diff --git a/hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/HoodieSparkUtils.scala b/hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/HoodieSparkUtils.scala index 54bc06bd76201..7a8f8a1580d97 100644 --- a/hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/HoodieSparkUtils.scala +++ b/hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/HoodieSparkUtils.scala @@ -53,13 +53,15 @@ object HoodieSparkUtils extends SparkAdapterSupport { def isSpark3_1: Boolean = SPARK_VERSION.startsWith("3.1") + def gteqSpark3_1: Boolean = SPARK_VERSION > "3.1" + + def gteqSpark3_1_3: Boolean = SPARK_VERSION >= "3.1.3" + def isSpark3_2: Boolean = SPARK_VERSION.startsWith("3.2") def gteqSpark3_2: Boolean = SPARK_VERSION > "3.2" - def gteqSpark3_1: Boolean = SPARK_VERSION > "3.1" - - def gteqSpark3_1_3: Boolean = SPARK_VERSION >= "3.1.3" + def gteqSpark3_2_1: Boolean = SPARK_VERSION >= "3.2.1" def getMetaSchema: StructType = { StructType(HoodieRecord.HOODIE_META_COLUMNS.asScala.map(col => { diff --git a/hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/adapter/Spark3_1Adapter.scala b/hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/adapter/Spark3_1Adapter.scala index cd5cd9c82fbec..22431cb2574a3 100644 --- a/hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/adapter/Spark3_1Adapter.scala +++ b/hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/adapter/Spark3_1Adapter.scala @@ -23,7 +23,7 @@ import org.apache.spark.SPARK_VERSION import org.apache.spark.sql.avro.{HoodieAvroDeserializer, HoodieAvroSerializer, HoodieSpark3_1AvroDeserializer, HoodieSpark3_1AvroSerializer} import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules.Rule -import org.apache.spark.sql.execution.datasources.parquet.{ParquetFileFormat, Spark312HoodieParquetFileFormat} +import org.apache.spark.sql.execution.datasources.parquet.{ParquetFileFormat, Spark31HoodieParquetFileFormat} import org.apache.spark.sql.hudi.SparkAdapter import org.apache.spark.sql.types.DataType import org.apache.spark.sql.{HoodieCatalystExpressionUtils, HoodieSpark3_1CatalystExpressionUtils, SparkSession} @@ -55,6 +55,6 @@ class Spark3_1Adapter extends BaseSpark3Adapter { } override def createHoodieParquetFileFormat(appendPartitionValues: Boolean): Option[ParquetFileFormat] = { - Some(new Spark312HoodieParquetFileFormat(appendPartitionValues)) + Some(new Spark31HoodieParquetFileFormat(appendPartitionValues)) } } diff --git a/hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark312HoodieParquetFileFormat.scala b/hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark31HoodieParquetFileFormat.scala similarity index 95% rename from hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark312HoodieParquetFileFormat.scala rename to hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark31HoodieParquetFileFormat.scala index 769373866ff34..e99850bef06b8 100644 --- a/hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark312HoodieParquetFileFormat.scala +++ b/hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark31HoodieParquetFileFormat.scala @@ -25,7 +25,7 @@ import org.apache.hudi.HoodieSparkUtils import org.apache.hudi.client.utils.SparkInternalSchemaConverter import org.apache.hudi.common.fs.FSUtils import org.apache.hudi.common.util.StringUtils.isNullOrEmpty -import org.apache.hudi.common.util.{InternalSchemaCache, StringUtils} +import org.apache.hudi.common.util.{InternalSchemaCache, ReflectionUtils, StringUtils} import org.apache.hudi.common.util.collection.Pair import org.apache.hudi.internal.schema.InternalSchema import org.apache.hudi.internal.schema.action.InternalSchemaMerger @@ -41,7 +41,7 @@ import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection import org.apache.spark.sql.catalyst.expressions.{Cast, JoinedRow} import org.apache.spark.sql.catalyst.util.DateTimeUtils -import org.apache.spark.sql.execution.datasources.parquet.Spark312HoodieParquetFileFormat.{createParquetFilters, pruneInternalSchema, rebuildFilterFromParquet} +import org.apache.spark.sql.execution.datasources.parquet.Spark31HoodieParquetFileFormat.{createParquetFilters, pruneInternalSchema, rebuildFilterFromParquet} import org.apache.spark.sql.execution.datasources.{DataSourceUtils, PartitionedFile, RecordReaderIterator} import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.sources._ @@ -61,7 +61,7 @@ import java.net.URI *
  • Schema on-read
    • * */ -class Spark312HoodieParquetFileFormat(private val shouldAppendPartitionValues: Boolean) extends ParquetFileFormat { +class Spark31HoodieParquetFileFormat(private val shouldAppendPartitionValues: Boolean) extends ParquetFileFormat { override def buildReaderWithPartitionValues(sparkSession: SparkSession, dataSchema: StructType, @@ -154,8 +154,8 @@ class Spark312HoodieParquetFileFormat(private val shouldAppendPartitionValues: B val shouldUseInternalSchema = !isNullOrEmpty(internalSchemaStr) && querySchemaOption.isPresent val tablePath = sharedConf.get(SparkInternalSchemaConverter.HOODIE_TABLE_PATH) - val commitInstantTime = FSUtils.getCommitTime(filePath.getName).toLong; val fileSchema = if (shouldUseInternalSchema) { + val commitInstantTime = FSUtils.getCommitTime(filePath.getName).toLong; val validCommits = sharedConf.get(SparkInternalSchemaConverter.HOODIE_VALID_COMMITS_LIST) InternalSchemaCache.getInternalSchemaByVersionId(commitInstantTime, tablePath, sharedConf, if (validCommits == null) "" else validCommits) } else { @@ -223,13 +223,17 @@ class Spark312HoodieParquetFileFormat(private val shouldAppendPartitionValues: B // Clone new conf val hadoopAttemptConf = new Configuration(broadcastedHadoopConf.value.value) - var typeChangeInfos: java.util.Map[Integer, Pair[DataType, DataType]] = new java.util.HashMap() - if (shouldUseInternalSchema) { + var typeChangeInfos: java.util.Map[Integer, Pair[DataType, DataType]] = if (shouldUseInternalSchema) { val mergedInternalSchema = new InternalSchemaMerger(fileSchema, querySchemaOption.get(), true, true).mergeSchema() val mergedSchema = SparkInternalSchemaConverter.constructSparkSchemaFromInternalSchema(mergedInternalSchema) - typeChangeInfos = SparkInternalSchemaConverter.collectTypeChangedCols(querySchemaOption.get(), mergedInternalSchema) + hadoopAttemptConf.set(ParquetReadSupport.SPARK_ROW_REQUESTED_SCHEMA, mergedSchema.json) + + SparkInternalSchemaConverter.collectTypeChangedCols(querySchemaOption.get(), mergedInternalSchema) + } else { + new java.util.HashMap() } + val hadoopAttemptContext = new TaskAttemptContextImpl(hadoopAttemptConf, attemptId) @@ -329,9 +333,7 @@ class Spark312HoodieParquetFileFormat(private val shouldAppendPartitionValues: B } } -object Spark312HoodieParquetFileFormat { - - val PARQUET_FILTERS_CLASS_NAME = "org.apache.spark.sql.execution.datasources.parquet.ParquetFilters" +object Spark31HoodieParquetFileFormat { def pruneInternalSchema(internalSchemaStr: String, requiredSchema: StructType): String = { val querySchemaOption = SerDeHelper.fromJson(internalSchemaStr) @@ -343,10 +345,11 @@ object Spark312HoodieParquetFileFormat { } } - private def createParquetFilters(arg: Any*): ParquetFilters = { - val clazz = Class.forName(PARQUET_FILTERS_CLASS_NAME, true, Thread.currentThread().getContextClassLoader) - val ctor = clazz.getConstructors.head - ctor.newInstance(arg.map(_.asInstanceOf[AnyRef]): _*).asInstanceOf[ParquetFilters] + private def createParquetFilters(args: Any*): ParquetFilters = { + // ParquetFilters bears a single ctor (in Spark 3.1) + val ctor = classOf[ParquetFilters].getConstructors.head + ctor.newInstance(args.map(_.asInstanceOf[AnyRef]): _*) + .asInstanceOf[ParquetFilters] } private def rebuildFilterFromParquet(oldFilter: Filter, fileSchema: InternalSchema, querySchema: InternalSchema): Filter = { diff --git a/hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark32DataSourceUtils.scala b/hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark32DataSourceUtils.scala new file mode 100644 index 0000000000000..6d1c76380f216 --- /dev/null +++ b/hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark32DataSourceUtils.scala @@ -0,0 +1,77 @@ +/* + * 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.spark.sql.execution.datasources.parquet + +import org.apache.spark.sql.SPARK_VERSION_METADATA_KEY +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.internal.SQLConf.LegacyBehaviorPolicy +import org.apache.spark.util.Utils + +object Spark32DataSourceUtils { + + /** + * NOTE: This method was copied from Spark 3.2.0, and is required to maintain runtime + * compatibility against Spark 3.2.0 + */ + // scalastyle:off + def int96RebaseMode(lookupFileMeta: String => String, + modeByConfig: String): LegacyBehaviorPolicy.Value = { + if (Utils.isTesting && SQLConf.get.getConfString("spark.test.forceNoRebase", "") == "true") { + return LegacyBehaviorPolicy.CORRECTED + } + // If there is no version, we return the mode specified by the config. + Option(lookupFileMeta(SPARK_VERSION_METADATA_KEY)).map { version => + // Files written by Spark 3.0 and earlier follow the legacy hybrid calendar and we need to + // rebase the INT96 timestamp values. + // Files written by Spark 3.1 and latter may also need the rebase if they were written with + // the "LEGACY" rebase mode. + if (version < "3.1.0" || lookupFileMeta("org.apache.spark.legacyINT96") != null) { + LegacyBehaviorPolicy.LEGACY + } else { + LegacyBehaviorPolicy.CORRECTED + } + }.getOrElse(LegacyBehaviorPolicy.withName(modeByConfig)) + } + // scalastyle:on + + /** + * NOTE: This method was copied from Spark 3.2.0, and is required to maintain runtime + * compatibility against Spark 3.2.0 + */ + // scalastyle:off + def datetimeRebaseMode(lookupFileMeta: String => String, + modeByConfig: String): LegacyBehaviorPolicy.Value = { + if (Utils.isTesting && SQLConf.get.getConfString("spark.test.forceNoRebase", "") == "true") { + return LegacyBehaviorPolicy.CORRECTED + } + // If there is no version, we return the mode specified by the config. + Option(lookupFileMeta(SPARK_VERSION_METADATA_KEY)).map { version => + // Files written by Spark 2.4 and earlier follow the legacy hybrid calendar and we need to + // rebase the datetime values. + // Files written by Spark 3.0 and latter may also need the rebase if they were written with + // the "LEGACY" rebase mode. + if (version < "3.0.0" || lookupFileMeta("org.apache.spark.legacyDateTime") != null) { + LegacyBehaviorPolicy.LEGACY + } else { + LegacyBehaviorPolicy.CORRECTED + } + }.getOrElse(LegacyBehaviorPolicy.withName(modeByConfig)) + } + // scalastyle:on + +} diff --git a/hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark32HoodieParquetFileFormat.scala b/hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark32HoodieParquetFileFormat.scala index f2a0a21df830f..7135f19e95e2d 100644 --- a/hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark32HoodieParquetFileFormat.scala +++ b/hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark32HoodieParquetFileFormat.scala @@ -22,6 +22,7 @@ import org.apache.hadoop.fs.Path import org.apache.hadoop.mapred.FileSplit import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl import org.apache.hadoop.mapreduce.{JobID, TaskAttemptID, TaskID, TaskType} +import org.apache.hudi.HoodieSparkUtils import org.apache.hudi.client.utils.SparkInternalSchemaConverter import org.apache.hudi.common.fs.FSUtils import org.apache.hudi.common.util.InternalSchemaCache @@ -37,10 +38,10 @@ import org.apache.parquet.hadoop.{ParquetInputFormat, ParquetRecordReader} import org.apache.spark.TaskContext import org.apache.spark.sql.SparkSession import org.apache.spark.sql.catalyst.InternalRow -import org.apache.spark.sql.catalyst.expressions.{Cast, JoinedRow} import org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection +import org.apache.spark.sql.catalyst.expressions.{Cast, JoinedRow} import org.apache.spark.sql.catalyst.util.DateTimeUtils -import org.apache.spark.sql.execution.datasources.parquet.Spark32HoodieParquetFileFormat.{pruneInternalSchema, rebuildFilterFromParquet} +import org.apache.spark.sql.execution.datasources.parquet.Spark32HoodieParquetFileFormat._ import org.apache.spark.sql.execution.datasources.{DataSourceUtils, PartitionedFile, RecordReaderIterator} import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.sources._ @@ -148,8 +149,8 @@ class Spark32HoodieParquetFileFormat(private val shouldAppendPartitionValues: Bo val shouldUseInternalSchema = !isNullOrEmpty(internalSchemaStr) && querySchemaOption.isPresent val tablePath = sharedConf.get(SparkInternalSchemaConverter.HOODIE_TABLE_PATH) - val commitInstantTime = FSUtils.getCommitTime(filePath.getName).toLong; val fileSchema = if (shouldUseInternalSchema) { + val commitInstantTime = FSUtils.getCommitTime(filePath.getName).toLong; val validCommits = sharedConf.get(SparkInternalSchemaConverter.HOODIE_VALID_COMMITS_LIST) InternalSchemaCache.getInternalSchemaByVersionId(commitInstantTime, tablePath, sharedConf, if (validCommits == null) "" else validCommits) } else { @@ -158,21 +159,38 @@ class Spark32HoodieParquetFileFormat(private val shouldAppendPartitionValues: Bo lazy val footerFileMetaData = ParquetFooterReader.readFooter(sharedConf, filePath, SKIP_ROW_GROUPS).getFileMetaData - val datetimeRebaseSpec = DataSourceUtils.datetimeRebaseSpec( - footerFileMetaData.getKeyValueMetaData.get, - datetimeRebaseModeInRead) // Try to push down filters when filter push-down is enabled. val pushed = if (enableParquetFilterPushDown) { val parquetSchema = footerFileMetaData.getSchema - val parquetFilters = new ParquetFilters( - parquetSchema, - pushDownDate, - pushDownTimestamp, - pushDownDecimal, - pushDownStringStartWith, - pushDownInFilterThreshold, - isCaseSensitive, - datetimeRebaseSpec) + val parquetFilters = if (HoodieSparkUtils.gteqSpark3_2_1) { + // NOTE: Below code could only be compiled against >= Spark 3.2.1, + // and unfortunately won't compile against Spark 3.2.0 + // However this code is runtime-compatible w/ both Spark 3.2.0 and >= Spark 3.2.1 + val datetimeRebaseSpec = + DataSourceUtils.datetimeRebaseSpec(footerFileMetaData.getKeyValueMetaData.get, datetimeRebaseModeInRead) + new ParquetFilters( + parquetSchema, + pushDownDate, + pushDownTimestamp, + pushDownDecimal, + pushDownStringStartWith, + pushDownInFilterThreshold, + isCaseSensitive, + datetimeRebaseSpec) + } else { + // Spark 3.2.0 + val datetimeRebaseMode = + Spark32DataSourceUtils.datetimeRebaseMode(footerFileMetaData.getKeyValueMetaData.get, datetimeRebaseModeInRead) + createParquetFilters( + parquetSchema, + pushDownDate, + pushDownTimestamp, + pushDownDecimal, + pushDownStringStartWith, + pushDownInFilterThreshold, + isCaseSensitive, + datetimeRebaseMode) + } filters.map(rebuildFilterFromParquet(_, fileSchema, querySchemaOption.orElse(null))) // Collects all converted Parquet filter predicates. Notice that not all predicates can be // converted (`ParquetFilters.createFilter` returns an `Option`). That's why a `flatMap` @@ -198,21 +216,21 @@ class Spark32HoodieParquetFileFormat(private val shouldAppendPartitionValues: Bo None } - val int96RebaseSpec = DataSourceUtils.int96RebaseSpec( - footerFileMetaData.getKeyValueMetaData.get, - int96RebaseModeInRead) - val attemptId = new TaskAttemptID(new TaskID(new JobID(), TaskType.MAP, 0), 0) // Clone new conf val hadoopAttemptConf = new Configuration(broadcastedHadoopConf.value.value) - var typeChangeInfos: java.util.Map[Integer, Pair[DataType, DataType]] = new java.util.HashMap() - if (shouldUseInternalSchema) { + val typeChangeInfos: java.util.Map[Integer, Pair[DataType, DataType]] = if (shouldUseInternalSchema) { val mergedInternalSchema = new InternalSchemaMerger(fileSchema, querySchemaOption.get(), true, true).mergeSchema() val mergedSchema = SparkInternalSchemaConverter.constructSparkSchemaFromInternalSchema(mergedInternalSchema) - typeChangeInfos = SparkInternalSchemaConverter.collectTypeChangedCols(querySchemaOption.get(), mergedInternalSchema) + hadoopAttemptConf.set(ParquetReadSupport.SPARK_ROW_REQUESTED_SCHEMA, mergedSchema.json) + + SparkInternalSchemaConverter.collectTypeChangedCols(querySchemaOption.get(), mergedInternalSchema) + } else { + new java.util.HashMap() } + val hadoopAttemptContext = new TaskAttemptContextImpl(hadoopAttemptConf, attemptId) @@ -225,6 +243,10 @@ class Spark32HoodieParquetFileFormat(private val shouldAppendPartitionValues: Bo if (enableVectorizedReader) { val vectorizedReader = if (shouldUseInternalSchema) { + val int96RebaseSpec = + DataSourceUtils.int96RebaseSpec(footerFileMetaData.getKeyValueMetaData.get, int96RebaseModeInRead) + val datetimeRebaseSpec = + DataSourceUtils.datetimeRebaseSpec(footerFileMetaData.getKeyValueMetaData.get, datetimeRebaseModeInRead) new Spark32HoodieVectorizedParquetRecordReader( convertTz.orNull, datetimeRebaseSpec.mode.toString, @@ -234,7 +256,14 @@ class Spark32HoodieParquetFileFormat(private val shouldAppendPartitionValues: Bo enableOffHeapColumnVector && taskContext.isDefined, capacity, typeChangeInfos) - } else { + } else if (HoodieSparkUtils.gteqSpark3_2_1) { + // NOTE: Below code could only be compiled against >= Spark 3.2.1, + // and unfortunately won't compile against Spark 3.2.0 + // However this code is runtime-compatible w/ both Spark 3.2.0 and >= Spark 3.2.1 + val int96RebaseSpec = + DataSourceUtils.int96RebaseSpec(footerFileMetaData.getKeyValueMetaData.get, int96RebaseModeInRead) + val datetimeRebaseSpec = + DataSourceUtils.datetimeRebaseSpec(footerFileMetaData.getKeyValueMetaData.get, datetimeRebaseModeInRead) new VectorizedParquetRecordReader( convertTz.orNull, datetimeRebaseSpec.mode.toString, @@ -243,7 +272,20 @@ class Spark32HoodieParquetFileFormat(private val shouldAppendPartitionValues: Bo int96RebaseSpec.timeZone, enableOffHeapColumnVector && taskContext.isDefined, capacity) + } else { + // Spark 3.2.0 + val datetimeRebaseMode = + Spark32DataSourceUtils.datetimeRebaseMode(footerFileMetaData.getKeyValueMetaData.get, datetimeRebaseModeInRead) + val int96RebaseMode = + Spark32DataSourceUtils.int96RebaseMode(footerFileMetaData.getKeyValueMetaData.get, int96RebaseModeInRead) + createVectorizedParquetRecordReader( + convertTz.orNull, + datetimeRebaseMode.toString, + int96RebaseMode.toString, + enableOffHeapColumnVector && taskContext.isDefined, + capacity) } + // SPARK-37089: We cannot register a task completion listener to close this iterator here // because downstream exec nodes have already registered their listeners. Since listeners // are executed in reverse order of registration, a listener registered here would close the @@ -279,12 +321,32 @@ class Spark32HoodieParquetFileFormat(private val shouldAppendPartitionValues: Bo } } else { logDebug(s"Falling back to parquet-mr") - // ParquetRecordReader returns InternalRow - val readSupport = new ParquetReadSupport( - convertTz, - enableVectorizedReader = false, - datetimeRebaseSpec, - int96RebaseSpec) + val readSupport = if (HoodieSparkUtils.gteqSpark3_2_1) { + // ParquetRecordReader returns InternalRow + // NOTE: Below code could only be compiled against >= Spark 3.2.1, + // and unfortunately won't compile against Spark 3.2.0 + // However this code is runtime-compatible w/ both Spark 3.2.0 and >= Spark 3.2.1 + val int96RebaseSpec = + DataSourceUtils.int96RebaseSpec(footerFileMetaData.getKeyValueMetaData.get, int96RebaseModeInRead) + val datetimeRebaseSpec = + DataSourceUtils.datetimeRebaseSpec(footerFileMetaData.getKeyValueMetaData.get, datetimeRebaseModeInRead) + new ParquetReadSupport( + convertTz, + enableVectorizedReader = false, + datetimeRebaseSpec, + int96RebaseSpec) + } else { + val datetimeRebaseMode = + Spark32DataSourceUtils.datetimeRebaseMode(footerFileMetaData.getKeyValueMetaData.get, datetimeRebaseModeInRead) + val int96RebaseMode = + Spark32DataSourceUtils.int96RebaseMode(footerFileMetaData.getKeyValueMetaData.get, int96RebaseModeInRead) + createParquetReadSupport( + convertTz, + /* enableVectorizedReader = */ false, + datetimeRebaseMode, + int96RebaseMode) + } + val reader = if (pushed.isDefined && enableRecordFilter) { val parquetFilter = FilterCompat.get(pushed.get, null) new ParquetRecordReader[InternalRow](readSupport, parquetFilter) @@ -332,10 +394,47 @@ class Spark32HoodieParquetFileFormat(private val shouldAppendPartitionValues: Bo } } } + } object Spark32HoodieParquetFileFormat { + /** + * NOTE: This method is specific to Spark 3.2.0 + */ + private def createParquetFilters(args: Any*): ParquetFilters = { + // NOTE: ParquetFilters ctor args contain Scala enum, therefore we can't look it + // up by arg types, and have to instead rely on the number of args based on individual class; + // the ctor order is not guaranteed + val ctor = classOf[ParquetFilters].getConstructors.maxBy(_.getParameterCount) + ctor.newInstance(args.map(_.asInstanceOf[AnyRef]): _*) + .asInstanceOf[ParquetFilters] + } + + /** + * NOTE: This method is specific to Spark 3.2.0 + */ + private def createParquetReadSupport(args: Any*): ParquetReadSupport = { + // NOTE: ParquetReadSupport ctor args contain Scala enum, therefore we can't look it + // up by arg types, and have to instead rely on the number of args based on individual class; + // the ctor order is not guaranteed + val ctor = classOf[ParquetReadSupport].getConstructors.maxBy(_.getParameterCount) + ctor.newInstance(args.map(_.asInstanceOf[AnyRef]): _*) + .asInstanceOf[ParquetReadSupport] + } + + /** + * NOTE: This method is specific to Spark 3.2.0 + */ + private def createVectorizedParquetRecordReader(args: Any*): VectorizedParquetRecordReader = { + // NOTE: ParquetReadSupport ctor args contain Scala enum, therefore we can't look it + // up by arg types, and have to instead rely on the number of args based on individual class; + // the ctor order is not guaranteed + val ctor = classOf[VectorizedParquetRecordReader].getConstructors.maxBy(_.getParameterCount) + ctor.newInstance(args.map(_.asInstanceOf[AnyRef]): _*) + .asInstanceOf[VectorizedParquetRecordReader] + } + def pruneInternalSchema(internalSchemaStr: String, requiredSchema: StructType): String = { val querySchemaOption = SerDeHelper.fromJson(internalSchemaStr) if (querySchemaOption.isPresent && requiredSchema.nonEmpty) {