perf: Optimize contains expression with SIMD-based scalar pattern sea…

native/spark-expr/Cargo.toml

@@ -31,6 +31,7 @@ arrow = { workspace = true }
 chrono = { workspace = true }
 datafusion = { workspace = true }
 chrono-tz = { workspace = true }
+memchr = "2.7"
 num = { workspace = true }
 regex = { workspace = true }
 serde_json = "1.0"

native/spark-expr/src/comet_scalar_funcs.rs

@@ -22,8 +22,8 @@ use crate::math_funcs::modulo_expr::spark_modulo;
 use crate::{
     spark_array_repeat, spark_ceil, spark_decimal_div, spark_decimal_integral_div, spark_floor,
     spark_isnan, spark_lpad, spark_make_decimal, spark_read_side_padding, spark_round, spark_rpad,
-    spark_unhex, spark_unscaled_value, EvalMode, SparkBitwiseCount, SparkDateTrunc, SparkSizeFunc,
-    SparkStringSpace,
+    spark_unhex, spark_unscaled_value, EvalMode, SparkBitwiseCount, SparkContains, SparkDateTrunc,
+    SparkSizeFunc, SparkStringSpace,
 };
 use arrow::datatypes::DataType;
 use datafusion::common::{DataFusionError, Result as DataFusionResult};
@@ -192,6 +192,7 @@ pub fn create_comet_physical_fun_with_eval_mode(
 fn all_scalar_functions() -> Vec<Arc<ScalarUDF>> {
     vec![
         Arc::new(ScalarUDF::new_from_impl(SparkBitwiseCount::default())),
+        Arc::new(ScalarUDF::new_from_impl(SparkContains::default())),
         Arc::new(ScalarUDF::new_from_impl(SparkDateTrunc::default())),
         Arc::new(ScalarUDF::new_from_impl(SparkStringSpace::default())),
         Arc::new(ScalarUDF::new_from_impl(SparkSizeFunc::default())),

native/spark-expr/src/string_funcs/contains.rs

@@ -0,0 +1,282 @@
+// 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.
+
+//! Optimized `contains` string function for Spark compatibility.
+//!
+//! This implementation is optimized for the common case where the pattern
+//! (second argument) is a scalar value. In this case, we use `memchr::memmem::Finder`
+//! which is SIMD-optimized and reuses a single finder instance across all rows.
+//!
+//! The DataFusion built-in `contains` function uses `make_scalar_function` which
+//! expands scalar values to arrays, losing the performance benefit of the optimized
+//! scalar path in arrow-rs.
+
+use arrow::array::{Array, ArrayRef, AsArray, BooleanArray};
+use arrow::compute::kernels::comparison::contains as arrow_contains;
+use arrow::datatypes::DataType;
+use datafusion::common::{exec_err, Result, ScalarValue};
+use datafusion::logical_expr::{
+    ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility,
+};
+use memchr::memmem::Finder;
+use std::any::Any;
+use std::sync::Arc;
+
+/// Spark-optimized contains function.
+///
+/// Returns true if the first string argument contains the second string argument.
+/// Optimized for the common case where the pattern is a scalar constant.
+#[derive(Debug, PartialEq, Eq, Hash)]
+pub struct SparkContains {
+    signature: Signature,
+}
+
+impl Default for SparkContains {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl SparkContains {
+    pub fn new() -> Self {
+        Self {
+            signature: Signature::variadic_any(Volatility::Immutable),
+        }
+    }
+}
+
+impl ScalarUDFImpl for SparkContains {
+    fn as_any(&self) -> &dyn Any {
+        self
+    }
+
+    fn name(&self) -> &str {
+        "contains"
+    }
+
+    fn signature(&self) -> &Signature {
+        &self.signature
+    }
+
+    fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
+        Ok(DataType::Boolean)
+    }
+
+    fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> {
+        if args.args.len() != 2 {
+            return exec_err!("contains function requires exactly 2 arguments");
+        }
+        spark_contains(&args.args[0], &args.args[1])
+    }
+}
+
+/// Execute the contains function with optimized scalar pattern handling.
+fn spark_contains(haystack: &ColumnarValue, needle: &ColumnarValue) -> Result<ColumnarValue> {
+    match (haystack, needle) {
+        // Case 1: Both are arrays - use arrow's contains directly
+        (ColumnarValue::Array(haystack_array), ColumnarValue::Array(needle_array)) => {
+            let result = arrow_contains(haystack_array, needle_array)?;
+            Ok(ColumnarValue::Array(Arc::new(result)))
+        }
+
+        // Case 2: Haystack is array, needle is scalar - OPTIMIZED PATH
+        // This is the common case in SQL like: WHERE col CONTAINS 'pattern'
+        (ColumnarValue::Array(haystack_array), ColumnarValue::Scalar(needle_scalar)) => {
+            let result = contains_with_scalar_pattern(haystack_array, needle_scalar)?;
+            Ok(ColumnarValue::Array(result))
+        }
+
+        // Case 3: Haystack is scalar, needle is array - less common
+        (ColumnarValue::Scalar(haystack_scalar), ColumnarValue::Array(needle_array)) => {
+            // Convert scalar to array and use arrow's contains
+            let haystack_array = haystack_scalar.to_array_of_size(needle_array.len())?;
+            let result = arrow_contains(&haystack_array, needle_array)?;
+            Ok(ColumnarValue::Array(Arc::new(result)))
+        }
+
+        // Case 4: Both are scalars - compute single result
+        (ColumnarValue::Scalar(haystack_scalar), ColumnarValue::Scalar(needle_scalar)) => {
+            let result = contains_scalar_scalar(haystack_scalar, needle_scalar)?;
+            Ok(ColumnarValue::Scalar(result))
+        }
+    }
+}
+
+/// Optimized contains for array haystack with scalar needle pattern.
+/// Uses memchr's SIMD-optimized Finder for efficient repeated searches.
+fn contains_with_scalar_pattern(
+    haystack_array: &ArrayRef,
+    needle_scalar: &ScalarValue,
+) -> Result<ArrayRef> {
+    // Handle null needle
+    if needle_scalar.is_null() {
+        return Ok(Arc::new(BooleanArray::new_null(haystack_array.len())));
+    }
+
+    // Extract the needle string
+    let needle_str = match needle_scalar {
+        ScalarValue::Utf8(Some(s))
+        | ScalarValue::LargeUtf8(Some(s))
+        | ScalarValue::Utf8View(Some(s)) => s.as_str(),
+        _ => {
+            return exec_err!(
+                "contains function requires string type for needle, got {:?}",
+                needle_scalar.data_type()
+            )
+        }
+    };
+
+    // Create a reusable Finder for efficient SIMD-optimized searching
+    let finder = Finder::new(needle_str.as_bytes());
+
+    match haystack_array.data_type() {
+        DataType::Utf8 => {
+            let array = haystack_array.as_string::<i32>();
+            let result: BooleanArray = array
+                .iter()
+                .map(|opt_haystack| opt_haystack.map(|h| finder.find(h.as_bytes()).is_some()))
+                .collect();
+            Ok(Arc::new(result))
+        }
+        DataType::LargeUtf8 => {
+            let array = haystack_array.as_string::<i64>();
+            let result: BooleanArray = array
+                .iter()
+                .map(|opt_haystack| opt_haystack.map(|h| finder.find(h.as_bytes()).is_some()))
+                .collect();
+            Ok(Arc::new(result))
+        }
+        DataType::Utf8View => {
+            let array = haystack_array.as_string_view();
+            let result: BooleanArray = array
+                .iter()
+                .map(|opt_haystack| opt_haystack.map(|h| finder.find(h.as_bytes()).is_some()))
+                .collect();
+            Ok(Arc::new(result))
+        }
+        other => exec_err!(
+            "contains function requires string type for haystack, got {:?}",
+            other
+        ),
+    }
+}
+
+/// Contains for two scalar values.
+fn contains_scalar_scalar(
+    haystack_scalar: &ScalarValue,
+    needle_scalar: &ScalarValue,
+) -> Result<ScalarValue> {
+    // Handle nulls
+    if haystack_scalar.is_null() || needle_scalar.is_null() {
+        return Ok(ScalarValue::Boolean(None));
+    }
+
+    let haystack_str = match haystack_scalar {
+        ScalarValue::Utf8(Some(s))
+        | ScalarValue::LargeUtf8(Some(s))
+        | ScalarValue::Utf8View(Some(s)) => s.as_str(),
+        _ => {
+            return exec_err!(
+                "contains function requires string type for haystack, got {:?}",
+                haystack_scalar.data_type()
+            )
+        }
+    };
+
+    let needle_str = match needle_scalar {
+        ScalarValue::Utf8(Some(s))
+        | ScalarValue::LargeUtf8(Some(s))
+        | ScalarValue::Utf8View(Some(s)) => s.as_str(),
+        _ => {
+            return exec_err!(
+                "contains function requires string type for needle, got {:?}",
+                needle_scalar.data_type()
+            )
+        }
+    };
+
+    Ok(ScalarValue::Boolean(Some(
+        haystack_str.contains(needle_str),
+    )))
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use arrow::array::StringArray;
+
+    #[test]
+    fn test_contains_array_scalar() {
+        let haystack = Arc::new(StringArray::from(vec![
+            Some("hello world"),
+            Some("foo bar"),
+            Some("testing"),
+            None,
+        ])) as ArrayRef;
+        let needle = ScalarValue::Utf8(Some("world".to_string()));
+
+        let result = contains_with_scalar_pattern(&haystack, &needle).unwrap();
+        let bool_array = result.as_any().downcast_ref::<BooleanArray>().unwrap();
+
+        assert!(bool_array.value(0)); // "hello world" contains "world"
+        assert!(!bool_array.value(1)); // "foo bar" does not contain "world"
+        assert!(!bool_array.value(2)); // "testing" does not contain "world"
+        assert!(bool_array.is_null(3)); // null input => null output
+    }
+
+    #[test]
+    fn test_contains_scalar_scalar() {
+        let haystack = ScalarValue::Utf8(Some("hello world".to_string()));
+        let needle = ScalarValue::Utf8(Some("world".to_string()));
+
+        let result = contains_scalar_scalar(&haystack, &needle).unwrap();
+        assert_eq!(result, ScalarValue::Boolean(Some(true)));
+
+        let needle_not_found = ScalarValue::Utf8(Some("xyz".to_string()));
+        let result = contains_scalar_scalar(&haystack, &needle_not_found).unwrap();
+        assert_eq!(result, ScalarValue::Boolean(Some(false)));
+    }
+
+    #[test]
+    fn test_contains_null_needle() {
+        let haystack = Arc::new(StringArray::from(vec![
+            Some("hello world"),
+            Some("foo bar"),
+        ])) as ArrayRef;
+        let needle = ScalarValue::Utf8(None);
+
+        let result = contains_with_scalar_pattern(&haystack, &needle).unwrap();
+        let bool_array = result.as_any().downcast_ref::<BooleanArray>().unwrap();
+
+        // Null needle should produce null results
+        assert!(bool_array.is_null(0));
+        assert!(bool_array.is_null(1));
+    }
+
+    #[test]
+    fn test_contains_empty_needle() {
+        let haystack = Arc::new(StringArray::from(vec![Some("hello world"), Some("")])) as ArrayRef;
+        let needle = ScalarValue::Utf8(Some("".to_string()));
+
+        let result = contains_with_scalar_pattern(&haystack, &needle).unwrap();
+        let bool_array = result.as_any().downcast_ref::<BooleanArray>().unwrap();
+
+        // Empty string is contained in any string
+        assert!(bool_array.value(0));
+        assert!(bool_array.value(1));
+    }
+}

native/spark-expr/src/string_funcs/mod.rs

@@ -15,8 +15,10 @@
 // specific language governing permissions and limitations
 // under the License.
 
+mod contains;
 mod string_space;
 mod substring;
 
+pub use contains::SparkContains;
 pub use string_space::SparkStringSpace;
 pub use substring::SubstringExpr;

spark/src/main/scala/org/apache/comet/serde/operator/CometDataWritingCommand.scala

@@ -50,6 +50,11 @@ object CometDataWritingCommand extends CometOperatorSerde[DataWritingCommandExec
   override def getSupportLevel(op: DataWritingCommandExec): SupportLevel = {
     op.cmd match {
       case cmd: InsertIntoHadoopFsRelationCommand =>
+        // Skip INSERT OVERWRITE DIRECTORY operations (catalogTable is None for directory writes)
+        if (cmd.catalogTable.isEmpty) {
+          return Unsupported(Some("INSERT OVERWRITE DIRECTORY is not supported"))
+        }
+
         cmd.fileFormat match {
           case _: ParquetFileFormat =>
             if (!cmd.outputPath.toString.startsWith("file:")) {

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

@@ -1107,7 +1107,24 @@ class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper {
 
       // Filter rows that contains 'rose' in 'name' column
       val queryContains = sql(s"select id from $table where contains (name, 'rose')")
-      checkAnswer(queryContains, Row(5) :: Nil)
+      checkSparkAnswerAndOperator(queryContains)
+
+      // Additional test cases for optimized contains implementation
+      // Test with empty pattern (should match all non-null rows)
+      val queryEmptyPattern = sql(s"select id from $table where contains (name, '')")
+      checkSparkAnswerAndOperator(queryEmptyPattern)
+
+      // Test with pattern not found
+      val queryNotFound = sql(s"select id from $table where contains (name, 'xyz')")
+      checkSparkAnswerAndOperator(queryNotFound)
+
+      // Test with pattern at start
+      val queryStart = sql(s"select id from $table where contains (name, 'James')")
+      checkSparkAnswerAndOperator(queryStart)
+
+      // Test with pattern at end
+      val queryEnd = sql(s"select id from $table where contains (name, 'Smith')")
+      checkSparkAnswerAndOperator(queryEnd)
     }
   }
 

spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala

@@ -528,6 +528,30 @@ abstract class CometTestBase
     }
   }
 
+  /**
+   * Override waitForTasksToFinish to ensure SparkContext is active before checking tasks. This
+   * fixes the issue where waitForTasksToFinish returns -1 when SparkContext is not active.
+   */
+  override protected def waitForTasksToFinish(): Unit = {
+    // Ensure SparkContext is active before checking tasks
+    // The parent implementation uses SparkContext.getActive.map(_.activeTasks).getOrElse(-1)
+    // If SparkContext is not active, it returns -1 which causes the assertion to fail.
+    // We ensure we have an active SparkContext before calling the parent method.
+    if (SparkContext.getActive.isEmpty) {
+      // Ensure we have a SparkContext from the spark session
+      if (_spark != null) {
+        // SparkContext from spark session should already be active
+        // but if not, getOrCreate will make it active
+        val _ = _spark.sparkContext
+      } else {
+        // Fallback to sparkContext which will get or create one
+        val _ = sparkContext
+      }
+    }
+    // Now call parent implementation which should find an active SparkContext
+    super.waitForTasksToFinish()
+  }
+
   protected def readResourceParquetFile(name: String): DataFrame = {
     spark.read.parquet(getResourceParquetFilePath(name))
   }