nsivabalan commented on a change in pull request #3149: URL: https://github.com/apache/hudi/pull/3149#discussion_r664610336
########## File path: hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/BulkInsertInternalPartitionerWithRowsFactory.java ########## @@ -0,0 +1,45 @@ +/* + * 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.hudi.execution.bulkinsert; + +import org.apache.hudi.exception.HoodieException; +import org.apache.hudi.table.BulkInsertPartitioner; + +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; + +/** + * A factory to generate built-in partitioner to repartition input Rows into at least + * expected number of output spark partitions for bulk insert operation. + */ +public abstract class BulkInsertInternalPartitionerWithRowsFactory { Review comment: Existing factory class for write client path is called BulkInsertInternalPartitionerFactory. hence named it this way. Reason is that, we have an interface called BulkInsertPartitioner. we have few out of the box partitioners and we could have user defined as well. hence the naming for these factories as internal. I can fix both the factories if you prefer. ########## File path: hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/BulkInsertInternalPartitionerWithRowsFactory.java ########## @@ -0,0 +1,45 @@ +/* + * 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.hudi.execution.bulkinsert; + +import org.apache.hudi.exception.HoodieException; +import org.apache.hudi.table.BulkInsertPartitioner; + +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; + +/** + * A factory to generate built-in partitioner to repartition input Rows into at least + * expected number of output spark partitions for bulk insert operation. + */ +public abstract class BulkInsertInternalPartitionerWithRowsFactory { Review comment: Existing factory class for write client path is called BulkInsertInternalPartitionerFactory. hence named it this way. Reason is that, we have an interface called BulkInsertPartitioner. we have few out of the box partitioners and we could have user defined as well. hence the naming for these factories as internal. I can fix the name for both the factories if you prefer. -- 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. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
