feat: Add manual test to calculate spark builtin functions coverage

doc/spark_builtin_expr_coverage_agg.txt

@@ -0,0 +1,9 @@
++-------+--------------------------------------------------------+---+
+|result |details                                                 |cnt|
++-------+--------------------------------------------------------+---+
+|FAILED |Unsupported                                             |282|
+|FAILED |Failed on native side                                   |16 |
+|FAILED |Failed on something else. Check query manually          |4  |
+|PASSED |OK                                                      |101|
+|SKIPPED|No examples found in spark.sessionState.functionRegistry|12 |
++-------+--------------------------------------------------------+---+

pom.xml

@@ -889,6 +889,7 @@ under the License.
             <exclude>tpcds-kit/**</exclude>
             <exclude>tpcds-sf-1/**</exclude>
             <exclude>tpch/**</exclude>
+            <exclude>doc/*.txt</exclude>
           </excludes>
         </configuration>
       </plugin>

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

@@ -0,0 +1,143 @@
+/*
+ * 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.comet
+
+import java.nio.charset.StandardCharsets
+import java.nio.file.{Files, Paths}
+
+import scala.collection.mutable
+
+import org.scalatest.Ignore
+import org.scalatest.exceptions.TestFailedException
+
+import org.apache.spark.sql.CometTestBase
+import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
+
+/**
+ * Manual test to calculate Spark builtin expressions coverage support by the Comet
+ *
+ * The test will update files doc/spark_builtin_expr_coverage.txt,
+ * doc/spark_builtin_expr_coverage_agg.txt
+ */
+
+@Ignore
+class CometExpressionCoverageSuite extends CometTestBase with AdaptiveSparkPlanHelper {
+
+  import testImplicits._
+
+  private val rawCoverageFilePath = "doc/spark_builtin_expr_coverage.txt"
+  private val aggCoverageFilePath = "doc/spark_builtin_expr_coverage_agg.txt"
+
+  test("Test Spark builtin expressions coverage") {
+    val queryPattern = """(?i)SELECT (.+?);""".r
+    val valuesPattern = """(?i)FROM VALUES(.+?);""".r
+    val selectPattern = """(i?)SELECT(.+?)FROM""".r
+    val builtinExamplesMap = spark.sessionState.functionRegistry
+      .listFunction()
+      .map(spark.sessionState.catalog.lookupFunctionInfo(_))
+      .filter(_.getSource.toLowerCase == "built-in")
+      // exclude spark streaming functions, Comet has no plans to support streaming in near future
+      .filter(f =>
+        !List("window", "session_window", "window_time").contains(f.getName.toLowerCase))
+      .map(f => {
+        val selectRows = queryPattern.findAllMatchIn(f.getExamples).map(_.group(0)).toList
+        (f.getName, selectRows.filter(_.nonEmpty))
+      })
+      .toMap
+
+    // key - function name
+    // value - list of result shows if function supported by Comet
+    val resultsMap = new mutable.HashMap[String, CoverageResult]()
+
+    builtinExamplesMap.foreach {
+      case (funcName, q :: _) =>
+        val queryResult =
+          try {
+            // Example with predefined values
+            // e.g. SELECT bit_xor(col) FROM VALUES (3), (5) AS tab(col)
+            // better option is probably to parse the query and iterate through expressions
+            // but this is adhoc coverage test
+            if (q.toLowerCase.contains(" from values")) {
+              val select = selectPattern.findFirstMatchIn(q).map(_.group(0))
+              val values = valuesPattern.findFirstMatchIn(q).map(_.group(0))
+              (select, values) match {
+                case (Some(s), Some(v)) =>
+                  testSingleLineQuery(s"select * $v", s"$s tbl")
+
+                case _ =>
+                  resultsMap.put(
+                    funcName,
+                    CoverageResult("FAILED", Seq((q, "Cannot parse properly"))))
+              }
+            } else {
+              // Plain example like SELECT cos(0);
+              testSingleLineQuery(
+                "select 'dummy' x",
+                s"${q.dropRight(1)}, x from tbl",
+                excludedOptimizerRules =
+                  Some("org.apache.spark.sql.catalyst.optimizer.ConstantFolding"))
+            }
+            CoverageResult(CoverageResultStatus.Passed.toString, Seq((q, "OK")))
+          } catch {
+            case e: TestFailedException
+                if e.message.getOrElse("").contains("Expected only Comet native operators") =>
+              CoverageResult(CoverageResultStatus.Failed.toString, Seq((q, "Unsupported")))
+            case e if e.getMessage.contains("CometNativeException") =>
+              CoverageResult(
+                CoverageResultStatus.Failed.toString,
+                Seq((q, "Failed on native side")))
+            case _ =>
+              CoverageResult(
+                CoverageResultStatus.Failed.toString,
+                Seq((q, "Failed on something else. Check query manually")))
+          }
+        resultsMap.put(funcName, queryResult)
+
+      case (funcName, List()) =>
+        resultsMap.put(
+          funcName,
+          CoverageResult(
+            CoverageResultStatus.Skipped.toString,
+            Seq(("", "No examples found in spark.sessionState.functionRegistry"))))
+    }
+
+    // TODO: convert results into HTML
+    resultsMap.toSeq.toDF("name", "details").createOrReplaceTempView("t")
+    val str_agg = showString(
+      spark.sql(
+        "select result, d._2 as details, count(1) cnt from (select name, t.details.result, explode_outer(t.details.details) as d from t) group by 1, 2 order by 1"),
+      1000,
+      0)
+    Files.write(Paths.get(aggCoverageFilePath), str_agg.getBytes(StandardCharsets.UTF_8))
+
+    val str = showString(spark.sql("select * from t order by 1"), 1000, 0)
+    Files.write(Paths.get(rawCoverageFilePath), str.getBytes(StandardCharsets.UTF_8))
+  }
+}
+
+case class CoverageResult(result: String, details: Seq[(String, String)])
+
+object CoverageResultStatus extends Enumeration {
+  type CoverageResultStatus = Value
+
+  val Failed: Value = Value("FAILED")
+  val Passed: Value = Value("PASSED")
+  val Skipped: Value = Value("SKIPPED")
+}

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

@@ -19,15 +19,13 @@
 
 package org.apache.comet
 
-import java.util
-
 import org.apache.hadoop.fs.Path
 import org.apache.spark.sql.{CometTestBase, DataFrame, Row}
 import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
 import org.apache.spark.sql.functions.expr
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.internal.SQLConf.SESSION_LOCAL_TIMEZONE
-import org.apache.spark.sql.types.{Decimal, DecimalType, StructType}
+import org.apache.spark.sql.types.{Decimal, DecimalType}
 
 import org.apache.comet.CometSparkSessionExtensions.{isSpark32, isSpark33Plus, isSpark34Plus}
 
@@ -1291,30 +1289,6 @@ class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper {
     }
   }
 
-  // tests one liner query without necessity to create external table
-  def testSingleLineQuery(
-      prepareQuery: String,
-      testQuery: String,
-      testName: String = "test",
-      tableName: String = "tbl"): Unit = {
-
-    withTempDir { dir =>
-      val path = new Path(dir.toURI.toString, testName).toUri.toString
-      var data: java.util.List[Row] = new util.ArrayList()
-      var schema: StructType = null
-
-      withSQLConf(CometConf.COMET_ENABLED.key -> "false") {
-        val df = spark.sql(prepareQuery)
-        data = df.collectAsList()
-        schema = df.schema
-      }
-
-      spark.createDataFrame(data, schema).repartition(1).write.parquet(path)
-      readParquetFile(path, Some(schema)) { df => df.createOrReplaceTempView(tableName) }
-      checkSparkAnswerAndOperator(testQuery)
-    }
-  }
-
   test("Decimal random number tests") {
     val rand = scala.util.Random
     def makeNum(p: Int, s: Int): String = {

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

@@ -718,4 +718,47 @@ abstract class CometTestBase
       Seq.empty
     }
   }
+
+  // tests one liner query without necessity to create external table
+  def testSingleLineQuery(
+      prepareQuery: String,
+      testQuery: String,
+      testName: String = "test",
+      tableName: String = "tbl",
+      excludedOptimizerRules: Option[String] = None): Unit = {
+
+    withTempDir { dir =>
+      val path = new Path(dir.toURI.toString, testName).toUri.toString
+      var data: java.util.List[Row] = new java.util.ArrayList()
+      var schema: StructType = null
+
+      withSQLConf(CometConf.COMET_ENABLED.key -> "false") {
+        val df = spark.sql(prepareQuery)
+        data = df.collectAsList()
+        schema = df.schema
+      }
+
+      spark.createDataFrame(data, schema).repartition(1).write.parquet(path)
+      readParquetFile(path, Some(schema)) { df => df.createOrReplaceTempView(tableName) }
+
+      // disable constant folding. This optimization rule precompute and select value as literal
+      // which subsequently leads to false positives
+      //
+      // ConstantFolding is a operator optimization rule in Catalyst that replaces expressions
+      // that can be statically evaluated with their equivalent literal values.
+      withSQLConf(
+        "spark.sql.optimizer.excludedRules" -> excludedOptimizerRules.getOrElse(""),
+        "spark.sql.adaptive.optimizer.excludedRules" -> excludedOptimizerRules.getOrElse("")) {
+        checkSparkAnswerAndOperator(sql(testQuery))
+      }
+    }
+  }
+
+  def showString[T](
+      df: Dataset[T],
+      _numRows: Int,
+      truncate: Int = 20,
+      vertical: Boolean = false): String = {
+    df.showString(_numRows, truncate, vertical)
+  }
 }