kz930 commented on code in PR #8512: URL: https://github.com/apache/texera/pull/8512#discussion_r3995677753
########## common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/source/scan/parquet/ParquetSchemaMapping.scala: ########## @@ -0,0 +1,96 @@ +/* + * 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.texera.amber.operator.source.scan.parquet + +import org.apache.parquet.schema.LogicalTypeAnnotation +import org.apache.parquet.schema.LogicalTypeAnnotation.{ + DateLogicalTypeAnnotation, + StringLogicalTypeAnnotation, + TimestampLogicalTypeAnnotation +} +import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName +import org.apache.parquet.schema.{MessageType, PrimitiveType, Type} +import org.apache.texera.amber.core.tuple.{Attribute, AttributeType, Schema} + +import scala.jdk.CollectionConverters._ + +/** + * What a Parquet file says its columns are, in Texera's terms. + * + * The file states its own types, so nothing is inferred from the values the way + * a CSV forces. Only the flat primitives map: a column that is a group, a list + * or a map has no Texera column to be, and is refused by name rather than + * silently dropped or stringified. + */ +object ParquetSchemaMapping { + + /** Texera's reading of the file's own schema, in the file's column order. */ + def toTexeraSchema(messageType: MessageType): Schema = + new Schema( + messageType.getFields.asScala.toSeq + .map(field => new Attribute(field.getName, typeOf(field))): _* + ) + + /** The Texera type a Parquet column is read as, or an error naming the column. */ + def typeOf(field: Type): AttributeType = { + if (!field.isPrimitive) { + throw new UnsupportedOperationException( + s"Parquet column '${field.getName}' is a nested ${describe(field)}, which has no Texera " + + "column to be. Flatten it before reading the file." + ) + } + val primitive = field.asPrimitiveType() + primitive.getPrimitiveTypeName match { + case PrimitiveTypeName.BOOLEAN => AttributeType.BOOLEAN + case PrimitiveTypeName.FLOAT | PrimitiveTypeName.DOUBLE => AttributeType.DOUBLE + case PrimitiveTypeName.INT32 => + annotated[DateLogicalTypeAnnotation]( + primitive, + AttributeType.TIMESTAMP, + AttributeType.INTEGER Review Comment: Fixed: a DECIMAL now reads as the number its scale makes of it, as a DOUBLE. The export casts pandas' Decimal objects to float so both sides match. ########## common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/source/scan/parquet/ParquetScanSourceOpExec.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.texera.amber.operator.source.scan.parquet + +import org.apache.parquet.example.data.Group +import org.apache.parquet.example.data.simple.convert.GroupRecordConverter +import org.apache.parquet.hadoop.ParquetFileReader +import org.apache.parquet.io.{ColumnIOFactory, LocalInputFile} +import org.apache.parquet.schema.LogicalTypeAnnotation.{ + DateLogicalTypeAnnotation, + StringLogicalTypeAnnotation, + TimeUnit, + TimestampLogicalTypeAnnotation +} +import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName +import org.apache.parquet.schema.MessageType +import org.apache.texera.amber.core.executor.SourceOperatorExecutor +import org.apache.texera.amber.core.storage.DocumentFactory +import org.apache.texera.amber.core.tuple.TupleLike +import org.apache.texera.amber.util.JSONUtils.objectMapper + +import java.net.URI +import java.sql.Timestamp +import java.time.{Instant, LocalDate, LocalDateTime, ZoneOffset} +import java.util.concurrent.TimeUnit.{MICROSECONDS, MILLISECONDS, NANOSECONDS} +import scala.jdk.CollectionConverters._ + +class ParquetScanSourceOpExec(descString: String) extends SourceOperatorExecutor { + private val desc: ParquetScanSourceOpDesc = + objectMapper.readValue(descString, classOf[ParquetScanSourceOpDesc]) + private var reader: Option[ParquetFileReader] = None + + override def open(): Unit = { + val file = DocumentFactory.openReadonlyDocument(new URI(desc.fileName.get)).asFile() + reader = Some(ParquetFileReader.open(new LocalInputFile(file.toPath))) + } + + override def produceTuple(): Iterator[TupleLike] = { + val fileReader = reader.get + val messageType = fileReader.getFooter.getFileMetaData.getSchema + val columns = messageType.getFields.asScala.toVector + + // One row group at a time: the format stores rows in groups and a reader + // that asked for all of them at once would hold the whole file in memory, + // which is the thing a columnar format is chosen to avoid. + val rows: Iterator[TupleLike] = Iterator + .continually(fileReader.readNextRowGroup()) + .takeWhile(_ != null) + .flatMap { pages => + val recordReader = new ColumnIOFactory() + .getColumnIO(messageType) + .getRecordReader(pages, new GroupRecordConverter(messageType)) + (0L until pages.getRowCount).iterator.map { _ => + val group = recordReader.read() + TupleLike(columns.indices.map(i => readField(group, i, messageType)): _*) + } + } + + val afterOffset = rows.drop(desc.offset.getOrElse(0)) + desc.limit.fold(afterOffset)(afterOffset.take) + } + + /** One cell, as the Texera type [[ParquetSchemaMapping]] said the column is. */ + private def readField(group: Group, index: Int, messageType: MessageType): Any = { + // An optional column that was not written for this row repeats zero times. + // Parquet has no "null value": absence is the null. + if (group.getFieldRepetitionCount(index) == 0) return null + val primitive = messageType.getType(index).asPrimitiveType() + primitive.getPrimitiveTypeName match { + case PrimitiveTypeName.BOOLEAN => group.getBoolean(index, 0) + case PrimitiveTypeName.FLOAT => group.getFloat(index, 0).toDouble + case PrimitiveTypeName.DOUBLE => group.getDouble(index, 0) + case PrimitiveTypeName.INT32 => + val raw = group.getInteger(index, 0) + primitive.getLogicalTypeAnnotation match { + // A DATE is a count of days, and Texera's nearest column is a moment. + // Midnight of that day, in the same UTC the file counts from. + case _: DateLogicalTypeAnnotation => + Timestamp.valueOf(LocalDate.ofEpochDay(raw.toLong).atStartOfDay) + case _ => raw + } + case PrimitiveTypeName.INT64 => + val raw = group.getLong(index, 0) + primitive.getLogicalTypeAnnotation match { + case annotation: TimestampLogicalTypeAnnotation => + // A Texera TIMESTAMP carries no zone, so the count from the epoch is + // read with UTC arithmetic and the wall clock it lands on is the + // whole of the value. `new Timestamp(millis)` would instead shift it + // by whatever zone the machine running the workflow is set to, and + // the exported script, which reads the same file with pandas, would + // disagree by exactly that offset. + Timestamp.valueOf( + LocalDateTime.ofInstant( + Instant.ofEpochMilli(toMillis(raw, annotation.getUnit)), Review Comment: Fixed: the count is now read in the unit the file declares, so micros and nanos keep their digits. -- This is an automated message from the Apache Git Service. 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