rdblue commented on a change in pull request #23606: [SPARK-26666][SQL] Support 
DSv2 overwrite and dynamic partition overwrite.
URL: https://github.com/apache/spark/pull/23606#discussion_r250025352
 
 

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 File path: 
sql/core/src/main/java/org/apache/spark/sql/sources/v2/writer/SupportsOverwrite.java
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+/*
+ * 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.sources.v2.writer;
+
+import org.apache.spark.sql.sources.Filter;
+
+/**
+ * Write builder trait for tables that support overwrite by filter.
+ * <p>
+ * Overwriting data by filter will delete any data that matches the filter and 
replace it with data
+ * that is committed in the write.
+ */
+public interface SupportsOverwrite extends WriteBuilder {
 
 Review comment:
   This is needed for a couple use cases:
   1. `INSERT OVERWRITE ... PARTITION ...` with static partitions in static 
overwrite mode, for compatibility with existing queries.
   2. Situations where users would currently call `INSERT OVERWRITE`, but 
should be explicit.
   
   This operation is a combined delete and replace, [ReplaceData in the 
SPIP](https://docs.google.com/document/d/1gYm5Ji2Mge3QBdOliFV5gSPTKlX4q1DCBXIkiyMv62A/edit?ts=5a987801#heading=h.vgt28bdlilsp).
 This is currently implemented by the existing `INSERT OVERWRITE` statement.
   
   `INSERT OVERWRITE` (as defined by Hive) is dynamic so what gets deleted is 
implicit. Implicit deletes lead to confusion, so it would be better to move 
users to patterns that explicitly replace data.
   
   An example of such a pattern is an hourly job that is idempotent and 
produces a summary for a day. Each hour, it overwrites the summary from the 
last hour, until the day is finished and the last summary is left. We are 
moving users to structure this query to explicitly overwrite using an 
expression, which we can also use to warn if the user writes data that wouldn't 
be replaced by running the query again.
   
   A second use for this is static overwrite mode, which is a Spark-only 
behavior. In static mode, Spark will drop any matching static partitions and 
then insert data. In that case, we can't use dynamic overwrite because it 
wouldn't delete all of the static partitions. Instead, we translate the static 
partitions to an overwrite expression. So using this, we can implement all 
overwrite behaviors using the v2 API.

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