pvary commented on code in PR #14435: URL: https://github.com/apache/iceberg/pull/14435#discussion_r2556275565
########## parquet/src/main/java/org/apache/iceberg/parquet/ParquetFileMerger.java: ########## @@ -0,0 +1,540 @@ +/* + * 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.parquet; + +import static java.util.Collections.emptyMap; + +import java.io.IOException; +import java.nio.ByteBuffer; +import java.nio.ByteOrder; +import java.util.List; +import java.util.Map; +import org.apache.iceberg.MetadataColumns; +import org.apache.iceberg.io.InputFile; +import org.apache.iceberg.io.OutputFile; +import org.apache.iceberg.io.SeekableInputStream; +import org.apache.iceberg.relocated.com.google.common.base.Preconditions; +import org.apache.iceberg.relocated.com.google.common.collect.Lists; +import org.apache.parquet.bytes.BytesInput; +import org.apache.parquet.column.ColumnDescriptor; +import org.apache.parquet.column.Encoding; +import org.apache.parquet.column.ParquetProperties; +import org.apache.parquet.column.statistics.LongStatistics; +import org.apache.parquet.hadoop.ParquetFileReader; +import org.apache.parquet.hadoop.ParquetFileWriter; +import org.apache.parquet.hadoop.metadata.BlockMetaData; +import org.apache.parquet.hadoop.metadata.ColumnChunkMetaData; +import org.apache.parquet.hadoop.metadata.CompressionCodecName; +import org.apache.parquet.io.DelegatingSeekableInputStream; +import org.apache.parquet.schema.MessageType; +import org.apache.parquet.schema.PrimitiveType; +import org.apache.parquet.schema.Type; +import org.apache.parquet.schema.Types; + +/** + * Utility class for performing strict schema validation and merging of Parquet files at the + * row-group level. + * + * <p>This class ensures that all input files have identical Parquet schemas before merging. The + * merge operation is performed by copying row groups directly without + * serialization/deserialization, providing significant performance benefits over traditional + * read-rewrite approaches. + * + * <p>This class works with any Iceberg FileIO implementation (HadoopFileIO, S3FileIO, GCSFileIO, + * etc.), making it cloud-agnostic. + * + * <p>TODO: Encrypted tables are not supported + * + * <p>Key features: + * + * <ul> + * <li>Row group merging without deserialization using {@link ParquetFileWriter#appendFile} + * <li>Strict schema validation - all files must have identical {@link MessageType} + * <li>Metadata merging for Iceberg-specific footer data + * <li>Works with any FileIO implementation (local, S3, GCS, Azure, etc.) + * </ul> + * + * <p>Restrictions: + * + * <ul> + * <li>All files must have compatible schemas (identical {@link MessageType}) + * <li>Files must not be encrypted + * <li>Files must not have associated delete files or delete vectors + * <li>Table must not have a sort order (including z-ordered tables) + * </ul> + * + * <p>Typical usage: + * + * <pre> + * FileIO fileIO = table.io(); + * List<InputFile> inputFiles = Arrays.asList( + * fileIO.newInputFile("s3://bucket/file1.parquet"), + * fileIO.newInputFile("s3://bucket/file2.parquet") + * ); + * OutputFile outputFile = fileIO.newOutputFile("s3://bucket/merged.parquet"); + * long rowGroupSize = 128 * 1024 * 1024; // 128 MB + * int columnIndexTruncateLength = 64; // Default truncation length + * ParquetFileMerger.mergeFiles(inputFiles, outputFile, rowGroupSize, columnIndexTruncateLength, null); + * </pre> + */ +public class ParquetFileMerger { + + private ParquetFileMerger() { + // Utility class - prevent instantiation + } + + /** + * Merges multiple Parquet files into a single output file at the row-group level using Iceberg + * FileIO. + * + * <p>This method works with any Iceberg FileIO implementation (S3FileIO, GCSFileIO, etc.), not + * just HadoopFileIO. + * + * <p>All input files must have identical Parquet schemas ({@link MessageType}), otherwise an + * exception is thrown. The merge is performed by copying row groups directly without + * serialization/deserialization. + * + * @param inputFiles List of Iceberg input files to merge + * @param outputFile Iceberg output file for the merged result + * @param rowGroupSize Target row group size in bytes + * @param columnIndexTruncateLength Maximum length for min/max values in column index + * @param extraMetadata Additional metadata to include in the output file footer (can be null) + * @throws IOException if I/O error occurs during merge operation + * @throws IllegalArgumentException if no input files provided or schemas don't match + */ + public static void mergeFiles( + List<InputFile> inputFiles, + OutputFile outputFile, + long rowGroupSize, + int columnIndexTruncateLength, + Map<String, String> extraMetadata) + throws IOException { + Preconditions.checkArgument( + inputFiles != null && !inputFiles.isEmpty(), "No input files provided for merging"); + + // Validate and get the common schema from the first file + MessageType schema = readSchema(inputFiles.get(0)); + + // Validate all files have the same schema + for (int i = 1; i < inputFiles.size(); i++) { + MessageType currentSchema = readSchema(inputFiles.get(i)); + + if (!schema.equals(currentSchema)) { + throw new IllegalArgumentException( + String.format( + "Schema mismatch detected: file '%s' has schema %s but file '%s' has schema %s. " + + "All files must have identical Parquet schemas for row-group level merging.", + inputFiles.get(0).location(), schema, inputFiles.get(i).location(), currentSchema)); + } + } + + // Create the output Parquet file writer + try (ParquetFileWriter writer = + new ParquetFileWriter( + ParquetIO.file(outputFile), + schema, + ParquetFileWriter.Mode.CREATE, + rowGroupSize, + 0, // maxPaddingSize - hardcoded to 0 (same as ParquetWriter) + columnIndexTruncateLength, + ParquetProperties.DEFAULT_STATISTICS_TRUNCATE_LENGTH, + ParquetProperties.DEFAULT_PAGE_WRITE_CHECKSUM_ENABLED)) { + + writer.start(); + + // Append each input file's row groups to the output + for (InputFile inputFile : inputFiles) { + writer.appendFile(ParquetIO.file(inputFile)); + } + + // End writing with optional metadata + if (extraMetadata != null && !extraMetadata.isEmpty()) { + writer.end(extraMetadata); + } else { + writer.end(emptyMap()); + } + } + } + + /** + * Checks if a list of Iceberg InputFiles can be merged (i.e., they all have identical schemas). + * + * <p>This method works with any Iceberg FileIO implementation (S3FileIO, GCSFileIO, etc.). + * + * @param inputFiles List of Iceberg input files to check + * @return true if all files have identical schemas and can be merged, false otherwise + */ + public static boolean canMerge(List<InputFile> inputFiles) { + try { + if (inputFiles == null || inputFiles.isEmpty()) { + return false; + } + + // Read schema from the first file + MessageType firstSchema = readSchema(inputFiles.get(0)); + + // Validate all remaining files have the same schema + for (int i = 1; i < inputFiles.size(); i++) { + MessageType currentSchema = readSchema(inputFiles.get(i)); + + if (!firstSchema.equals(currentSchema)) { + return false; + } + } + + return true; + } catch (IllegalArgumentException | IOException e) { + return false; + } + } + + /** + * Checks if a list of Iceberg InputFiles can be merged with explicit firstRowIds. + * + * <p>This method performs additional validation beyond {@link #canMerge(List)} to ensure that + * files can be merged when explicit firstRowIds are provided. + * + * <p>Returns false if files already have a physical _row_id column and firstRowIds are provided, + * since we cannot override existing row IDs. + * + * @param inputFiles List of Iceberg input files to check + * @param firstRowIds Optional list of starting row IDs for each input file (null if no lineage + * needed) + * @return true if files can be merged with the given firstRowIds, false otherwise + */ + public static boolean canMergeWithRowIds(List<InputFile> inputFiles, List<Long> firstRowIds) { + // First check normal merge compatibility (schemas, etc.) + if (!canMerge(inputFiles)) { + return false; + } + + // If firstRowIds provided, ensure files don't already have physical _row_id + boolean needsRowLineageProcessing = firstRowIds != null && !firstRowIds.isEmpty(); + if (needsRowLineageProcessing) { + try { + MessageType schema = readSchema(inputFiles.get(0)); + if (schema.containsField(MetadataColumns.ROW_ID.name())) { + // Files already have physical _row_id - can't override with new firstRowIds + return false; + } + } catch (IOException e) { + return false; + } + } + + return true; + } + + /** + * Reads the Parquet schema from an Iceberg InputFile. + * + * @param inputFile Iceberg input file to read schema from + * @return MessageType schema of the Parquet file + * @throws IOException if reading fails + */ + private static MessageType readSchema(InputFile inputFile) throws IOException { + return ParquetFileReader.open(ParquetIO.file(inputFile)) + .getFooter() + .getFileMetaData() + .getSchema(); + } + + /** + * Validates that all input files have the same Parquet schema. + * + * @param inputFiles List of files to validate + * @param firstSchema Schema from the first file to compare against + * @throws IOException if reading fails + * @throws IllegalArgumentException if schemas don't match + */ + private static void validateSchemasMatch(List<InputFile> inputFiles, MessageType firstSchema) + throws IOException { + for (int i = 1; i < inputFiles.size(); i++) { + MessageType currentSchema = readSchema(inputFiles.get(i)); + if (!firstSchema.equals(currentSchema)) { + throw new IllegalArgumentException( + String.format( + "Schema mismatch detected: file '%s' has schema %s but file '%s' has schema %s. " + + "All files must have identical Parquet schemas for row-group level merging.", + inputFiles.get(0).location(), + firstSchema, + inputFiles.get(i).location(), + currentSchema)); + } + } + } + + /** Internal method to merge files when schema is already known. */ + private static void mergeFilesWithSchema( + List<InputFile> inputFiles, + OutputFile outputFile, + MessageType schema, + long rowGroupSize, + int columnIndexTruncateLength, + Map<String, String> extraMetadata) + throws IOException { + try (ParquetFileWriter writer = + new ParquetFileWriter( + ParquetIO.file(outputFile), + schema, + ParquetFileWriter.Mode.CREATE, + rowGroupSize, + 0, // maxPaddingSize - hardcoded to 0 (same as ParquetWriter) + columnIndexTruncateLength, + ParquetProperties.DEFAULT_STATISTICS_TRUNCATE_LENGTH, + ParquetProperties.DEFAULT_PAGE_WRITE_CHECKSUM_ENABLED)) { + + writer.start(); + for (InputFile inputFile : inputFiles) { + writer.appendFile(ParquetIO.file(inputFile)); + } + if (extraMetadata != null && !extraMetadata.isEmpty()) { + writer.end(extraMetadata); + } else { + writer.end(emptyMap()); + } + } + } + + /** Internal method to merge files with row IDs when base schema is already known. */ + private static void mergeFilesWithRowIdsAndSchema( + List<InputFile> inputFiles, + OutputFile outputFile, + List<Long> firstRowIds, + MessageType baseSchema, + long rowGroupSize, + int columnIndexTruncateLength, + Map<String, String> extraMetadata) + throws IOException { + // Extend schema to include _row_id column + MessageType extendedSchema = addRowIdColumn(baseSchema); + + // Create output writer with extended schema + try (ParquetFileWriter writer = + new ParquetFileWriter( + ParquetIO.file(outputFile), + extendedSchema, + ParquetFileWriter.Mode.CREATE, + rowGroupSize, + 0, // maxPaddingSize - hardcoded to 0 (same as ParquetWriter) + columnIndexTruncateLength, + ParquetProperties.DEFAULT_STATISTICS_TRUNCATE_LENGTH, + ParquetProperties.DEFAULT_PAGE_WRITE_CHECKSUM_ENABLED)) { + + writer.start(); + + // Get _row_id column descriptor from extended schema + ColumnDescriptor rowIdDescriptor = + extendedSchema.getColumnDescription(new String[] {MetadataColumns.ROW_ID.name()}); + + // Process each input file + for (int fileIdx = 0; fileIdx < inputFiles.size(); fileIdx++) { + InputFile inputFile = inputFiles.get(fileIdx); + long currentRowId = firstRowIds.get(fileIdx); + + try (ParquetFileReader reader = ParquetFileReader.open(ParquetIO.file(inputFile))) { + List<BlockMetaData> rowGroups = reader.getFooter().getBlocks(); + + for (BlockMetaData rowGroup : rowGroups) { + long rowCount = rowGroup.getRowCount(); + writer.startBlock(rowCount); + + // Copy all existing column chunks (binary copy) + copyColumnChunks(writer, baseSchema, inputFile, rowGroup); + + // Write new _row_id column chunk + writeRowIdColumnChunk(writer, rowIdDescriptor, currentRowId, rowCount); + currentRowId += rowCount; + writer.endBlock(); + } + } + } + + if (extraMetadata != null && !extraMetadata.isEmpty()) { + writer.end(extraMetadata); + } else { + writer.end(emptyMap()); + } + } + } + + /** + * Merges multiple Parquet files with optional row lineage preservation. + * + * <p>This method intelligently handles row lineage based on the input files and firstRowIds: + * + * <ul> + * <li>If firstRowIds is null/empty: performs simple binary copy merge + * <li>If files already have physical _row_id column: performs simple binary copy merge + * <li>Otherwise: synthesizes physical _row_id column from virtual metadata + * </ul> + * + * @param inputFiles List of Iceberg input files to merge + * @param outputFile Iceberg output file for the merged result + * @param firstRowIds Optional list of starting row IDs for each input file (null if no lineage + * needed) + * @param rowGroupSize Target row group size in bytes + * @param columnIndexTruncateLength Maximum length for min/max values in column index + * @param extraMetadata Additional metadata to include in the output file footer (can be null) + * @return true if output file has physical _row_id column, false otherwise + * @throws IOException if I/O error occurs during merge operation + */ + public static boolean mergeFilesWithOptionalRowIds( + List<InputFile> inputFiles, + OutputFile outputFile, + List<Long> firstRowIds, + long rowGroupSize, + int columnIndexTruncateLength, + Map<String, String> extraMetadata) + throws IOException { + // Read schema once and validate all files + MessageType schema = readSchema(inputFiles.get(0)); + validateSchemasMatch(inputFiles, schema); + + // Check if row lineage processing is requested + boolean needsRowLineageProcessing = firstRowIds != null && !firstRowIds.isEmpty(); + + if (needsRowLineageProcessing) { + if (schema.containsField(MetadataColumns.ROW_ID.name())) { + // Files already have physical _row_id - use simple binary copy (fastest!) + mergeFilesWithSchema( + inputFiles, outputFile, schema, rowGroupSize, columnIndexTruncateLength, extraMetadata); + return true; // Output has physical _row_id from input + } else { + // Files have virtual _row_id - synthesize physical column + mergeFilesWithRowIdsAndSchema( + inputFiles, + outputFile, + firstRowIds, + schema, + rowGroupSize, + columnIndexTruncateLength, + extraMetadata); + return true; // We just wrote physical _row_id + } + } else { + // No row lineage processing needed - simple binary merge + mergeFilesWithSchema( + inputFiles, outputFile, schema, rowGroupSize, columnIndexTruncateLength, extraMetadata); + return false; // No physical _row_id + } + } + + /** + * Extends a Parquet schema by adding the _row_id metadata column. + * + * @param baseSchema Original Parquet schema + * @return Extended schema with _row_id column added + */ + private static MessageType addRowIdColumn(MessageType baseSchema) { + // Create _row_id column: required int64 (no logical type annotation) + PrimitiveType rowIdType = + Types.required(PrimitiveType.PrimitiveTypeName.INT64).named(MetadataColumns.ROW_ID.name()); + + // Add to existing fields + List<Type> fields = Lists.newArrayList(baseSchema.getFields()); + fields.add(rowIdType); + + return new MessageType(baseSchema.getName(), fields); + } + + /** + * Writes a _row_id column chunk with sequential row IDs. + * + * <p>Uses PLAIN encoding and DataPageV2 format for simplicity. Each row ID is encoded as an + * 8-byte little-endian long value. + * + * @param writer ParquetFileWriter to write to + * @param rowIdDescriptor Column descriptor for _row_id + * @param startRowId Starting row ID for this row group + * @param rowCount Number of rows in this row group + * @throws IOException if writing fails + */ + private static void writeRowIdColumnChunk( + ParquetFileWriter writer, ColumnDescriptor rowIdDescriptor, long startRowId, long rowCount) + throws IOException { + + // Start the column chunk + writer.startColumn(rowIdDescriptor, rowCount, CompressionCodecName.UNCOMPRESSED); + + // Encode row IDs as PLAIN encoding (8 bytes per long, little-endian) + int dataSize = (int) (rowCount * 8); + ByteBuffer buffer = ByteBuffer.allocate(dataSize).order(ByteOrder.LITTLE_ENDIAN); + + for (long i = 0; i < rowCount; i++) { + buffer.putLong(startRowId + i); + } Review Comment: Can we have a better compression? Maybe RLE, or something similar? 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