pengzhiwei2018 commented on a change in pull request #2651: URL: https://github.com/apache/hudi/pull/2651#discussion_r593550517
########## File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieFileIndex.scala ########## @@ -0,0 +1,273 @@ +/* + * 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.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, PartitionDirectory, PartitionUtils} +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.types.StructType + +/** + * 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. + * + * Note: + * Only when the URL_ENCODE_PARTITIONING_OPT_KEY is enable, we can store the partition columns + * to the hoodie.properties in HoodieSqlWriter when write table. So that the query can benefit + * from the partition prune. + */ +case class HoodieFileIndex( + spark: SparkSession, + basePath: String, + schemaSpec: Option[StructType], + options: Map[String, String]) + extends FileIndex with Logging { + + @transient private val hadoopConf = spark.sessionState.newHadoopConf() + private lazy val metaClient = HoodieTableMetaClient + .builder().setConf(hadoopConf).setBasePath(basePath).build() + + @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. + */ + private lazy val _partitionSchema: StructType = { + val tableConfig = metaClient.getTableConfig + val partitionColumns = tableConfig.getPartitionColumns + val nameFieldMap = schema.fields.map(filed => filed.name -> filed).toMap + // If the URL_ENCODE_PARTITIONING_OPT_KEY has enable, the partition schema will stored in + // hoodie.properties, So we can benefit from the partition prune. + 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 URL_ENCODE_PARTITIONING_OPT_KEY is disable, 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[PartitionPath] = _ + + refresh() + + override def rootPaths: Seq[Path] = queryPath :: Nil + + override def listFiles(partitionFilters: Seq[Expression], + dataFilters: Seq[Expression]): Seq[PartitionDirectory] = { + if (partitionSchema.fields.isEmpty) { // None partition 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 = { + 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 + + 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 = _partitionSchema + + /** + * 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[PartitionPath], + predicates: Seq[Expression]): Seq[PartitionPath] = { + + 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) + Review comment: Yes, I can work well for different operators. And this code refers to the [PartitioningAwareFileIndex#prunePartitions`](https://github.com/apache/spark/blob/branch-2.4/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningAwareFileIndex.scala). I also have a test for this in `TestHoodieFileIndex#testPartitionPrune`. ---------------------------------------------------------------- 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. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
