szehon-ho commented on code in PR #58632: URL: https://github.com/apache/spark/pull/58632#discussion_r4032546661
########## sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/SchemaAlignmentConfig.java: ########## @@ -0,0 +1,53 @@ +/* + * 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.connector.catalog; + +import org.apache.spark.annotation.Evolving; + +/** + * Schema-alignment configuration for batch/row-level writes to a {@link Table}. This allows + * connectors to configure casting behavior and handling of schema mismatches during DSv2 writes. + * It is not consulted for streaming writes, which do not go through this alignment path. Review Comment: I was actually wondering if there is a plan to go through in future myself ########## sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/SchemaAlignmentConfig.java: ########## @@ -0,0 +1,53 @@ +/* + * 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.connector.catalog; + +import org.apache.spark.annotation.Evolving; + +/** + * Schema-alignment configuration for batch/row-level writes to a {@link Table}. This allows + * connectors to configure casting behavior and handling of schema mismatches during DSv2 writes. + * It is not consulted for streaming writes, which do not go through this alignment path. + * + * @since 4.4.0 + */ +@Evolving +public interface SchemaAlignmentConfig { Review Comment: Why is it Intefface, should just be a class if its just two booleans? Also (optional) we could make a trait SupportsSchemaAlignmentConfig extend Table and have the two methods there to follow the other example , to make Table clean? Most connector I assume implement Table and dont want to overwhelm the first time connector authors Related suggestion, make it internal like SupportsPushdownCatalystFilter as it exposes some Spark internal (LEGACY) ########## sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/SchemaAlignmentConfig.java: ########## @@ -0,0 +1,53 @@ +/* + * 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.connector.catalog; + +import org.apache.spark.annotation.Evolving; + +/** + * Schema-alignment configuration for batch/row-level writes to a {@link Table}. This allows + * connectors to configure casting behavior and handling of schema mismatches during DSv2 writes. + * It is not consulted for streaming writes, which do not go through this alignment path. + * + * @since 4.4.0 + */ +@Evolving +public interface SchemaAlignmentConfig { + + /** The strict data source v2 configuration, returned by {@link Table} by default. */ + SchemaAlignmentConfig DEFAULT = new SchemaAlignmentConfig() {}; + + /** + * Whether {@code spark.sql.storeAssignmentPolicy=LEGACY} is allowed for writes and row-level + * operations targeting this table. Data source v2 rejects LEGACY by default; a table can decide + * to opt-out from this restriction. + */ + default boolean allowLegacyStoreAssignmentPolicy() { + return false; + } + + /** + * Whether the {@code ANSI} store-assignment cast check is deferred from analysis to runtime under + * {@code spark.sql.storeAssignmentPolicy=ANSI}. When {@code true}, the analyzer skips the + * store-assignment compatibility check and inserts an ANSI cast, so malformed values or + * overflows surface at execution time. + */ + default boolean deferAnsiCastValidationToRuntime() { Review Comment: actually this is a bit confusing. allowLegacyStoreAssignmentPolicy is only active if user set LEGACY deferAnsiCastValidationToRuntime is only active if user set ANSI and control a behavior in ANSI wondering if there is a cleaner way. Maybe a boolean or TableCapability for the first, and an explicit enum like "AnsiAssignmentMode" for the second -- 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. 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