sunchao commented on a change in pull request #34659: URL: https://github.com/apache/spark/pull/34659#discussion_r839080186
########## File path: sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/ParquetColumnVector.java ########## @@ -0,0 +1,379 @@ +/* + * 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.spark.sql.execution.datasources.parquet; + +import java.util.ArrayList; +import java.util.List; +import java.util.Set; + +import com.google.common.base.Preconditions; +import org.apache.spark.memory.MemoryMode; +import org.apache.spark.sql.execution.vectorized.OffHeapColumnVector; +import org.apache.spark.sql.execution.vectorized.OnHeapColumnVector; +import org.apache.spark.sql.execution.vectorized.WritableColumnVector; +import org.apache.spark.sql.types.ArrayType; +import org.apache.spark.sql.types.DataType; +import org.apache.spark.sql.types.DataTypes; +import org.apache.spark.sql.types.MapType; +import org.apache.spark.sql.types.StructType; + +/** + * Contains necessary information representing a Parquet column, either of primitive or nested type. + */ +final class ParquetColumnVector { + private final ParquetColumn column; + private final List<ParquetColumnVector> children; + private final WritableColumnVector vector; + + /** + * Repetition & Definition levels + * These are allocated only for leaf columns; for non-leaf columns, they simply maintain + * references to that of the former. + */ + private WritableColumnVector repetitionLevels; + private WritableColumnVector definitionLevels; + + /** Whether this column is primitive (i.e., leaf column) */ + private final boolean isPrimitive; + + /** Reader for this column - only set if 'isPrimitive' is true */ + private VectorizedColumnReader columnReader; + + ParquetColumnVector( + ParquetColumn column, + WritableColumnVector vector, + int capacity, + MemoryMode memoryMode, + Set<ParquetColumn> missingColumns) { + + DataType sparkType = column.sparkType(); + if (!sparkType.sameType(vector.dataType())) { + throw new IllegalArgumentException("Spark type: " + sparkType + + " doesn't match the type: " + vector.dataType() + " in column vector"); + } + + this.column = column; + this.vector = vector; + this.children = new ArrayList<>(); + this.isPrimitive = column.isPrimitive(); + + if (missingColumns.contains(column)) { + vector.setAllNull(); + return; + } + + if (isPrimitive) { + // TODO: avoid allocating these if not necessary, for instance, the node is of top-level + // and is not repeated, or the node is not top-level but its max repetition level is 0. + repetitionLevels = allocateLevelsVector(capacity, memoryMode); + definitionLevels = allocateLevelsVector(capacity, memoryMode); + } else { + Preconditions.checkArgument(column.children().size() == vector.getNumChildren()); + for (int i = 0; i < column.children().size(); i++) { + ParquetColumnVector childCv = new ParquetColumnVector(column.children().apply(i), + vector.getChild(i), capacity, memoryMode, missingColumns); + children.add(childCv); + + // Only use levels from non-missing child, this can happen if only some but not all + // fields of a struct are missing. + if (!childCv.vector.isAllNull()) { + this.repetitionLevels = childCv.repetitionLevels; + this.definitionLevels = childCv.definitionLevels; + } + } + + // This can happen if all the fields of a struct are missing, in which case we should mark + // the struct itself as a missing column + if (repetitionLevels == null) { + vector.setAllNull(); + } + } + } + + /** + * Returns all the children of this column. + */ + List<ParquetColumnVector> getChildren() { + return children; + } + + /** + * Returns all the leaf columns in depth-first order. + */ + List<ParquetColumnVector> getLeaves() { + List<ParquetColumnVector> result = new ArrayList<>(); + getLeavesHelper(this, result); + return result; + } + + private static void getLeavesHelper(ParquetColumnVector vector, List<ParquetColumnVector> coll) { + if (vector.isPrimitive) { + coll.add(vector); + } else { + for (ParquetColumnVector child : vector.children) { + getLeavesHelper(child, coll); + } + } + } + + /** + * Assembles this column and calculate collection offsets recursively. + * This is a no-op for primitive columns. + */ + void assemble() { + // nothing to do if the column itself is missing + if (vector.isAllNull()) return; + + DataType type = column.sparkType(); + if (type instanceof ArrayType || type instanceof MapType) { + for (ParquetColumnVector child : children) { + child.assemble(); + } + calculateCollectionOffsets(); + } else if (type instanceof StructType) { + for (ParquetColumnVector child : children) { + child.assemble(); + } + calculateStructOffsets(); + } + } + + /** + * Resets this Parquet column vector, which includes resetting all the writable column vectors + * (used to store values, definition levels, and repetition levels) for this and all its children. + */ + void reset() { + // nothing to do if the column itself is missing + if (vector.isAllNull()) return; + + vector.reset(); + repetitionLevels.reset(); + definitionLevels.reset(); + for (ParquetColumnVector child : children) { + child.reset(); + } + } + + /** + * Returns the {@link ParquetColumn} of this column vector. + */ + ParquetColumn getColumn() { + return this.column; + } + + /** + * Returns the writable column vector used to store values. + */ + WritableColumnVector getValueVector() { + return this.vector; + } + + /** + * Returns the writable column vector used to store repetition levels. + */ + WritableColumnVector getRepetitionLevelVector() { + return this.repetitionLevels; + } + + /** + * Returns the writable column vector used to store definition levels. + */ + WritableColumnVector getDefinitionLevelVector() { + return this.definitionLevels; + } + + /** + * Returns the column reader for reading a Parquet column. + */ + VectorizedColumnReader getColumnReader() { + return this.columnReader; + } + + /** + * Sets the column vector to 'reader'. Note this can only be called on a primitive Parquet + * column. + */ + void setColumnReader(VectorizedColumnReader reader) { + if (!isPrimitive) { + throw new IllegalStateException("Can't set reader for non-primitive column"); + } + this.columnReader = reader; + } + + private void calculateCollectionOffsets() { + int maxDefinitionLevel = column.definitionLevel(); + int maxElementRepetitionLevel = column.repetitionLevel(); + + ParquetColumn child = column.children().apply(0); + int maxElementDefinitionLevel = child.definitionLevel(); + if (!child.required()) maxElementDefinitionLevel -= 1; + + // There are 4 cases when calculating definition levels: + // 1. definitionLevel == maxDefinitionLevel + // ==> value is defined and not null + // 2. definitionLevel == maxDefinitionLevel - 1 + // ==> value is null + // 3. definitionLevel < maxDefinitionLevel - 1 + // ==> value doesn't exist since one of its optional parents is null + // 4. definitionLevel > maxDefinitionLevel + // ==> value is a nested element within an array or map + // + // `i` is the index over all leaf elements of this array, while `offset` is the index over + // all top-level elements of this array. + int rowId = 0; + for (int i = 0, offset = 0; i < definitionLevels.getElementsAppended(); + i = getNextCollectionStart(maxElementRepetitionLevel, i)) { + vector.reserve(rowId + 1); + int definitionLevel = definitionLevels.getInt(i); + if (definitionLevel < maxElementDefinitionLevel) { + // This means the collection is null, and it is not an array element. In this case, we + // should increase offset to skip it when returning an array starting from the offset. + // + // For instance, considering an array of strings with 2 elements like the following: + // null, [a, b, c] + // the child array (which is of String type) in this case will be: + // null: 1 0 0 0 + // length: 0 1 1 1 + // offset: 0 0 1 2 + // and the array itself will be: + // null: 1 0 + // length: 0 3 + // offset: 0 1 + // + // It's important that for the second element `[a, b, c]`, the offset starts from 1 + // since otherwise we'd include the first null element from child array in the result. + offset += 1; + } + if (definitionLevel <= maxDefinitionLevel - 1) { + // Collection is null or one of its optional parents is null + vector.putNull(rowId++); + } else if (definitionLevel == maxDefinitionLevel) { + // Collection is defined but empty + vector.putNotNull(rowId); + vector.putArray(rowId, offset, 0); + rowId++; + } else if (definitionLevel > maxDefinitionLevel) { + // Collection is defined and non-empty: find out how many top elements are there until the + // start of the next array. + vector.putNotNull(rowId); + int length = getCollectionSize(maxElementRepetitionLevel, i); + vector.putArray(rowId, offset, length); + offset += length; + rowId++; + } + } + vector.addElementsAppended(rowId); + } + + private void calculateStructOffsets() { Review comment: 👍 Let me change it to `assembleStruct` -- This is an automated message from the Apache Git Service. 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