sunchao commented on a change in pull request #34298: URL: https://github.com/apache/spark/pull/34298#discussion_r737894051
########## File path: sql/core/src/main/java/org/apache/spark/sql/execution/datasources/orc/OrcColumnStatistics.java ########## @@ -0,0 +1,80 @@ +/* + * 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.orc; + +import org.apache.orc.ColumnStatistics; + +import java.util.ArrayList; +import java.util.List; + +/** + * Columns statistics interface wrapping ORC {@link ColumnStatistics}s. + * + * Because ORC {@link ColumnStatistics}s are stored as an flatten array in ORC file footer, + * this class is used to covert ORC {@link ColumnStatistics}s from array to nested tree structure, + * according to data types. The flatten array stores all data types (including nested types) in + * tree pre-ordering. This is used for aggregate push down in ORC. + * + * For nested data types (array, map and struct), the sub-field statistics are stored recursively + * inside parent column's `children` field. Here is an example of `OrcColumnStatistics`: + * + * Data schema: + * c1: int + * c2: struct<f1: int, f2: float> + * c3: map<key: int, value: string> + * c4: array<int> + * + * OrcColumnStatistics Review comment: 👍 ########## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcUtils.scala ########## @@ -377,4 +381,106 @@ object OrcUtils extends Logging { case _ => false } } + + /** + * When the partial aggregates (Max/Min/Count) are pushed down to ORC, we don't need to read data + * from ORC and aggregate at Spark layer. Instead we want to get the partial aggregates + * (Max/Min/Count) result using the statistics information from ORC file footer, and then + * construct an InternalRow from these aggregate results. + * + * @return Aggregate results in the format of InternalRow + */ + def createAggInternalRowFromFooter( + reader: Reader, + dataSchema: StructType, + partitionSchema: StructType, + aggregation: Aggregation, + aggSchema: StructType, + isCaseSensitive: Boolean): InternalRow = { + require(aggregation.groupByColumns.length == 0, + s"aggregate $aggregation with group-by column shouldn't be pushed down") + val columnsStatistics = OrcFooterReader.readStatistics(reader) Review comment: I'm just curious, since from https://github.com/apache/orc/blob/main/proto/orc_proto.proto, min/max are optional fields, and ORC's `[ColumnStatisticsImpl](https://github.com/apache/orc/blob/main/java/core/src/java/org/apache/orc/impl/ColumnStatisticsImpl.java#L337)` also doesn't set `minimum` or `maximum` if the fields from protobuf are not defined. -- 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. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
