.. 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. ================================= Upgrading from PySpark 1.4 to 1.5 ================================= * Resolution of strings to columns in Python now supports using dots (.) to qualify the column or access nested values. For example ``df['table.column.nestedField']``. However, this means that if your column name contains any dots you must now escape them using backticks (e.g., ``table.`column.with.dots`.nested``). * DataFrame.withColumn method in PySpark supports adding a new column or replacing existing columns of the same name.