YannByron commented on a change in pull request #4709: URL: https://github.com/apache/hudi/pull/4709#discussion_r802549605
########## File path: hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieDataSourceHelper.scala ########## @@ -0,0 +1,175 @@ +/* + * 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.hadoop.fs.FileStatus + +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.{Expression, PredicateHelper, SpecificInternalRow, SubqueryExpression, UnsafeProjection} +import org.apache.spark.sql.execution.datasources.{FilePartition, PartitionedFile} +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.vectorized.ColumnarBatch + +import scala.collection.JavaConverters._ +import scala.collection.mutable.ArrayBuffer + +object HoodieDataSourceHelper extends PredicateHelper { + + /** + * Partition the given condition into two sequence of conjunctive predicates: + * - predicates that can be evaluated using metadata only. + * - other predicates. + */ + def splitPartitionAndDataPredicates( + condition: Expression, + partitionColumns: Seq[String], + spark: SparkSession): (Seq[Expression], Seq[Expression]) = { + splitConjunctivePredicates(condition).partition( + isPredicateMetadataOnly(_, partitionColumns, spark)) + } + + /** + * Check if condition can be evaluated using only metadata. In Delta, this means the condition + * only references partition columns and involves no subquery. + */ + def isPredicateMetadataOnly( + condition: Expression, + partitionColumns: Seq[String], + spark: SparkSession): Boolean = { + isPredicatePartitionColumnsOnly(condition, partitionColumns, spark) && + !containsSubquery(condition) + } + + /** + * Does the predicate only contains partition columns? + */ + def isPredicatePartitionColumnsOnly( + condition: Expression, + partitionColumns: Seq[String], + spark: SparkSession): Boolean = { + val nameEquality = spark.sessionState.analyzer.resolver + condition.references.forall { r => + partitionColumns.exists(nameEquality(r.name, _)) + } + } + + /** + * Check if condition involves a subquery expression. + */ + def containsSubquery(condition: Expression): Boolean = { + SubqueryExpression.hasSubquery(condition) + } + + /** + * Wrapper `readFunction` to deal with [[ColumnarBatch]] when enable parquet vectorized reader. + */ + def readParquetFile( + file: PartitionedFile, + readFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = { + val fileIterator = readFunction(file) + val rows = fileIterator.flatMap(_ match { + case r: InternalRow => Seq(r) + case b: ColumnarBatch => b.rowIterator().asScala + }) + rows + } + + /** + * Extract the required schema from [[InternalRow]] + */ + def extractRequiredSchema( + iter: Iterator[InternalRow], + requiredSchema: StructType, + requiredFieldPos: Seq[Int]): Iterator[InternalRow] = { + val unsafeProjection = UnsafeProjection.create(requiredSchema) + val rows = iter.map { row => + unsafeProjection(createInternalRowWithSchema(row, requiredSchema, requiredFieldPos)) + } + rows + } + + /** + * Convert [[InternalRow]] to [[SpecificInternalRow]]. + */ + def createInternalRowWithSchema( + row: InternalRow, + schema: StructType, + positions: Seq[Int]): InternalRow = { + val rowToReturn = new SpecificInternalRow(schema) + var curIndex = 0 + schema.zip(positions).foreach { case (field, pos) => + val curField = if (row.isNullAt(pos)) { + null + } else { + row.get(pos, field.dataType) + } + rowToReturn.update(curIndex, curField) + curIndex += 1 + } + rowToReturn + } + + + def splitFiles( + sparkSession: SparkSession, + file: FileStatus, + partitionValues: InternalRow): Seq[PartitionedFile] = { + val filePath = file.getPath + val maxSplitBytes = sparkSession.sessionState.conf.filesMaxPartitionBytes + (0L until file.getLen by maxSplitBytes).map { offset => + val remaining = file.getLen - offset + val size = if (remaining > maxSplitBytes) maxSplitBytes else remaining + PartitionedFile(partitionValues, filePath.toUri.toString, offset, size) + } + } + + def getFilePartitions( Review comment: only spark3 has this method, spark2.x not. -- This is an automated message from the Apache Git Service. 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