rdblue commented on a change in pull request #24117: [SPARK-27181][SQL]: Add public transform API URL: https://github.com/apache/spark/pull/24117#discussion_r271392079
########## File path: sql/catalyst/src/main/java/org/apache/spark/sql/catalog/v2/expressions/Expressions.java ########## @@ -0,0 +1,141 @@ +/* + * 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.catalog.v2.expressions; + +import org.apache.spark.annotation.Experimental; + +/** + * Helper methods to create logical transforms to pass into Spark. + */ +@Experimental +public class Expressions { + private Expressions() { + } + + /** + * Create a logical transform for applying a named transform. + * <p> + * This transform can represent applying any named transform. + * + * @param name the transform name + * @param args expression arguments to the transform + * @return a logical transform + */ + public Transform apply(String name, Expression... args) { + return LogicalExpressions.apply(name, args); + } + + /** + * Create a named reference expression for a column. + * + * @param name a column name + * @return a named reference for the column + */ + public NamedReference column(String name) { + return LogicalExpressions.reference(name); + } + + /** + * Create a literal from a value. + * + * @param value a value + * @param <T> the JVM type of the value + * @return a literal expression for the value + */ + public <T> Literal<T> literal(T value) { + return LogicalExpressions.literal(value); + } + + /** + * Create a bucket transform for one or more columns. + * <p> + * This transform represents a logical mapping from a value to a bucket id in [0, numBuckets) + * based on a hash of the value. + * + * @param numBuckets the number of output buckets + * @param columns input columns for the bucket transform + * @return a logical bucket transform + */ + public Transform bucket(int numBuckets, String... columns) { + return LogicalExpressions.bucket(numBuckets, columns); + } + + /** + * Create an identity transform for a column. + * <p> + * This transform represents a logical mapping from a value to itself. + * + * @param column an input column + * @return a logical identity transform + */ + public Transform identity(String column) { + return LogicalExpressions.identity(column); + } + + /** + * Create a year transform for a timestamp or date column. + * <p> + * This transform represents a logical mapping from a timestamp or date to a year, such as 2018. + * + * @param column an input timestamp or date column + * @return a logical year transform + */ + public Transform year(String column) { + return LogicalExpressions.year(column); + } + + /** + * Create a month transform for a timestamp or date column. + * <p> + * This transform represents a logical mapping from a timestamp or date to a month, such as + * 2018-05. + * + * @param column an input timestamp or date column + * @return a logical month transform + */ + public Transform month(String column) { + return LogicalExpressions.month(column); + } + + /** + * Create a date transform for a timestamp or date column. + * <p> + * This transform represents a logical mapping from a timestamp or date to a date, such as + * 2018-05-13. + * + * @param column an input timestamp or date column + * @return a logical date transform + */ + public Transform date(String column) { Review comment: I should also note the suggestion I made above for using transforms to pass data back to Spark. I think we should pass back `builtin.date` as the transform so that Spark knows the date is in its internal format. ---------------------------------------------------------------- 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: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
