Github user cloud-fan commented on a diff in the pull request: https://github.com/apache/spark/pull/19269#discussion_r139705608 --- Diff: sql/core/src/main/java/org/apache/spark/sql/sources/v2/writer/DataSourceV2Writer.java --- @@ -0,0 +1,71 @@ +/* + * 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.annotation.InterfaceStability; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.SaveMode; +import org.apache.spark.sql.sources.v2.DataSourceV2Options; +import org.apache.spark.sql.sources.v2.WriteSupport; +import org.apache.spark.sql.types.StructType; + +/** + * A data source writer that is returned by + * {@link WriteSupport#createWriter(StructType, SaveMode, DataSourceV2Options)}. + * It can mix in various writing optimization interfaces to speed up the data saving. The actual + * writing logic is delegated to {@link WriteTask} that is returned by {@link #createWriteTask()}. + * + * The writing procedure is: + * 1. Create a write task by {@link #createWriteTask()}, serialize and send it to all the + * partitions of the input data(RDD). + * 2. For each partition, create a data writer with the write task, and write the data of the + * partition with this writer. If all the data are written successfully, call + * {@link DataWriter#commit()}. If exception happens during the writing, call + * {@link DataWriter#abort()}. This step may repeat several times as Spark will retry failed + * tasks. + * 3. Wait until all the writers/partitions are finished, i.e., either committed or aborted. If + * all partitions are written successfully, call {@link #commit(WriterCommitMessage[])}. If + * some partitions failed and aborted, call {@link #abort()}. --- End diff -- cc @rdblue @rxin do we really need an individual SPIP for the write path? I think this procedure is the only thing we need some high-level discussion, other parts are very similar to the read path, e.g. `WriteSupport` -> `DataSourceV2Writer` -> `WriteTask` -> `DataWriter`.
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