options.binary_output_style {
+            Some(s) => spark_binary_formatter(value, s),
+            None => cast_binary_formatter(value),
+        }
+    }
+
+    let output_array = input
+        .iter()
+        .map(|value| match value {
+            Some(value) => Ok(Some(binary_formatter(value, spark_cast_options))),
+            _ => Ok(None),
+        })
+        .collect::<Result<GenericStringArray<O>, ArrowError>>()?;
+    Ok(Arc::new(output_array))
+}
+
+/// This function mimics the [BinaryFormatter]: https://github.com/apache/spark/blob/v4.0.0/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ToStringBase.scala#L449-L468
+/// used by SparkSQL's ToPrettyString expression.
+/// The BinaryFormatter was [introduced]: https://issues.apache.org/jira/browse/SPARK-47911 in Spark 4.0.0
+/// Before Spark 4.0.0, the default is SPACE_DELIMITED_UPPERCASE_HEX
+fn spark_binary_formatter(value: &[u8], binary_output_style: BinaryOutputStyle) -> String {
+    match binary_output_style {
+        BinaryOutputStyle::Utf8 => String::from_utf8(value.to_vec()).unwrap(),
+        BinaryOutputStyle::Basic => {
+            format!(
+                "{:?}",
+                value
+                    .iter()
+                    .map(|v| i8::from_ne_bytes([*v]))
+                    .collect::<Vec<i8>>()
+            )
+        }
+        BinaryOutputStyle::Base64 => BASE64_STANDARD_NO_PAD.encode(value),
+        BinaryOutputStyle::Hex => value
+            .iter()
+            .map(|v| hex::encode_upper([*v]))
+            .collect::<String>(),
+        BinaryOutputStyle::HexDiscrete => {
+            // Spark's default SPACE_DELIMITED_UPPERCASE_HEX
+            format!(
+                "[{}]",
+                value
+                    .iter()
+                    .map(|v| hex::encode_upper([*v]))
+                    .collect::<Vec<String>>()
+                    .join(" ")
+            )
+        }
+    }
+}
+
+fn cast_binary_formatter(value: &[u8]) -> String {
+    match String::from_utf8(value.to_vec()) {
+        Ok(value) => value,
+        Err(_) => unsafe { String::from_utf8_unchecked(value.to_vec()) },
+    }
+}
+
 /// Determines if DataFusion supports the given cast in a way that is
 /// compatible with Spark
 fn is_datafusion_spark_compatible(

native/spark-expr/src/lib.rs

@@ -98,6 +98,15 @@ pub enum EvalMode {
     Try,
 }
 
+#[derive(Debug, Hash, PartialEq, Eq, Clone, Copy)]
+pub enum BinaryOutputStyle {
+    Utf8,
+    Basic,
+    Base64,
+    Hex,
+    HexDiscrete,
+}
+
 pub(crate) fn arithmetic_overflow_error(from_type: &str) -> SparkError {
     SparkError::ArithmeticOverflow {
         from_type: from_type.to_string(),

spark/src/main/scala/org/apache/comet/expressions/CometCast.scala

@@ -215,8 +215,7 @@ object CometCast extends CometExpressionSerde[Cast] with CometExprShim {
             "There can be formatting differences in some case due to Spark using " +
               "scientific notation where Comet does not"))
       case DataTypes.BinaryType =>
-        // https://github.com/apache/datafusion-comet/issues/377
-        Incompatible(Some("Only works for binary data representing valid UTF-8 strings"))
+        Compatible()
       case StructType(fields) =>
         for (field <- fields) {
           isSupported(field.dataType, DataTypes.StringType, timeZoneId, evalMode) match {

spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala

@@ -716,6 +716,7 @@ object QueryPlanSerde extends Logging with CometExprShim {
                 .newBuilder()
                 .setChild(p)
                 .setTimezone(timezoneId.getOrElse("UTC"))
+                .setBinaryOutputStyle(binaryOutputStyle)
                 .build()
               Some(
                 ExprOuterClass.Expr

spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala

@@ -20,7 +20,7 @@ package org.apache.comet.shims
 
 import org.apache.comet.expressions.CometEvalMode
 import org.apache.comet.serde.CommonStringExprs
-import org.apache.comet.serde.ExprOuterClass.Expr
+import org.apache.comet.serde.ExprOuterClass.{BinaryOutputStyle, Expr}
 import org.apache.spark.sql.catalyst.expressions._
 
 /**
@@ -30,6 +30,8 @@ trait CometExprShim extends CommonStringExprs {
     protected def evalMode(c: Cast): CometEvalMode.Value =
         CometEvalModeUtil.fromSparkEvalMode(c.evalMode)
 
+    protected def binaryOutputStyle: BinaryOutputStyle = BinaryOutputStyle.HEX_DISCRETE
+
     def versionSpecificExprToProtoInternal(
         expr: Expression,
         inputs: Seq[Attribute],

spark/src/main/spark-3.5/org/apache/comet/shims/CometExprShim.scala

@@ -20,7 +20,7 @@ package org.apache.comet.shims
 
 import org.apache.comet.expressions.CometEvalMode
 import org.apache.comet.serde.CommonStringExprs
-import org.apache.comet.serde.ExprOuterClass.Expr
+import org.apache.comet.serde.ExprOuterClass.{BinaryOutputStyle, Expr}
 import org.apache.spark.sql.catalyst.expressions._
 
 /**
@@ -30,6 +30,8 @@ trait CometExprShim extends CommonStringExprs {
     protected def evalMode(c: Cast): CometEvalMode.Value =
         CometEvalModeUtil.fromSparkEvalMode(c.evalMode)
 
+  protected def binaryOutputStyle: BinaryOutputStyle = BinaryOutputStyle.HEX_DISCRETE
+
     def versionSpecificExprToProtoInternal(
         expr: Expression,
         inputs: Seq[Attribute],

spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala

@@ -20,9 +20,10 @@ package org.apache.comet.shims
 
 import org.apache.comet.expressions.CometEvalMode
 import org.apache.comet.serde.CommonStringExprs
-import org.apache.comet.serde.ExprOuterClass.Expr
+import org.apache.comet.serde.ExprOuterClass.{BinaryOutputStyle, Expr}
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.expressions.objects.StaticInvoke
+import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.internal.types.StringTypeWithCollation
 import org.apache.spark.sql.types.{BinaryType, BooleanType, StringType}
 
@@ -33,6 +34,16 @@ trait CometExprShim extends CommonStringExprs {
     protected def evalMode(c: Cast): CometEvalMode.Value =
         CometEvalModeUtil.fromSparkEvalMode(c.evalMode)
 
+    protected def binaryOutputStyle: BinaryOutputStyle = {
+        SQLConf.get.getConf(SQLConf.BINARY_OUTPUT_STYLE).map(SQLConf.BinaryOutputStyle.withName) match {
+        case Some(SQLConf.BinaryOutputStyle.UTF8) => BinaryOutputStyle.UTF8
+        case Some(SQLConf.BinaryOutputStyle.BASIC) => BinaryOutputStyle.BASIC
+        case Some(SQLConf.BinaryOutputStyle.BASE64) => BinaryOutputStyle.BASE64
+        case Some(SQLConf.BinaryOutputStyle.HEX) => BinaryOutputStyle.HEX
+        case _ => BinaryOutputStyle.HEX_DISCRETE
+      }
+    }
+
     def versionSpecificExprToProtoInternal(
         expr: Expression,
         inputs: Seq[Attribute],

spark/src/test/scala/org/apache/comet/CometCastSuite.scala

@@ -827,8 +827,7 @@ class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper {
 
   // CAST from BinaryType
 
-  ignore("cast BinaryType to StringType") {
-    // https://github.com/apache/datafusion-comet/issues/377
+  test("cast BinaryType to StringType") {
     castTest(generateBinary(), DataTypes.StringType)
   }