xiarixiaoyao commented on a change in pull request #2651: URL: https://github.com/apache/hudi/pull/2651#discussion_r600990095
########## File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieFileIndex.scala ########## @@ -0,0 +1,349 @@ +/* + * 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 java.util.Properties + +import scala.collection.JavaConverters._ +import org.apache.hadoop.fs.{FileStatus, Path} +import org.apache.hudi.client.common.HoodieSparkEngineContext +import org.apache.hudi.common.config.{HoodieMetadataConfig, SerializableConfiguration} +import org.apache.hudi.common.engine.HoodieLocalEngineContext +import org.apache.hudi.common.fs.FSUtils +import org.apache.hudi.common.model.HoodieBaseFile +import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver} +import org.apache.hudi.common.table.view.HoodieTableFileSystemView +import org.apache.hudi.config.HoodieWriteConfig +import org.apache.spark.api.java.JavaSparkContext +import org.apache.spark.internal.Logging +import org.apache.spark.sql.catalyst.{InternalRow, expressions} +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.avro.SchemaConverters +import org.apache.spark.sql.catalyst.expressions.{AttributeReference, BoundReference, Expression, InterpretedPredicate} +import org.apache.spark.sql.catalyst.util.{CaseInsensitiveMap, DateTimeUtils} +import org.apache.spark.sql.execution.datasources.{FileIndex, FileStatusCache, NoopCache, PartitionDirectory, PartitionUtils} +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.types.StructType +import org.apache.spark.unsafe.types.UTF8String + +import scala.collection.mutable + +/** + * A File Index which support partition prune for hoodie snapshot and read-optimized + * query. + * Main steps to get the file list for query: + * 1、Load all files and partition values from the table path. + * 2、Do the partition prune by the partition filter condition. + * + * There are 3 cases for this: + * 1、If the partition columns size is equal to the actually partition path level, we + * read it as partitioned table.(e.g partition column is "dt", the partition path is "2021-03-10") + * + * 2、If the partition columns size is not equal to the partition path level, but the partition + * column size is "1" (e.g. partition column is "dt", but the partition path is "2021/03/10" + * who'es directory level is 3).We can still read it as a partitioned table. We will mapping the + * partition path (e.g. 2021/03/10) to the only partition column (e.g. "dt"). + * + * 3、Else the the partition columns size is not equal to the partition directory level and the + * size is great than "1" (e.g. partition column is "dt,hh", the partition path is "2021/03/10/12") + * , we read it as a None Partitioned table because we cannot know how to mapping the partition + * path with the partition columns in this case. + */ +case class HoodieFileIndex( + spark: SparkSession, + metaClient: HoodieTableMetaClient, + schemaSpec: Option[StructType], + options: Map[String, String], + @transient fileStatusCache: FileStatusCache = NoopCache) + extends FileIndex with Logging { + + private val basePath = metaClient.getBasePath + + @transient private val queryPath = new Path(options.getOrElse("path", "'path' option required")) + /** + * Get the schema of the table. + */ + lazy val schema: StructType = schemaSpec.getOrElse({ + val schemaUtil = new TableSchemaResolver(metaClient) + SchemaConverters.toSqlType(schemaUtil.getTableAvroSchema) + .dataType.asInstanceOf[StructType] + }) + + /** + * Get the partition schema from the hoodie.properties. + */ + private lazy val _partitionSchemaFromProperties: StructType = { + val tableConfig = metaClient.getTableConfig + val partitionColumns = tableConfig.getPartitionColumns + val nameFieldMap = schema.fields.map(filed => filed.name -> filed).toMap + + if (partitionColumns.isPresent) { + val partitionFields = partitionColumns.get().map(column => + nameFieldMap.getOrElse(column, throw new IllegalArgumentException(s"Cannot find column: '" + + s"$column' in the schema[${schema.fields.mkString(",")}]"))) + new StructType(partitionFields) + } else { // If the partition columns have not stored in hoodie.properites(the table that was + // created earlier), we trait it as a none-partitioned table. + new StructType() + } + } + + @transient @volatile private var fileSystemView: HoodieTableFileSystemView = _ + @transient @volatile private var cachedAllInputFiles: Array[HoodieBaseFile] = _ + @transient @volatile private var cachedFileSize: Long = 0L + @transient @volatile private var cachedAllPartitionPaths: Seq[PartitionRowPath] = _ + + @volatile private var queryAsNonePartitionedTable: Boolean = _ + + refresh0() + + override def rootPaths: Seq[Path] = queryPath :: Nil + + override def listFiles(partitionFilters: Seq[Expression], + dataFilters: Seq[Expression]): Seq[PartitionDirectory] = { + if (queryAsNonePartitionedTable) { // Read as None Partitioned table. + Seq(PartitionDirectory(InternalRow.empty, allFiles)) + } else { + // Prune the partition path by the partition filters + val prunedPartitions = prunePartition(cachedAllPartitionPaths, partitionFilters) + prunedPartitions.map { partition => + val fileStatues = fileSystemView.getLatestBaseFiles(partition.partitionPath).iterator() + .asScala.toSeq + .map(_.getFileStatus) + PartitionDirectory(partition.values, fileStatues) + } + } + } + + override def inputFiles: Array[String] = { + cachedAllInputFiles.map(_.getFileStatus.getPath.toString) + } + + override def refresh(): Unit = { + fileStatusCache.invalidateAll() + refresh0() + } + + private def refresh0(): Unit = { + val startTime = System.currentTimeMillis() + val partitionFiles = loadPartitionPathFiles() + val allFiles = partitionFiles.values.reduceOption(_ ++ _) + .getOrElse(Array.empty[FileStatus]) + + metaClient.reloadActiveTimeline() + val activeInstants = metaClient.getActiveTimeline.getCommitsTimeline.filterCompletedInstants + fileSystemView = new HoodieTableFileSystemView(metaClient, activeInstants, allFiles) + cachedAllInputFiles = fileSystemView.getLatestBaseFiles.iterator().asScala.toArray + cachedAllPartitionPaths = partitionFiles.keys.toSeq + cachedFileSize = cachedAllInputFiles.map(_.getFileLen).sum + + // If the partition value contains InternalRow.empty, we query it as a none partitioned table. + queryAsNonePartitionedTable = cachedAllPartitionPaths + .exists(p => p.values == InternalRow.empty) + val flushSpend = System.currentTimeMillis() - startTime + logInfo(s"Refresh for table ${metaClient.getTableConfig.getTableName}," + + s" spend: $flushSpend ms") + } + + override def sizeInBytes: Long = { + cachedFileSize + } + + override def partitionSchema: StructType = { + if (queryAsNonePartitionedTable) { + // If we read it as None Partitioned table, we should not + // return the partition schema. + new StructType() + } else { + _partitionSchemaFromProperties + } + } + + /** + * Get the data schema of the table. + * @return + */ + def dataSchema: StructType = { + val partitionColumns = partitionSchema.fields.map(_.name).toSet + StructType(schema.fields.filterNot(f => partitionColumns.contains(f.name))) + } + + def allFiles: Seq[FileStatus] = cachedAllInputFiles.map(_.getFileStatus) + + private def prunePartition(partitionPaths: Seq[PartitionRowPath], + predicates: Seq[Expression]): Seq[PartitionRowPath] = { + + val partitionColumnNames = partitionSchema.fields.map(_.name).toSet + val partitionPruningPredicates = predicates.filter { + _.references.map(_.name).toSet.subsetOf(partitionColumnNames) + } + if (partitionPruningPredicates.nonEmpty) { + val predicate = partitionPruningPredicates.reduce(expressions.And) + + val boundPredicate = InterpretedPredicate.create(predicate.transform { Review comment: good job。 but this code is incompatible with spark3 。 InterpretedPredicate is restructure in spark3.0， we can use Predicate.createInterpreted in spark3.0 -- This is an automated message from the Apache Git Service. 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