shangxinli commented on code in PR #14435: URL: https://github.com/apache/iceberg/pull/14435#discussion_r2556619786
########## spark/v4.0/spark/src/main/java/org/apache/iceberg/spark/actions/SparkParquetFileMergeRunner.java: ########## @@ -0,0 +1,466 @@ +/* + * 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.iceberg.spark.actions; + +import java.io.IOException; +import java.io.Serializable; +import java.nio.ByteBuffer; +import java.util.List; +import java.util.Set; +import java.util.UUID; +import java.util.stream.Collectors; +import org.apache.hadoop.conf.Configuration; +import org.apache.iceberg.DataFile; +import org.apache.iceberg.DataFiles; +import org.apache.iceberg.FileFormat; +import org.apache.iceberg.MetadataColumns; +import org.apache.iceberg.Metrics; +import org.apache.iceberg.MetricsConfig; +import org.apache.iceberg.PartitionSpec; +import org.apache.iceberg.StructLike; +import org.apache.iceberg.Table; +import org.apache.iceberg.TableProperties; +import org.apache.iceberg.TableUtil; +import org.apache.iceberg.actions.RewriteFileGroup; +import org.apache.iceberg.io.FileIO; +import org.apache.iceberg.io.InputFile; +import org.apache.iceberg.io.OutputFile; +import org.apache.iceberg.parquet.ParquetFileMerger; +import org.apache.iceberg.parquet.ParquetUtil; +import org.apache.iceberg.relocated.com.google.common.collect.Lists; +import org.apache.iceberg.relocated.com.google.common.collect.Sets; +import org.apache.iceberg.spark.FileRewriteCoordinator; +import org.apache.iceberg.types.Conversions; +import org.apache.iceberg.types.Types; +import org.apache.iceberg.util.PropertyUtil; +import org.apache.parquet.crypto.ParquetCryptoRuntimeException; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.sql.SparkSession; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** + * Extension of SparkBinPackFileRewriteRunner that uses ParquetFileMerger for efficient row-group + * level merging of Parquet files when applicable. + * + * <p>This runner uses {@link ParquetFileMerger} to merge Parquet files at the row-group level + * without full deserialization, which is significantly faster than the standard Spark rewrite + * approach for Parquet files. + * + * <p>The decision to use this runner vs. SparkBinPackFileRewriteRunner is controlled by the + * configuration option {@code use-parquet-file-merger}. + */ +public class SparkParquetFileMergeRunner extends SparkBinPackFileRewriteRunner { + private static final Logger LOG = LoggerFactory.getLogger(SparkParquetFileMergeRunner.class); + private final FileRewriteCoordinator coordinator = FileRewriteCoordinator.get(); + + public SparkParquetFileMergeRunner(SparkSession spark, Table table) { + super(spark, table); + } + + @Override + public String description() { + return "PARQUET-MERGE"; + } + + @Override + protected void doRewrite(String groupId, RewriteFileGroup group) { + // Early validation: check if requirements are met + if (!canUseMerger(group)) { + LOG.info( + "Row-group merge requirements not met for group {}. Using standard Spark rewrite.", + groupId); + super.doRewrite(groupId, group); + return; + } + + // Requirements met - attempt row-group level merge + try { + LOG.info( + "Merging {} Parquet files using row-group level merge (group: {})", + group.rewrittenFiles().size(), + groupId); + mergeParquetFilesDistributed(groupId, group); + } catch (Exception e) { + LOG.warn( + "Row-group merge failed for group {}, falling back to standard Spark rewrite: {}", + groupId, + e.getMessage(), + e); + // Fallback to standard rewrite + super.doRewrite(groupId, group); + } + } + + /** + * Checks if the file group can use row-group level merging. + * + * <p>Requirements: + * + * <ul> + * <li>All files must be Parquet format + * <li>Table must not have a sort order (no sorting or z-ordering) + * <li>Files must not have delete files or delete vectors + * <li>Files must have compatible schemas (verified by ParquetFileMerger.canMerge) + * <li>Files must not be encrypted (detected by ParquetCryptoRuntimeException) + * </ul> + * + * @param group the file group to check + * @return true if row-group merging can be used, false otherwise + */ + private boolean canUseMerger(RewriteFileGroup group) { + // Check if all files are Parquet format + boolean allParquet = + group.rewrittenFiles().stream().allMatch(file -> file.format() == FileFormat.PARQUET); + + if (!allParquet) { + LOG.debug("Cannot use row-group merge: not all files are Parquet format"); + return false; + } + + // Check if table has a sort order - row-group merge cannot preserve sort order + if (table().sortOrder().isSorted()) { + LOG.debug( + "Cannot use row-group merge: table has a sort order ({}). " + + "Row-group merging would not preserve the sort order.", + table().sortOrder()); + return false; + } + + // Check for delete files - row-group merge cannot apply deletes + boolean hasDeletes = group.fileScanTasks().stream().anyMatch(task -> !task.deletes().isEmpty()); + + if (hasDeletes) { + LOG.debug( + "Cannot use row-group merge: files have delete files or delete vectors. " + + "Row-group merging cannot apply deletes."); + return false; + } + + // Validate schema compatibility and check for encryption using Iceberg InputFile API + try { + List<InputFile> inputFiles = + group.rewrittenFiles().stream() + .map(f -> table().io().newInputFile(f.path().toString())) + .collect(Collectors.toList()); + + // Check if table supports row lineage (determines if firstRowIds will be extracted) + boolean preserveRowLineage = TableUtil.supportsRowLineage(table()); + + // Extract firstRowIds from the files (null if row lineage not supported) + List<Long> firstRowIds = null; + if (preserveRowLineage) { + firstRowIds = + group.rewrittenFiles().stream().map(DataFile::firstRowId).collect(Collectors.toList()); + } + + // Validate with row lineage awareness + boolean canMerge = ParquetFileMerger.canMergeWithRowIds(inputFiles, firstRowIds); + + if (!canMerge) { + LOG.warn( + "Cannot use row-group merge for {} files. Falling back to standard rewrite. " + + "Reason: {}", + group.rewrittenFiles().size(), + preserveRowLineage && !firstRowIds.isEmpty() + ? "Files already contain physical _row_id column and row lineage is enabled" + : "Schema validation failed"); + return false; + } + + return true; + } catch (ParquetCryptoRuntimeException e) { + // ParquetFileReader.open() throws this when trying to read an encrypted footer without keys. + // This happens in ParquetFileMerger.canMerge() when validating schemas. + // Exception message: "Trying to read file with encrypted footer. No keys available" + LOG.debug("Cannot use row-group merge: encrypted files detected", e); + return false; + } catch (Exception e) { + LOG.warn("Cannot use row-group merge: validation failed", e); + return false; + } + } + + /** + * Merges Parquet files in the group, respecting the expected output file count determined by the + * planner. Files are distributed evenly across the expected number of output files. + */ + private void mergeParquetFilesDistributed(String groupId, RewriteFileGroup group) { + PartitionSpec spec = table().specs().get(group.outputSpecId()); + StructLike partition = group.info().partition(); + long maxOutputFileSize = group.maxOutputFileSize(); + int expectedOutputFiles = group.expectedOutputFiles(); + + LOG.info( + "Merging {} Parquet files into {} expected output files (group: {})", + group.rewrittenFiles().size(), + expectedOutputFiles, + groupId); + + // Check if table supports row lineage + boolean preserveRowLineage = TableUtil.supportsRowLineage(table()); + + // Distribute files evenly across expected output files (planner already determined the count) + List<List<DataFile>> fileBatches = + distributeFilesEvenly(group.rewrittenFiles(), expectedOutputFiles); + + // Get row group size from table properties + long rowGroupSize = + PropertyUtil.propertyAsLong( + table().properties(), + TableProperties.PARQUET_ROW_GROUP_SIZE_BYTES, + TableProperties.PARQUET_ROW_GROUP_SIZE_BYTES_DEFAULT); + + // Get column index truncate length from Hadoop Configuration (same as ParquetWriter) + Configuration hadoopConf = spark().sessionState().newHadoopConf(); + int columnIndexTruncateLength = hadoopConf.getInt("parquet.columnindex.truncate.length", 64); + + // Create merge tasks for each batch + List<MergeTaskInfo> mergeTasks = Lists.newArrayList(); + int batchIndex = 0; + for (List<DataFile> batch : fileBatches) { + String taskId = String.format("%s-%d", groupId, batchIndex++); + List<String> filePaths = + batch.stream().map(f -> f.path().toString()).collect(Collectors.toList()); + + // Extract firstRowIds for row lineage preservation + List<Long> firstRowIds = null; + if (preserveRowLineage) { + firstRowIds = batch.stream().map(DataFile::firstRowId).collect(Collectors.toList()); + LOG.debug( + "Task {} will preserve row lineage with firstRowIds: {} (group: {})", + taskId, + firstRowIds, + groupId); + } + + mergeTasks.add( + new MergeTaskInfo( + taskId, + filePaths, + spec, + partition, + rowGroupSize, + columnIndexTruncateLength, + firstRowIds)); + } + + // Get FileIO for executors - table().io() is serializable + FileIO fileIO = table().io(); + + // Execute merges on executors in parallel + JavaSparkContext jsc = JavaSparkContext.fromSparkContext(spark().sparkContext()); + JavaRDD<MergeTaskInfo> taskRDD = jsc.parallelize(mergeTasks, mergeTasks.size()); + List<MergeResult> mergeResults = taskRDD.map(task -> mergeFilesForTask(task, fileIO)).collect(); + + // Driver constructs DataFiles from metadata + MetricsConfig metricsConfig = MetricsConfig.getDefault(); + Set<DataFile> newFiles = Sets.newHashSet(); + + for (MergeResult mergeResult : mergeResults) { + Metrics metrics = + ParquetUtil.fileMetrics(table().io().newInputFile(mergeResult.getPath()), metricsConfig); + + DataFiles.Builder builder = + DataFiles.builder(mergeResult.getSpec()) + .withPath(mergeResult.getPath()) + .withFormat(FileFormat.PARQUET) + .withPartition(mergeResult.getPartition()) + .withFileSizeInBytes(mergeResult.getFileSize()) + .withMetrics(metrics); + + // Extract firstRowId from Parquet column statistics (same as binpack approach) + // For V3+ tables with row lineage, the min value of _row_id column becomes firstRowId + if (preserveRowLineage && metrics.lowerBounds() != null) { + ByteBuffer rowIdLowerBound = metrics.lowerBounds().get(MetadataColumns.ROW_ID.fieldId()); + if (rowIdLowerBound != null) { + Long firstRowId = Conversions.fromByteBuffer(Types.LongType.get(), rowIdLowerBound); + builder.withFirstRowId(firstRowId); + } + } + + newFiles.add(builder.build()); + } + + // Register merged files with coordinator + coordinator.stageRewrite(table(), groupId, newFiles); + + LOG.info( + "Successfully merged {} Parquet files into {} output files (group: {})", + group.rewrittenFiles().size(), + newFiles.size(), + groupId); + } + + /** + * Distributes files evenly across the expected number of output files. This simple distribution + * trusts the planner's calculation of expectedOutputFiles and just divides files evenly. + */ + private List<List<DataFile>> distributeFilesEvenly(Set<DataFile> files, int expectedOutputFiles) { + List<DataFile> fileList = Lists.newArrayList(files); + List<List<DataFile>> groups = Lists.newArrayList(); + + if (expectedOutputFiles <= 0 || fileList.isEmpty()) { + return groups; + } + + int filesPerGroup = (int) Math.ceil((double) fileList.size() / expectedOutputFiles); + + for (int i = 0; i < fileList.size(); i += filesPerGroup) { + int endIndex = Math.min(i + filesPerGroup, fileList.size()); + groups.add(fileList.subList(i, endIndex)); + } + + return groups; + } + + /** + * Performs the actual merge operation for a single task on an executor. Returns only metadata + * (file path and size); DataFile construction happens on the driver. + */ + private static MergeResult mergeFilesForTask(MergeTaskInfo task, FileIO fileIO) + throws IOException { + // Convert file path strings to Iceberg InputFile objects + List<InputFile> inputFiles = + task.getFilePaths().stream() + .map(path -> fileIO.newInputFile(path)) + .collect(Collectors.toList()); + + // Generate output file path - derive directory from first input file + String outputFileName = String.format("%s-%s.parquet", task.getTaskId(), UUID.randomUUID()); + String firstInputFilePath = task.getFilePaths().get(0); + int lastSlash = firstInputFilePath.lastIndexOf('/'); + String outputDir = lastSlash > 0 ? firstInputFilePath.substring(0, lastSlash) : ""; + String outputPath = outputDir.isEmpty() ? outputFileName : outputDir + "/" + outputFileName; Review Comment: Make sense! -- This is an automated message from the Apache Git Service. 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