the-other-tim-brown commented on code in PR #17660: URL: https://github.com/apache/hudi/pull/17660#discussion_r2651104039
########## hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/execution/datasources/lance/SparkLanceReaderBase.scala: ########## @@ -0,0 +1,136 @@ +/* + * 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.lance + +import org.apache.hudi.common.util +import org.apache.hudi.internal.schema.InternalSchema +import org.apache.hudi.io.memory.HoodieArrowAllocator +import org.apache.hudi.io.storage.{HoodieLanceRecordIterator, HoodieSparkLanceReader} +import org.apache.hudi.storage.StorageConfiguration + +import com.lancedb.lance.file.LanceFileReader +import org.apache.hadoop.conf.Configuration +import org.apache.parquet.schema.MessageType +import org.apache.spark.TaskContext +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.JoinedRow +import org.apache.spark.sql.execution.datasources.{PartitionedFile, SparkColumnarFileReader} +import org.apache.spark.sql.sources.Filter +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.util.LanceArrowUtils + +import java.io.IOException + +import scala.collection.JavaConverters._ + +/** + * Reader for Lance files in Spark datasource. + * Implements vectorized reading using LanceArrowColumnVector. + * + * @param enableVectorizedReader whether to use vectorized reading (currently always true for Lance) + */ +class SparkLanceReaderBase(enableVectorizedReader: Boolean) extends SparkColumnarFileReader { + + // Batch size for reading Lance files (number of rows per batch) + private val DEFAULT_BATCH_SIZE = 512 + + /** + * Read a Lance file with schema projection and partition column support. + * + * @param file Lance file to read + * @param requiredSchema desired output schema of the data (columns to read) + * @param partitionSchema schema of the partition columns. Partition values will be appended to the end of every row + * @param internalSchemaOpt option of internal schema for schema.on.read (not currently used for Lance) + * @param filters filters for data skipping. Not guaranteed to be used; the spark plan will also apply the filters. + * @param storageConf the hadoop conf + * @return iterator of rows read from the file output type says [[InternalRow]] but could be [[ColumnarBatch]] + */ + override def read(file: PartitionedFile, + requiredSchema: StructType, + partitionSchema: StructType, + internalSchemaOpt: util.Option[InternalSchema], + filters: Seq[Filter], + storageConf: StorageConfiguration[Configuration], + tableSchemaOpt: util.Option[MessageType] = util.Option.empty()): Iterator[InternalRow] = { + + val filePath = file.filePath.toString + + if (requiredSchema.isEmpty && partitionSchema.isEmpty) { + // No columns requested - return empty iterator + Iterator.empty + } else { + // Create child allocator for reading + val allocator = HoodieArrowAllocator.newChildAllocator(getClass.getSimpleName + "-data-" + filePath, + HoodieSparkLanceReader.LANCE_DATA_ALLOCATOR_SIZE); + + try { + // Open Lance file reader + val lanceReader = LanceFileReader.open(filePath, allocator) + + // Extract column names from required schema for projection + val columnNames: java.util.List[String] = if (requiredSchema.nonEmpty) { + requiredSchema.fields.map(_.name).toList.asJava + } else { + // If only partition columns requested, read minimal data + null + } + + // Get schema from Lance file for HoodieLanceRecordIterator + val arrowSchema = lanceReader.schema() + val sparkSchema = LanceArrowUtils.fromArrowSchema(arrowSchema) + + // Read data with column projection (filters not supported yet) + val arrowReader = lanceReader.readAll(columnNames, null, DEFAULT_BATCH_SIZE) + + // Create iterator using shared HoodieLanceRecordIterator + val lanceIterator = new HoodieLanceRecordIterator( Review Comment: I'm mainly trying to understand the completeness of the feature at this stage. If it is going to be handled in a separate task that is fine with me. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
