[GLUTEN-7028][CH][Part-15] [MINOR] Fix UTs (#8364)

* [Fix UT] spark.databricks.delta.stats.skipping -> false

* [Fix UT] Bucket table not support

* [Fix UT] 'test cache mergetree data no partition columns' already fixed by (#8346)

* [UT] open ignore test

* [MINOR REFACTOR] Pass by const reference instead of pass by value

* [MINOR REFACTOR] validatedPartitionID

* [Fix Bug] decode part name

* clang 19 fix

backends-clickhouse/src-delta-32/main/scala/org/apache/spark/sql/delta/ClickhouseOptimisticTransaction.scala

@@ -340,20 +340,19 @@ class ClickhouseOptimisticTransaction(
 
     var resultFiles =
       (if (optionalStatsTracker.isDefined) {
-         committer.addedStatuses.map {
-           a =>
-             a.copy(stats =
-               optionalStatsTracker.map(_.recordedStats(a.toPath.getName)).getOrElse(a.stats))
-         }
-       } else {
-         committer.addedStatuses
-       })
+        committer.addedStatuses.map { a =>
+          a.copy(stats = optionalStatsTracker.map(
+            _.recordedStats(a.toPath.getName)).getOrElse(a.stats))
+        }
+      }
+      else {
+        committer.addedStatuses
+      })
         .filter {
-          // In some cases, we can write out an empty `inputData`. Some examples of this (though,
-          // they may be fixed in the future) are the MERGE command when you delete with empty
-          // source, or empty target, or on disjoint tables. This is hard to catch before
-          // the write without collecting the DF ahead of time. Instead,
-          // we can return only the AddFiles that
+          // In some cases, we can write out an empty `inputData`. Some examples of this (though, they
+          // may be fixed in the future) are the MERGE command when you delete with empty source, or
+          // empty target, or on disjoint tables. This is hard to catch before the write without
+          // collecting the DF ahead of time. Instead, we can return only the AddFiles that
           // a) actually add rows, or
           // b) don't have any stats so we don't know the number of rows at all
           case a: AddFile => a.numLogicalRecords.forall(_ > 0)

backends-clickhouse/src-delta-32/main/scala/org/apache/spark/sql/execution/FileDeltaColumnarWrite.scala

@@ -19,7 +19,7 @@ package org.apache.spark.sql.execution
 import org.apache.gluten.backendsapi.clickhouse.RuntimeSettings
 import org.apache.gluten.exception.GlutenNotSupportException
 import org.apache.gluten.vectorized.NativeExpressionEvaluator
-
+import org.apache.hadoop.fs.Path
 import org.apache.spark.internal.Logging
 import org.apache.spark.internal.io.FileCommitProtocol
 import org.apache.spark.sql.catalyst.InternalRow
@@ -37,11 +37,11 @@ case class DeltaFileCommitInfo(committer: FileDelayedCommitProtocol)
   val addedFiles: ArrayBuffer[(Map[String, String], String)] =
     new ArrayBuffer[(Map[String, String], String)]
   override def apply(stat: NativeFileWriteResult): Unit = {
-    if (stat.partition_id == CHColumnarWrite.EMPTY_PARTITION_ID) {
-      addedFiles.append((Map.empty[String, String], stat.filename))
-    } else {
+    if (CHColumnarWrite.validatedPartitionID(stat.partition_id)) {
       val partitionValues = committer.parsePartitions(stat.partition_id)
-      addedFiles.append((partitionValues, stat.relativePath))
+      addedFiles.append((partitionValues, new Path(stat.relativePath).toUri.toString))
+    } else {
+      addedFiles.append((Map.empty[String, String], stat.filename))
     }
   }
 

backends-clickhouse/src-delta-32/main/scala/org/apache/spark/sql/execution/MergeTreeDeltaColumnarWrite.scala

@@ -52,10 +52,10 @@ case class MergeTreeWriteResult(
       path: Path,
       modificationTime: Long,
       hostName: Seq[String]): FileAction = {
-    val (partitionValues, part_path) = if (partition_id == CHColumnarWrite.EMPTY_PARTITION_ID) {
-      (Map.empty[String, String], part_name)
-    } else {
+    val (partitionValues, part_path) = if (CHColumnarWrite.validatedPartitionID(partition_id)) {
       (MergeTreePartitionUtils.parsePartitions(partition_id), s"$partition_id/$part_name")
+    } else {
+      (Map.empty[String, String], part_name)
     }
     val tags = Map[String, String](
       "database" -> database,
@@ -88,7 +88,7 @@ case class MergeTreeWriteResult(
       DeltaStatistics.NULL_COUNT -> ""
     )
     AddFile(
-      part_path,
+      new Path(part_path).toUri.toString,
       partitionValues,
       size_in_bytes,
       modificationTime,
@@ -153,7 +153,7 @@ case class MergeTreeBasicWriteTaskStatsTracker() extends (MergeTreeWriteResult =
   private var numFiles: Int = 0
 
   def apply(stat: MergeTreeWriteResult): Unit = {
-    if (stat.partition_id != CHColumnarWrite.EMPTY_PARTITION_ID) {
+    if (CHColumnarWrite.validatedPartitionID(stat.partition_id)) {
       partitions.append(new GenericInternalRow(Array[Any](stat.partition_id)))
     }
     numFiles += 1

backends-clickhouse/src/main/scala/org/apache/spark/sql/execution/CHColumnarWrite.scala

@@ -158,10 +158,10 @@ case class HadoopMapReduceAdapter(sparkCommitter: HadoopMapReduceCommitProtocol)
 }
 
 case class NativeFileWriteResult(filename: String, partition_id: String, record_count: Long) {
-  lazy val relativePath: String = if (partition_id == CHColumnarWrite.EMPTY_PARTITION_ID) {
-    filename
-  } else {
+  lazy val relativePath: String = if (CHColumnarWrite.validatedPartitionID(partition_id)) {
     s"$partition_id/$filename"
+  } else {
+    filename
   }
 }
 
@@ -212,7 +212,7 @@ case class NativeBasicWriteTaskStatsTracker(
   private var numWrittenRows: Long = 0
   override def apply(stat: NativeFileWriteResult): Unit = {
     val absolutePath = s"$writeDir/${stat.relativePath}"
-    if (stat.partition_id != CHColumnarWrite.EMPTY_PARTITION_ID) {
+    if (CHColumnarWrite.validatedPartitionID(stat.partition_id)) {
       basicWriteJobStatsTracker.newPartition(new GenericInternalRow(Array[Any](stat.partition_id)))
     }
     basicWriteJobStatsTracker.newFile(absolutePath)
@@ -233,7 +233,7 @@ case class FileCommitInfo(description: WriteJobDescription)
 
   def apply(stat: NativeFileWriteResult): Unit = {
     val tmpAbsolutePath = s"${description.path}/${stat.relativePath}"
-    if (stat.partition_id != CHColumnarWrite.EMPTY_PARTITION_ID) {
+    if (CHColumnarWrite.validatedPartitionID(stat.partition_id)) {
       partitions += stat.partition_id
       val customOutputPath =
         description.customPartitionLocations.get(
@@ -325,5 +325,7 @@ object CHColumnarWrite {
     case other => CHDeltaColumnarWrite(jobTrackerID, description, other)
   }
 
-  val EMPTY_PARTITION_ID = "__NO_PARTITION_ID__"
+  private val EMPTY_PARTITION_ID = "__NO_PARTITION_ID__"
+
+  def validatedPartitionID(partitionID: String): Boolean = partitionID != EMPTY_PARTITION_ID
 }

backends-clickhouse/src/test/scala/org/apache/gluten/execution/mergetree/GlutenClickHouseMergeTreeCacheDataSuite.scala

@@ -401,7 +401,7 @@ class GlutenClickHouseMergeTreeCacheDataSuite
     spark.sql("drop table lineitem_mergetree_hdfs purge")
   }
 
-  testSparkVersionLE33("test cache mergetree data no partition columns") {
+  test("test cache mergetree data no partition columns") {
 
     spark.sql(s"""
                  |DROP TABLE IF EXISTS lineitem_mergetree_hdfs;

backends-clickhouse/src/test/scala/org/apache/gluten/execution/mergetree/GlutenClickHouseMergeTreePathBasedWriteSuite.scala

@@ -302,7 +302,7 @@ class GlutenClickHouseMergeTreePathBasedWriteSuite
     }
   }
 
-  testSparkVersionLE33("test mergetree path based table update") {
+  test("test mergetree path based table update") {
     val dataPath = s"$basePath/lineitem_mergetree_update"
     clearDataPath(dataPath)
 
@@ -315,78 +315,87 @@ class GlutenClickHouseMergeTreePathBasedWriteSuite
       .mode(SaveMode.Append)
       .save(dataPath)
 
-    spark.sql(s"""
-                 | update clickhouse.`$dataPath` set l_returnflag = 'Z' where l_orderkey = 12647
-                 |""".stripMargin)
-
-    {
-      val df = spark.read
-        .format("clickhouse")
-        .load(dataPath)
-        .where("l_returnflag = 'Z'")
-      assertResult(1)(df.count())
-      val scanExec = collect(df.queryExecution.executedPlan) {
-        case f: FileSourceScanExecTransformer => f
-      }
-      assertResult(1)(scanExec.size)
+    /**
+     * TODO: new test for (spark.databricks.delta.stats.skipping -> true)
+     *
+     * Since one pipeline write will collect stats, so that pruning will be more accurate in point
+     * query. Let's add a new test when we implement lightweight update and delete.
+     */
+    withSQLConf(("spark.databricks.delta.stats.skipping", "false")) {
+      spark.sql(s"""
+                   | update clickhouse.`$dataPath` set l_returnflag = 'Z' where l_orderkey = 12647
+                   |""".stripMargin)
+
+      {
+        val df = spark.read
+          .format("clickhouse")
+          .load(dataPath)
+          .where("l_returnflag = 'Z'")
+        assertResult(1)(df.count())
+        val scanExec = collect(df.queryExecution.executedPlan) {
+          case f: FileSourceScanExecTransformer => f
+        }
+        assertResult(1)(scanExec.size)
 
-      val mergetreeScan = scanExec.head
-      assert(mergetreeScan.nodeName.startsWith("ScanTransformer mergetree"))
+        val mergetreeScan = scanExec.head
+        assert(mergetreeScan.nodeName.startsWith("ScanTransformer mergetree"))
 
-      val fileIndex = mergetreeScan.relation.location.asInstanceOf[TahoeFileIndex]
-      assert(ClickHouseTableV2.getTable(fileIndex.deltaLog).clickhouseTableConfigs.nonEmpty)
-      assert(ClickHouseTableV2.getTable(fileIndex.deltaLog).bucketOption.isEmpty)
-      assert(
-        ClickHouseTableV2
-          .getTable(fileIndex.deltaLog)
-          .orderByKey === StorageMeta.DEFAULT_ORDER_BY_KEY)
-      assert(ClickHouseTableV2.getTable(fileIndex.deltaLog).primaryKey.isEmpty)
-      assert(ClickHouseTableV2.getTable(fileIndex.deltaLog).partitionColumns.isEmpty)
-      val addFiles = fileIndex.matchingFiles(Nil, Nil).map(f => f.asInstanceOf[AddMergeTreeParts])
-      assertResult(600572)(addFiles.map(_.rows).sum)
-      // 4 parts belong to the first batch
-      // 2 parts belong to the second batch (1 actual updated part, 1 passively updated).
-      assertResult(6)(addFiles.size)
-      val filePaths = addFiles.map(_.path).groupBy(name => name.substring(0, name.lastIndexOf("_")))
-      assertResult(2)(filePaths.size)
-      assertResult(Array(2, 4))(filePaths.values.map(paths => paths.size).toArray.sorted)
-    }
+        val fileIndex = mergetreeScan.relation.location.asInstanceOf[TahoeFileIndex]
+        assert(ClickHouseTableV2.getTable(fileIndex.deltaLog).clickhouseTableConfigs.nonEmpty)
+        assert(ClickHouseTableV2.getTable(fileIndex.deltaLog).bucketOption.isEmpty)
+        assert(
+          ClickHouseTableV2
+            .getTable(fileIndex.deltaLog)
+            .orderByKey === StorageMeta.DEFAULT_ORDER_BY_KEY)
+        assert(ClickHouseTableV2.getTable(fileIndex.deltaLog).primaryKey.isEmpty)
+        assert(ClickHouseTableV2.getTable(fileIndex.deltaLog).partitionColumns.isEmpty)
+        val addFiles = fileIndex.matchingFiles(Nil, Nil).map(f => f.asInstanceOf[AddMergeTreeParts])
+        assertResult(600572)(addFiles.map(_.rows).sum)
+        // 4 parts belong to the first batch
+        // 2 parts belong to the second batch (1 actual updated part, 1 passively updated).
+        assertResult(6)(addFiles.size)
+        val filePaths =
+          addFiles.map(_.path).groupBy(name => name.substring(0, name.lastIndexOf("_")))
+        assertResult(2)(filePaths.size)
+        assertResult(Array(2, 4))(filePaths.values.map(paths => paths.size).toArray.sorted)
+      }
 
-    val clickhouseTable = ClickhouseTable.forPath(spark, dataPath)
-    clickhouseTable.updateExpr("l_orderkey = 10086", Map("l_returnflag" -> "'X'"))
+      val clickhouseTable = ClickhouseTable.forPath(spark, dataPath)
+      clickhouseTable.updateExpr("l_orderkey = 10086", Map("l_returnflag" -> "'X'"))
 
-    {
-      val df = spark.read
-        .format("clickhouse")
-        .load(dataPath)
-        .where("l_returnflag = 'X'")
-      assertResult(1)(df.count())
-      val scanExec = collect(df.queryExecution.executedPlan) {
-        case f: FileSourceScanExecTransformer => f
-      }
-      assertResult(1)(scanExec.size)
+      {
+        val df = spark.read
+          .format("clickhouse")
+          .load(dataPath)
+          .where("l_returnflag = 'X'")
+        assertResult(1)(df.count())
+        val scanExec = collect(df.queryExecution.executedPlan) {
+          case f: FileSourceScanExecTransformer => f
+        }
+        assertResult(1)(scanExec.size)
 
-      val mergetreeScan = scanExec.head
-      assert(mergetreeScan.nodeName.startsWith("ScanTransformer mergetree"))
+        val mergetreeScan = scanExec.head
+        assert(mergetreeScan.nodeName.startsWith("ScanTransformer mergetree"))
 
-      val fileIndex = mergetreeScan.relation.location.asInstanceOf[TahoeFileIndex]
-      val addFiles = fileIndex.matchingFiles(Nil, Nil).map(f => f.asInstanceOf[AddMergeTreeParts])
-      assertResult(600572)(addFiles.map(_.rows).sum)
+        val fileIndex = mergetreeScan.relation.location.asInstanceOf[TahoeFileIndex]
+        val addFiles = fileIndex.matchingFiles(Nil, Nil).map(f => f.asInstanceOf[AddMergeTreeParts])
+        assertResult(600572)(addFiles.map(_.rows).sum)
 
-      // 4 parts belong to the first batch
-      // 2 parts belong to the second batch (1 actual updated part, 1 passively updated).
-      assertResult(6)(addFiles.size)
-      val filePaths = addFiles.map(_.path).groupBy(name => name.substring(0, name.lastIndexOf("_")))
-      assertResult(2)(filePaths.size)
+        // 4 parts belong to the first batch
+        // 2 parts belong to the second batch (1 actual updated part, 1 passively updated).
+        assertResult(6)(addFiles.size)
+        val filePaths =
+          addFiles.map(_.path).groupBy(name => name.substring(0, name.lastIndexOf("_")))
+        assertResult(2)(filePaths.size)
+      }
     }
-
     val df = spark.read
       .format("clickhouse")
       .load(dataPath)
     assertResult(600572)(df.count())
   }
 
-  testSparkVersionLE33("test mergetree path based table delete") {
+  test("test mergetree path based table delete") {
     val dataPath = s"$basePath/lineitem_mergetree_delete"
     clearDataPath(dataPath)
 
@@ -399,32 +408,40 @@ class GlutenClickHouseMergeTreePathBasedWriteSuite
       .mode(SaveMode.Append)
       .save(dataPath)
 
-    spark.sql(s"""
-                 | delete from clickhouse.`$dataPath` where l_orderkey = 12647
-                 |""".stripMargin)
-    val df = spark.read
-      .format("clickhouse")
-      .load(dataPath)
-    assertResult(600571)(df.count())
-    val scanExec = collect(df.queryExecution.executedPlan) {
-      case f: FileSourceScanExecTransformer => f
+    /**
+     * TODO: new test for (spark.databricks.delta.stats.skipping -> true)
+     *
+     * Since one pipeline write will collect stats, so that pruning will be more accurate in point
+     * query. Let's add a new test when we implement lightweight update and delete.
+     */
+    withSQLConf(("spark.databricks.delta.stats.skipping", "false")) {
+      spark.sql(s"""
+                   | delete from clickhouse.`$dataPath` where l_orderkey = 12647
+                   |""".stripMargin)
+      val df = spark.read
+        .format("clickhouse")
+        .load(dataPath)
+      assertResult(600571)(df.count())
+      val scanExec = collect(df.queryExecution.executedPlan) {
+        case f: FileSourceScanExecTransformer => f
+      }
+      val mergetreeScan = scanExec.head
+      val fileIndex = mergetreeScan.relation.location.asInstanceOf[TahoeFileIndex]
+      val addFiles = fileIndex.matchingFiles(Nil, Nil).map(f => f.asInstanceOf[AddMergeTreeParts])
+      // 4 parts belong to the first batch
+      // 2 parts belong to the second batch (1 actual updated part, 1 passively updated).
+      assertResult(6)(addFiles.size)
+      val filePaths = addFiles.map(_.path).groupBy(name => name.substring(0, name.lastIndexOf("_")))
+      assertResult(2)(filePaths.size)
+      assertResult(Array(2, 4))(filePaths.values.map(paths => paths.size).toArray.sorted)
+
+      val clickhouseTable = ClickhouseTable.forPath(spark, dataPath)
+      clickhouseTable.delete("mod(l_orderkey, 3) = 2")
+      val df1 = spark.read
+        .format("clickhouse")
+        .load(dataPath)
+      assertResult(400089)(df1.count())
     }
-    val mergetreeScan = scanExec.head
-    val fileIndex = mergetreeScan.relation.location.asInstanceOf[TahoeFileIndex]
-    val addFiles = fileIndex.matchingFiles(Nil, Nil).map(f => f.asInstanceOf[AddMergeTreeParts])
-    // 4 parts belong to the first batch
-    // 2 parts belong to the second batch (1 actual updated part, 1 passively updated).
-    assertResult(6)(addFiles.size)
-    val filePaths = addFiles.map(_.path).groupBy(name => name.substring(0, name.lastIndexOf("_")))
-    assertResult(2)(filePaths.size)
-    assertResult(Array(2, 4))(filePaths.values.map(paths => paths.size).toArray.sorted)
-
-    val clickhouseTable = ClickhouseTable.forPath(spark, dataPath)
-    clickhouseTable.delete("mod(l_orderkey, 3) = 2")
-    val df1 = spark.read
-      .format("clickhouse")
-      .load(dataPath)
-    assertResult(400089)(df1.count())
   }
 
   test("test mergetree path based table upsert") {

backends-clickhouse/src/test/scala/org/apache/gluten/execution/mergetree/GlutenClickHouseMergeTreeWriteOnHDFSSuite.scala

@@ -436,7 +436,7 @@ class GlutenClickHouseMergeTreeWriteOnHDFSSuite
     spark.sql("drop table lineitem_mergetree_bucket_hdfs")
   }
 
-  testSparkVersionLE33("test mergetree write with the path based") {
+  testSparkVersionLE33("test mergetree write with the path based bucket table") {
     val dataPath = s"$HDFS_URL/test/lineitem_mergetree_bucket_hdfs"
 
     val sourceDF = spark.sql(s"""

backends-clickhouse/src/test/scala/org/apache/gluten/execution/mergetree/GlutenClickHouseMergeTreeWriteOnHDFSWithRocksDBMetaSuite.scala

@@ -435,7 +435,7 @@ class GlutenClickHouseMergeTreeWriteOnHDFSWithRocksDBMetaSuite
     spark.sql("drop table lineitem_mergetree_bucket_hdfs purge")
   }
 
-  testSparkVersionLE33("test mergetree write with the path based") {
+  testSparkVersionLE33("test mergetree write with the path based bucket table") {
     val dataPath = s"$HDFS_URL/test/lineitem_mergetree_bucket_hdfs"
 
     val sourceDF = spark.sql(s"""

backends-clickhouse/src/test/scala/org/apache/gluten/execution/mergetree/GlutenClickHouseMergeTreeWriteOnS3Suite.scala

@@ -496,7 +496,7 @@ class GlutenClickHouseMergeTreeWriteOnS3Suite
     spark.sql("drop table lineitem_mergetree_bucket_s3")
   }
 
-  testSparkVersionLE33("test mergetree write with the path based") {
+  testSparkVersionLE33("test mergetree write with the path based bucket table") {
     val dataPath = s"s3a://$BUCKET_NAME/lineitem_mergetree_bucket_s3"
 
     val sourceDF = spark.sql(s"""

backends-clickhouse/src/test/scala/org/apache/gluten/execution/mergetree/GlutenClickHouseMergeTreeWriteSuite.scala

@@ -1826,7 +1826,7 @@ class GlutenClickHouseMergeTreeWriteSuite
     runTPCHQueryBySQL(6, q6("lineitem_mergetree_case_sensitive")) { _ => }
   }
 
-  testSparkVersionLE33("test mergetree with partition with whitespace") {
+  test("test mergetree with partition with whitespace") {
     spark.sql(s"""
                  |DROP TABLE IF EXISTS lineitem_mergetree_partition_with_whitespace;
                  |""".stripMargin)