feat: add support for array_contains expression (apache#1163)

* feat: add support for array_contains expression

* test: add unit test for array_contains function

* Removes unnecessary case expression for handling null values

* chore: Move more expressions from core crate to spark-expr crate (apache#1152)

* move aggregate expressions to spark-expr crate

* move more expressions

* move benchmark

* normalize_nan

* bitwise not

* comet scalar funcs

* update bench imports

* remove dead code (apache#1155)

* fix: Spark 4.0-preview1 SPARK-47120 (apache#1156)

## Which issue does this PR close?

Part of apache#372 and apache#551

## Rationale for this change

To be ready for Spark 4.0

## What changes are included in this PR?

This PR fixes the new test SPARK-47120 added in Spark 4.0

## How are these changes tested?

tests enabled

* chore: Move string kernels and expressions to spark-expr crate (apache#1164)

* Move string kernels and expressions to spark-expr crate

* remove unused hash kernel

* remove unused dependencies

* chore: Move remaining expressions to spark-expr crate + some minor refactoring (apache#1165)

* move CheckOverflow to spark-expr crate

* move NegativeExpr to spark-expr crate

* move UnboundColumn to spark-expr crate

* move ExpandExec from execution::datafusion::operators to execution::operators

* refactoring to remove datafusion subpackage

* update imports in benches

* fix

* fix

* chore: Add ignored tests for reading complex types from Parquet (apache#1167)

* Add ignored tests for reading structs from Parquet

* add basic map test

* add tests for Map and Array

* feat: Add Spark-compatible implementation of SchemaAdapterFactory (apache#1169)

* Add Spark-compatible SchemaAdapterFactory implementation

* remove prototype code

* fix

* refactor

* implement more cast logic

* implement more cast logic

* add basic test

* improve test

* cleanup

* fmt

* add support for casting unsigned int to signed int

* clippy

* address feedback

* fix test

* fix: Document enabling comet explain plan usage in Spark (4.0) (apache#1176)

* test: enabling Spark tests with offHeap requirement (apache#1177)

## Which issue does this PR close?

## Rationale for this change

After apache#1062 We have not running Spark tests for native execution

## What changes are included in this PR?

Removed the off heap requirement for testing

## How are these changes tested?

Bringing back Spark tests for native execution

* feat: Improve shuffle metrics (second attempt) (apache#1175)

* improve shuffle metrics

* docs

* more metrics

* refactor

* address feedback

* fix: stddev_pop should not directly return 0.0 when count is 1.0 (apache#1184)

* add test

* fix

* fix

* fix

* feat: Make native shuffle compression configurable and respect `spark.shuffle.compress` (apache#1185)

* Make shuffle compression codec and level configurable

* remove lz4 references

* docs

* update comment

* clippy

* fix benches

* clippy

* clippy

* disable test for miri

* remove lz4 reference from proto

* minor: move shuffle classes from common to spark (apache#1193)

* minor: refactor decodeBatches to make private in broadcast exchange (apache#1195)

* minor: refactor prepare_output so that it does not require an ExecutionContext (apache#1194)

* fix: fix missing explanation for then branch in case when (apache#1200)

* minor: remove unused source files (apache#1202)

* chore: Upgrade to DataFusion 44.0.0-rc2 (apache#1154)

* move aggregate expressions to spark-expr crate

* move more expressions

* move benchmark

* normalize_nan

* bitwise not

* comet scalar funcs

* update bench imports

* save

* save

* save

* remove unused imports

* clippy

* implement more hashers

* implement Hash and PartialEq

* implement Hash and PartialEq

* implement Hash and PartialEq

* benches

* fix ScalarUDFImpl.return_type failure

* exclude test from miri

* ignore correct test

* ignore another test

* remove miri checks

* use return_type_from_exprs

* Revert "use return_type_from_exprs"

This reverts commit febc1f1.

* use DF main branch

* hacky workaround for regression in ScalarUDFImpl.return_type

* fix repo url

* pin to revision

* bump to latest rev

* bump to latest DF rev

* bump DF to rev 9f530dd

* add Cargo.lock

* bump DF version

* no default features

* Revert "remove miri checks"

This reverts commit 4638fe3.

* Update pin to DataFusion e99e02b9b9093ceb0c13a2dd32a2a89beba47930

* update pin

* Update Cargo.toml

Bump to 44.0.0-rc2

* update cargo lock

* revert miri change

---------

Co-authored-by: Andrew Lamb <[email protected]>

* update UT

Signed-off-by: Dharan Aditya <[email protected]>

* fix typo in UT

Signed-off-by: Dharan Aditya <[email protected]>

---------

Signed-off-by: Dharan Aditya <[email protected]>
Co-authored-by: Andy Grove <[email protected]>
Co-authored-by: KAZUYUKI TANIMURA <[email protected]>
Co-authored-by: Parth Chandra <[email protected]>
Co-authored-by: Liang-Chi Hsieh <[email protected]>
Co-authored-by: Raz Luvaton <[email protected]>
Co-authored-by: Andrew Lamb <[email protected]>

Author: 7 people

native/core/src/execution/planner.rs

@@ -98,6 +98,7 @@ use datafusion_expr::{
     AggregateUDF, ScalarUDF, WindowFrame, WindowFrameBound, WindowFrameUnits,
     WindowFunctionDefinition,
 };
+use datafusion_functions_nested::array_has::ArrayHas;
 use datafusion_physical_expr::expressions::{Literal, StatsType};
 use datafusion_physical_expr::window::WindowExpr;
 use datafusion_physical_expr::LexOrdering;
@@ -719,6 +720,20 @@ impl PhysicalPlanner {
                     expr.legacy_negative_index,
                 )))
             }
+            ExprStruct::ArrayContains(expr) => {
+                let src_array_expr =
+                    self.create_expr(expr.left.as_ref().unwrap(), Arc::clone(&input_schema))?;
+                let key_expr =
+                    self.create_expr(expr.right.as_ref().unwrap(), Arc::clone(&input_schema))?;
+                let args = vec![Arc::clone(&src_array_expr), key_expr];
+                let array_has_expr = Arc::new(ScalarFunctionExpr::new(
+                    "array_has",
+                    Arc::new(ScalarUDF::new_from_impl(ArrayHas::new())),
+                    args,
+                    DataType::Boolean,
+                ));
+                Ok(array_has_expr)
+            }
             expr => Err(ExecutionError::GeneralError(format!(
                 "Not implemented: {:?}",
                 expr

native/proto/src/proto/expr.proto

@@ -84,6 +84,7 @@ message Expr {
     GetArrayStructFields get_array_struct_fields = 57;
     BinaryExpr array_append = 58;
     ArrayInsert array_insert = 59;
+    BinaryExpr array_contains = 60;
   }
 }
 

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

@@ -2266,6 +2266,12 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim
             withInfo(expr, "unsupported arguments for GetArrayStructFields", child)
             None
           }
+        case expr if expr.prettyName == "array_contains" =>
+          createBinaryExpr(
+            expr.children(0),
+            expr.children(1),
+            inputs,
+            (builder, binaryExpr) => builder.setArrayContains(binaryExpr))
         case _ if expr.prettyName == "array_append" =>
           createBinaryExpr(
             expr.children(0),

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

@@ -2517,4 +2517,16 @@ class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper {
       checkSparkAnswer(df.select("arrUnsupportedArgs"))
     }
   }
+
+  test("array_contains") {
+    withTempDir { dir =>
+      val path = new Path(dir.toURI.toString, "test.parquet")
+      makeParquetFileAllTypes(path, dictionaryEnabled = false, n = 10000)
+      spark.read.parquet(path.toString).createOrReplaceTempView("t1");
+      checkSparkAnswerAndOperator(
+        spark.sql("SELECT array_contains(array(_2, _3, _4), _2) FROM t1"))
+      checkSparkAnswerAndOperator(
+        spark.sql("SELECT array_contains((CASE WHEN _2 =_3 THEN array(_4) END), _4) FROM t1"));
+    }
+  }
 }