carloea2 commented on code in PR #8512: URL: https://github.com/apache/texera/pull/8512#discussion_r3992542228
########## 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: Converting every timestamp to milliseconds discards valid precision. A Parquet timestamp in microseconds containing 2023-11-14 22:13:20.123456 is read as 2023-11-14 22:13:20.123 by the native executor; the export preserves .123456. I reproduced this in UTC, with a whole-millisecond value passing as a control. Please retain the fractional remainder when constructing the Timestamp. ########## 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: DECIMAL annotations are treated as ordinary integers here. I wrote a decimal128(9, 2) Parquet column containing 12.34 with integer storage: the native reader declares INTEGER and returns 1234, while PyArrow reads Decimal("12.34"). Please apply the decimal scale or reject unsupported decimal columns explicitly instead of silently changing the value. -- 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. 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