chore: extract comparison into separate tool

dev/benchmarks/tpcbench.py

@@ -21,6 +21,22 @@
 from pyspark.sql import SparkSession
 import time
 
+# rename same columns aliases
+# a, a, b, b -> a, a_1, b, b_1
+#
+# Important for writing data where column name uniqueness is required
+def dedup_columns(df):
+    counts = {}
+    new_cols = []
+    for c in df.columns:
+        if c not in counts:
+            counts[c] = 0
+            new_cols.append(c)
+        else:
+            counts[c] += 1
+            new_cols.append(f"{c}_{counts[c]}")
+    return df.toDF(*new_cols)
+
 def main(benchmark: str, data_path: str, query_path: str, iterations: int, output: str, name: str, query_num: int = None, write_path: str = None):
 
     # Initialize a SparkSession
@@ -91,9 +107,19 @@ def main(benchmark: str, data_path: str, query_path: str, iterations: int, outpu
                         df.explain()
 
                         if write_path is not None:
-                            output_path = f"{write_path}/q{query}"
-                            df.coalesce(1).write.mode("overwrite").parquet(output_path)
-                            print(f"Query {query} results written to {output_path}")
+                            # skip results with empty schema
+                            # coming across for running DDL stmt
+                            if len(df.columns) > 0:
+                                output_path = f"{write_path}/q{query}"
+                                # rename same column names for output
+                                # a, a, b, b => a, a_1, b, b_1
+                                # output doesn't allow non unique column names
+                                deduped = dedup_columns(df)
+                                # sort by all columns to have predictable output dataset for comparison
+                                deduped.orderBy(*deduped.columns).coalesce(1).write.mode("overwrite").parquet(output_path)
+                                print(f"Query {query} results written to {output_path}")
+                            else:
+                                print(f"Skipping write: DataFrame has no schema for {output_path}")
                         else:
                             rows = df.collect()
                             print(f"Query {query} returned {len(rows)} rows")
@@ -132,4 +158,5 @@ def main(benchmark: str, data_path: str, query_path: str, iterations: int, outpu
     parser.add_argument("--write", required=False, help="Path to save query results to, in Parquet format.")
     args = parser.parse_args()
 
-    main(args.benchmark, args.data, args.queries, int(args.iterations), args.output, args.name, args.query, args.write)
+    main(args.benchmark, args.data, args.queries, int(args.iterations), args.output, args.name, args.query, args.write)
+

fuzz-testing/README.md

@@ -103,3 +103,19 @@ $SPARK_HOME/bin/spark-submit \
 ```
 
 Note that the output filename is currently hard-coded as `results-${System.currentTimeMillis()}.md`
+
+### Compare existing datasets
+
+To compare a pair of existing datasets you can use a comparison tool. 
+The example below is for TPC-H queries results generated by pure Spark and Comet
+
+
+```shell
+$SPARK_HOME/bin/spark-submit \    
+    --master $SPARK_MASTER \
+    --class org.apache.comet.fuzz.ComparisonTool     
+    target/comet-fuzz-spark3.5_2.12-0.12.0-SNAPSHOT-jar-with-dependencies.jar \
+    compareParquet --input-spark-folder=/tmp/tpch/spark --input-comet-folder=/tmp/tpch/comet
+```
+
+The tool takes a pair of existing folders of the same layout and compares subfolders treating them as parquet based datasets

fuzz-testing/src/main/scala/org/apache/comet/fuzz/ComparisonTool.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.fuzz
+
+import java.io.File
+
+import org.rogach.scallop.{ScallopConf, ScallopOption, Subcommand}
+
+import org.apache.spark.sql.{functions, SparkSession}
+
+class ComparisonToolConf(arguments: Seq[String]) extends ScallopConf(arguments) {
+  object compareParquet extends Subcommand("compareParquet") {
+    val inputSparkFolder: ScallopOption[String] =
+      opt[String](required = true, descr = "Folder with Spark produced results in Parquet format")
+    val inputCometFolder: ScallopOption[String] =
+      opt[String](required = true, descr = "Folder with Comet produced results in Parquet format")
+  }
+  addSubcommand(compareParquet)
+  verify()
+}
+
+object ComparisonTool {
+
+  lazy val spark: SparkSession = SparkSession
+    .builder()
+    .getOrCreate()
+
+  def main(args: Array[String]): Unit = {
+    val conf = new ComparisonToolConf(args.toIndexedSeq)
+    conf.subcommand match {
+      case Some(conf.compareParquet) =>
+        compareParquetFolders(
+          spark,
+          conf.compareParquet.inputSparkFolder(),
+          conf.compareParquet.inputCometFolder())
+
+      case _ =>
+        // scalastyle:off println
+        println("Invalid subcommand")
+        // scalastyle:on println
+        sys.exit(-1)
+    }
+  }
+
+  private def compareParquetFolders(
+      spark: SparkSession,
+      sparkFolderPath: String,
+      cometFolderPath: String): Unit = {
+
+    val output = QueryRunner.createOutputMdFile()
+
+    try {
+      val sparkFolder = new File(sparkFolderPath)
+      val cometFolder = new File(cometFolderPath)
+
+      if (!sparkFolder.exists() || !sparkFolder.isDirectory) {
+        throw new IllegalArgumentException(
+          s"Spark folder does not exist or is not a directory: $sparkFolderPath")
+      }
+
+      if (!cometFolder.exists() || !cometFolder.isDirectory) {
+        throw new IllegalArgumentException(
+          s"Comet folder does not exist or is not a directory: $cometFolderPath")
+      }
+
+      // Get all subdirectories from the Spark folder
+      val sparkSubfolders = sparkFolder
+        .listFiles()
+        .filter(_.isDirectory)
+        .map(_.getName)
+        .sorted
+
+      output.write("# Comparing Parquet Folders\n\n")
+      output.write(s"Spark folder: $sparkFolderPath\n")
+      output.write(s"Comet folder: $cometFolderPath\n")
+      output.write(s"Found ${sparkSubfolders.length} subfolders to compare\n\n")
+
+      // Compare each subfolder
+      sparkSubfolders.foreach { subfolderName =>
+        val sparkSubfolderPath = new File(sparkFolder, subfolderName)
+        val cometSubfolderPath = new File(cometFolder, subfolderName)
+
+        if (!cometSubfolderPath.exists() || !cometSubfolderPath.isDirectory) {
+          output.write(s"## Subfolder: $subfolderName\n")
+          output.write(
+            s"[WARNING] Comet subfolder not found: ${cometSubfolderPath.getAbsolutePath}\n\n")
+        } else {
+          output.write(s"## Comparing subfolder: $subfolderName\n\n")
+
+          try {
+            // Read Spark parquet files
+            spark.conf.set("spark.comet.enabled", "false")
+            val sparkDf = spark.read.parquet(sparkSubfolderPath.getAbsolutePath)
+            val sparkRows = sparkDf.orderBy(sparkDf.columns.map(functions.col): _*).collect()
+
+            // Read Comet parquet files
+            val cometDf = spark.read.parquet(cometSubfolderPath.getAbsolutePath)
+            val cometRows = cometDf.orderBy(cometDf.columns.map(functions.col): _*).collect()
+
+            // Compare the results
+            if (QueryComparison.assertSameRows(sparkRows, cometRows, output)) {
+              output.write(s"Subfolder $subfolderName: ${sparkRows.length} rows matched\n\n")
+            }
+          } catch {
+            case e: Exception =>
+              output.write(
+                s"[ERROR] Failed to compare subfolder $subfolderName: ${e.getMessage}\n")
+              val sw = new java.io.StringWriter()
+              val p = new java.io.PrintWriter(sw)
+              e.printStackTrace(p)
+              p.close()
+              output.write(s"```\n${sw.toString}\n```\n\n")
+          }
+        }
+
+        output.flush()
+      }
+
+      output.write("\n# Comparison Complete\n")
+      output.write(s"Compared ${sparkSubfolders.length} subfolders\n")
+
+    } finally {
+      output.close()
+    }
+  }
+}