nsivabalan commented on code in PR #8956: URL: https://github.com/apache/hudi/pull/8956#discussion_r1235647089
########## hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieCreateRecordUtils.scala: ########## @@ -0,0 +1,280 @@ +/* + * 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.hudi + +import org.apache.avro.Schema +import org.apache.avro.generic.GenericRecord +import org.apache.hudi.DataSourceWriteOptions.{INSERT_DROP_DUPS, PAYLOAD_CLASS_NAME, PRECOMBINE_FIELD} +import org.apache.hudi.avro.HoodieAvroUtils +import org.apache.hudi.common.config.TypedProperties +import org.apache.hudi.common.fs.FSUtils +import org.apache.hudi.common.model.{HoodieKey, HoodieRecord, HoodieRecordLocation, HoodieSparkRecord, WriteOperationType} +import org.apache.hudi.common.model.HoodieRecord.HOODIE_META_COLUMNS_NAME_TO_POS +import org.apache.hudi.config.HoodieWriteConfig +import org.apache.hudi.exception.HoodieException +import org.apache.hudi.keygen.constant.KeyGeneratorOptions +import org.apache.hudi.keygen.factory.HoodieSparkKeyGeneratorFactory +import org.apache.hudi.keygen.{BaseKeyGenerator, KeyGenUtils, KeyGenerator, SparkKeyGeneratorInterface} +import org.apache.spark.TaskContext +import org.apache.spark.api.java.JavaRDD +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.HoodieInternalRowUtils.getCachedUnsafeRowWriter +import org.apache.spark.sql.{DataFrame, HoodieInternalRowUtils} +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.types.StructType +import org.slf4j.LoggerFactory + +import scala.collection.JavaConversions.mapAsJavaMap + +/** Utility class for converting dataframe into RDD[HoodieRecord]. */ +object HoodieCreateRecordUtils { + private val log = LoggerFactory.getLogger(getClass) + + def createHoodieRecordRdd(df: DataFrame, + config: HoodieWriteConfig, + parameters: Map[String, String], + recordName: String, + recordNameSpace: String, + writerSchema: Schema, + dataFileSchema: Schema, + operation: WriteOperationType, + instantTime: String, + isPrepped: Boolean) = { + val shouldDropPartitionColumns = config.getBoolean(DataSourceWriteOptions.DROP_PARTITION_COLUMNS) + val recordType = config.getRecordMerger.getRecordType + val autoGenerateRecordKeys: Boolean = !parameters.containsKey(KeyGeneratorOptions.RECORDKEY_FIELD_NAME.key()); + + val shouldCombine = if (!isPrepped && WriteOperationType.isInsert(operation)) { + parameters(INSERT_DROP_DUPS.key()).toBoolean || + parameters.getOrElse( + HoodieWriteConfig.COMBINE_BEFORE_INSERT.key(), + HoodieWriteConfig.COMBINE_BEFORE_INSERT.defaultValue() + ).toBoolean + } else if (!isPrepped && WriteOperationType.isUpsert(operation)) { + parameters.getOrElse( + HoodieWriteConfig.COMBINE_BEFORE_UPSERT.key(), + HoodieWriteConfig.COMBINE_BEFORE_UPSERT.defaultValue() + ).toBoolean + } else { + !isPrepped + } + + // NOTE: Avro's [[Schema]] can't be effectively serialized by JVM native serialization framework + // (due to containing cyclic refs), therefore we have to convert it to string before + // passing onto the Executor + val dataFileSchemaStr = dataFileSchema.toString + + log.debug(s"Creating HoodieRecords (as $recordType)") + + recordType match { + case HoodieRecord.HoodieRecordType.AVRO => + // avroRecords will contain meta fields when isPrepped is true. + val avroRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, recordName, recordNameSpace, + Some(writerSchema)) + + avroRecords.mapPartitions(it => { + val sparkPartitionId = TaskContext.getPartitionId() + val keyGenProps = new TypedProperties(config.getProps) + if (autoGenerateRecordKeys) { + keyGenProps.setProperty(KeyGenUtils.RECORD_KEY_GEN_PARTITION_ID_CONFIG, String.valueOf(sparkPartitionId)) + keyGenProps.setProperty(KeyGenUtils.RECORD_KEY_GEN_INSTANT_TIME_CONFIG, instantTime) + } + val keyGenerator : Option[BaseKeyGenerator] = if (isPrepped) None else Some(HoodieSparkKeyGeneratorFactory.createKeyGenerator(keyGenProps).asInstanceOf[BaseKeyGenerator]) + val dataFileSchema = new Schema.Parser().parse(dataFileSchemaStr) + val consistentLogicalTimestampEnabled = parameters.getOrElse( + DataSourceWriteOptions.KEYGENERATOR_CONSISTENT_LOGICAL_TIMESTAMP_ENABLED.key(), + DataSourceWriteOptions.KEYGENERATOR_CONSISTENT_LOGICAL_TIMESTAMP_ENABLED.defaultValue()).toBoolean + + // handle dropping partition columns + var validatePreppedRecord = true + it.map { avroRec => + if (validatePreppedRecord && isPrepped) { + // For prepped records, check the first record to make sure it has meta fields set. + validateMetaFieldsInAvroRecords(avroRec) + // Do validation only once. + validatePreppedRecord = false + } + + val (hoodieKey: HoodieKey, recordLocation: Option[HoodieRecordLocation]) = HoodieCreateRecordUtils.getHoodieKeyAndMaybeLocationFromAvroRecord(keyGenerator, avroRec, + isPrepped) + val avroRecWithoutMeta: GenericRecord = if (isPrepped) { + HoodieAvroUtils.rewriteRecord(avroRec, HoodieAvroUtils.removeMetadataFields(dataFileSchema)) + } else { + avroRec + } + + val processedRecord = if (shouldDropPartitionColumns) { + HoodieAvroUtils.rewriteRecord(avroRecWithoutMeta, dataFileSchema) + } else { + avroRecWithoutMeta + } + + val hoodieRecord = if (shouldCombine) { + val orderingVal = HoodieAvroUtils.getNestedFieldVal(avroRec, config.getString(PRECOMBINE_FIELD), + false, consistentLogicalTimestampEnabled).asInstanceOf[Comparable[_]] + DataSourceUtils.createHoodieRecord(processedRecord, orderingVal, hoodieKey, + config.getString(PAYLOAD_CLASS_NAME), recordLocation) + } else { + DataSourceUtils.createHoodieRecord(processedRecord, hoodieKey, + config.getString(PAYLOAD_CLASS_NAME), recordLocation) + } + hoodieRecord + } + }).toJavaRDD() + + case HoodieRecord.HoodieRecordType.SPARK => + val dataFileSchema = new Schema.Parser().parse(dataFileSchemaStr) + val dataFileStructType = HoodieInternalRowUtils.getCachedSchema(dataFileSchema) + val writerStructType = HoodieInternalRowUtils.getCachedSchema(writerSchema) + val sourceStructType = df.schema + + df.queryExecution.toRdd.mapPartitions { it => + val sparkPartitionId = TaskContext.getPartitionId() + val keyGenProps = new TypedProperties(config.getProps) + if (autoGenerateRecordKeys) { + keyGenProps.setProperty(KeyGenUtils.RECORD_KEY_GEN_PARTITION_ID_CONFIG, String.valueOf(sparkPartitionId)) + keyGenProps.setProperty(KeyGenUtils.RECORD_KEY_GEN_INSTANT_TIME_CONFIG, instantTime) + } + val sparkKeyGenerator : Option[SparkKeyGeneratorInterface] = if (isPrepped) None else Some(HoodieSparkKeyGeneratorFactory.createKeyGenerator(keyGenProps).asInstanceOf[SparkKeyGeneratorInterface]) + val targetStructType = if (shouldDropPartitionColumns) dataFileStructType else writerStructType + val finalStructType = if (isPrepped) { + val fieldsToExclude = HoodieRecord.HOODIE_META_COLUMNS_WITH_OPERATION.toArray() + StructType(targetStructType.fields.filterNot(field => fieldsToExclude.contains(field.name))) + } else { + targetStructType + } + // NOTE: To make sure we properly transform records + val finalStructTypeRowWriter = getCachedUnsafeRowWriter(sourceStructType, finalStructType) + + var validatePreppedRecord = true + it.map { sourceRow => + if (isPrepped) { + // For prepped records, check the record schema to make sure it has meta fields set. + validateMetaFieldsInSparkRecords(sourceStructType) + // Do validation only once. + validatePreppedRecord = false + } + val (key: HoodieKey, recordLocation: Option[HoodieRecordLocation]) = HoodieCreateRecordUtils.getHoodieKeyAndMayBeLocationFromSparkRecord(sparkKeyGenerator, sourceRow, sourceStructType, isPrepped) + + val targetRow = finalStructTypeRowWriter(sourceRow) + var hoodieSparkRecord = new HoodieSparkRecord(key, targetRow, dataFileStructType, false) + if (recordLocation.isDefined) { + hoodieSparkRecord.setCurrentLocation(recordLocation.get) + } + hoodieSparkRecord + } + }.toJavaRDD().asInstanceOf[JavaRDD[HoodieRecord[_]]] + } + } + + private def validateMetaFieldsInSparkRecords(schema: StructType): Boolean = { + if (!schema.fieldNames.contains(HoodieRecord.COMMIT_TIME_METADATA_FIELD) + || !schema.fieldNames.contains(HoodieRecord.COMMIT_SEQNO_METADATA_FIELD) + || !schema.fieldNames.contains(HoodieRecord.RECORD_KEY_METADATA_FIELD) + || !schema.fieldNames.contains(HoodieRecord.PARTITION_PATH_METADATA_FIELD) + || !schema.fieldNames.contains(HoodieRecord.FILENAME_METADATA_FIELD)) { + throw new HoodieException("Metadata fields missing from spark prepared record.") + } + true + } + + private def validateMetaFieldsInAvroRecords(avroRec: GenericRecord): Unit = { + val avroSchema = avroRec.getSchema; + if (avroSchema.getField(HoodieRecord.RECORD_KEY_METADATA_FIELD) == null + || avroSchema.getField(HoodieRecord.COMMIT_TIME_METADATA_FIELD) == null + || avroSchema.getField(HoodieRecord.COMMIT_SEQNO_METADATA_FIELD) == null + || avroSchema.getField(HoodieRecord.PARTITION_PATH_METADATA_FIELD) == null + || avroSchema.getField(HoodieRecord.FILENAME_METADATA_FIELD) == null) { + throw new HoodieException("Metadata fields missing from avro prepared record.") + } + } + + def getHoodieKeyAndMaybeLocationFromAvroRecord(keyGenerator: Option[BaseKeyGenerator], avroRec: GenericRecord, + isPrepped: Boolean): (HoodieKey, Option[HoodieRecordLocation]) = { + val recordKey = if (isPrepped) { + avroRec.get(HoodieRecord.RECORD_KEY_METADATA_FIELD).toString + } else { + keyGenerator.get.getRecordKey(avroRec) + }; + + val partitionPath = if (isPrepped) { + avroRec.get(HoodieRecord.PARTITION_PATH_METADATA_FIELD).toString + } else { + keyGenerator.get.getPartitionPath(avroRec) + }; + + val hoodieKey = new HoodieKey(recordKey, partitionPath) + val instantTime: Option[String] = if (isPrepped) { + Option(avroRec.get(HoodieRecord.COMMIT_TIME_METADATA_FIELD)).map(_.toString) + } + else { + None + } + val fileName: Option[String] = if (isPrepped) { + Option(avroRec.get(HoodieRecord.FILENAME_METADATA_FIELD)).map(_.toString) + } + else { + None + } + val recordLocation: Option[HoodieRecordLocation] = if (instantTime.isDefined && fileName.isDefined) { + val fileId = FSUtils.getFileId(fileName.get) + Some(new HoodieRecordLocation(instantTime.get, fileId)) + } else { + None + } + (hoodieKey, recordLocation) + } + + def getHoodieKeyAndMayBeLocationFromSparkRecord(sparkKeyGenerator: Option[SparkKeyGeneratorInterface], + sourceRow: InternalRow, schema: StructType, + isPrepped: Boolean): (HoodieKey, Option[HoodieRecordLocation]) = { + val recordKey = if (isPrepped) { + sourceRow.getString(HOODIE_META_COLUMNS_NAME_TO_POS.get(HoodieRecord.RECORD_KEY_METADATA_FIELD)); + } else { + sparkKeyGenerator.get.getRecordKey(sourceRow, schema).toString + } + + val partitionPath = if (isPrepped) { + sourceRow.getString(HOODIE_META_COLUMNS_NAME_TO_POS.get(HoodieRecord.PARTITION_PATH_METADATA_FIELD)) + } else { + sparkKeyGenerator.get.getPartitionPath(sourceRow, schema).toString + }; + + val instantTime: Option[String] = if (isPrepped) { + Option(sourceRow.getString(HOODIE_META_COLUMNS_NAME_TO_POS.get(HoodieRecord.COMMIT_TIME_METADATA_FIELD))) Review Comment: its better to keep the behavior consistent. we can use FSUtils.getCommitTime(String fileName) to fetch instant time and use that instead of commit time meta field. this will be in line w/ how Simple And Bloom index works as of today. -- This is an automated message from the Apache Git Service. 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