rdblue commented on code in PR #5872: URL: https://github.com/apache/iceberg/pull/5872#discussion_r990821451
########## spark/v3.3/spark/src/main/java/org/apache/iceberg/spark/source/SparkPushedDownAggregateUtil.java: ########## @@ -0,0 +1,376 @@ +/* + * 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.iceberg.spark.source; + +import java.math.BigDecimal; +import java.nio.ByteBuffer; +import java.util.List; +import java.util.Locale; +import java.util.Map; +import org.apache.iceberg.MetadataTableType; +import org.apache.iceberg.Schema; +import org.apache.iceberg.Table; +import org.apache.iceberg.expressions.Expression; +import org.apache.iceberg.expressions.Literal; +import org.apache.iceberg.expressions.UnboundAggregate; +import org.apache.iceberg.relocated.com.google.common.collect.Lists; +import org.apache.iceberg.spark.SparkSchemaUtil; +import org.apache.iceberg.spark.SparkTableUtil; +import org.apache.iceberg.types.Conversions; +import org.apache.iceberg.types.Type; +import org.apache.iceberg.types.Types; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.SparkSession; +import org.apache.spark.sql.catalyst.InternalRow; +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.Decimal; +import org.apache.spark.sql.types.DecimalType; +import org.apache.spark.sql.types.MapType; +import org.apache.spark.sql.types.Metadata; +import org.apache.spark.sql.types.StructField; +import org.apache.spark.sql.types.StructType; +import scala.collection.JavaConverters; + +/** Helper methods for working with Spark aggregate push down. */ +public class SparkPushedDownAggregateUtil { + + private SparkPushedDownAggregateUtil() {} + + // Build schema for pushed down aggregates. This schema will be used as the scan schema. + public static StructType buildSchemaForPushedDownAggregate( + List<Expression> aggregates, boolean caseSensitive, Schema schema) { + StructType finalSchema = new StructType(); + for (int index = 0; index < aggregates.size(); index++) { + if ((aggregates.get(index)).op().name().equals("COUNTSTAR")) { + StructField field = + new StructField("COUNT(*)", DataTypes.LongType, false, Metadata.empty()); + finalSchema = finalSchema.add(field); + } else { + String colName = ((UnboundAggregate) aggregates.get(index)).ref().name(); + DataType dataType = getDataTypeForAggregateColumn(colName, caseSensitive, schema); + if (dataType instanceof StructType + || dataType instanceof ArrayType + || dataType instanceof MapType) { + // not building pushed down aggregate schema for complex types to disable aggregate push + // down because the statistic info for complex are not available. + return finalSchema; + } + if ((aggregates.get(index)).op().name().equals("COUNT")) { + StructField field = + new StructField( + "COUNT(" + colName + ")", DataTypes.LongType, false, Metadata.empty()); + finalSchema = finalSchema.add(field); + } else if ((aggregates.get(index)).op().name().equals("MAX")) { + StructField field = + new StructField("MAX(" + colName + ")", dataType, false, Metadata.empty()); + finalSchema = finalSchema.add(field); + } else if ((aggregates.get(index)).op().name().equals("MIN")) { + StructField field = + new StructField("MIN(" + colName + ")", dataType, false, Metadata.empty()); + finalSchema = finalSchema.add(field); + } + } + } + return finalSchema; Review Comment: I think that this should be done in Iceberg code rather than in Spark code. This can produce an Iceberg schema and the convert it. That would allow us to more easily reuse this for other engines. -- 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]
