cshuo commented on code in PR #12795: URL: https://github.com/apache/hudi/pull/12795#discussion_r1945873749
########## rfc/rfc-88/rfc-88.md: ########## @@ -0,0 +1,601 @@ +<!-- + 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. +--> +# RFC-88: New Schema/DataType/Expression Abstractions + +## Proposers + +- @cshuo +- @danny0405 + +## Approvers +- .. + +## Status + +JIRA: https://issues.apache.org/jira/browse/HUDI-8966 + +## Abstract + +Hudi currently is tightly coupled with Avro, particularly in terms of basic data types, schema, and the internal record +representation used in read/write paths. This coupling leads to numerous issues, for example, record-level unnecessary +Ser/De costs are introduced because of engine native row and Avro record converting, the data type can not be extended +to support other complex/advanced type, such as Variant and the basic read/ write functionality codes cannot be effectively +reused among different engines. As for Expression, currently, different engines have their own implementation to achieve +pushdown optimization, which is not friendly for extending as more indices are introduced. + +This RFC aims to propose an improvement to the current Schema/Type/Expression abstractions, to achieve the following goals: Review Comment: replied below. ########## rfc/rfc-88/rfc-88.md: ########## @@ -0,0 +1,601 @@ +<!-- + 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. +--> +# RFC-88: New Schema/DataType/Expression Abstractions + +## Proposers + +- @cshuo +- @danny0405 + +## Approvers +- .. + +## Status + +JIRA: https://issues.apache.org/jira/browse/HUDI-8966 + +## Abstract + +Hudi currently is tightly coupled with Avro, particularly in terms of basic data types, schema, and the internal record +representation used in read/write paths. This coupling leads to numerous issues, for example, record-level unnecessary +Ser/De costs are introduced because of engine native row and Avro record converting, the data type can not be extended +to support other complex/advanced type, such as Variant and the basic read/ write functionality codes cannot be effectively +reused among different engines. As for Expression, currently, different engines have their own implementation to achieve +pushdown optimization, which is not friendly for extending as more indices are introduced. + +This RFC aims to propose an improvement to the current Schema/Type/Expression abstractions, to achieve the following goals: +* Use a native schema as the authoritative schema, and make the type system extensible to support or customize other types, e.g, Variant. +* Abstract the common implementation of writer/readers and move them to hudi-common module, and engines just need implement getter/setters for specific rows(Flink RowData and Spark InternalRow). +* Add a concentrated and sharable expression abstraction for all kinds of expression pushdown for all engines and integrate it deeply with the MDT indices. + + +## Background +### Two 'Schema's +There exist two Schemas currently in Hudi's table management, Table schema in Avro format and a Hudi native `InternalSchema`. +During the processes of reading, writing and other operations, there are numerous mutual conversions, reconciliations, +and validation logics between the Avro table schema and `InternalSchema`, which incurs more difficulties in the understanding +and maintaining of specific functionalities. + +#### 1. Avro Schema +Hudi currently uses Avro schema as the table schema, to represent the structure of data written into the table. The table +schema is stored in the metadata of each writing commit to ensure that data of different versions can be resolved and reading +correctly, specifically: +* For reading: the Avro table schema is used throughout the scan process, to properly build readers, do some scan optimization and deserialize underlying data into specific records. +* For writing: the Avro table schema is used to check the validity of incoming data, build proper file writers, and finally commit the data with the schema itself stored in the commit metadata. + +#### 2. InternalSchema +`InternalSchema` is introduced to support the comprehensive schema evolution in RFC-33. The most notable feature of +`InternalSchema` is that it adds an `id` attribute to each column field, which is used to track all the column changes. +Currently, `InternalSchema` is also stored in the metadata of each writing commit if the schema evolution is enabled. +* For reading, with schema evolution enabled, `InternalSchema` is used to resolving data committed at different instant properly by make reconciliation between current table schema and historical `InternalSchema`. +* For writing, `InternalSchema` is necessary to deduce the proper writing schema by reconciling the input source schema with the latest table schema. In this way, the compatibility of the reading and writing process in schema evolution scenario can be well guaranteed. + +### Unnecessary AVRO Ser/De +Avro format is the default representation when dealing with records (reading, writing, clustering etc.). While it's simpler +to share more common functionalities, such as reading and writing of log block, it incurs more unnecessary Ser/De costs +between engine specific row (RowData for Flink, Internal for Spark). +Take Flink-Hudi as an example. For the upsert streaming writing cases, the basic data transforming flow is: + + +For the Flink streaming reading cases, the basic data transforming flow is: + + +As can be seen, there exists unnecessary record-level Avro Ser/De costs both in the log reading and writing process and +the similar problem exists when spark writes hoodie logs with Avro HoodieRecord. The costs can be eliminated if Avro +record can be substituted by engine specific row. Actually, RFC-46 has a good start to remove the need for conversion +from engine-specific internal representation to Avro. Currently, only Spark and Hive have implemented the new `HoodieRecord`, +and there arises another issue, i.e., no engine-agnostic basic infras for writers/readers for different engines and +different formats. We elaborate on the issue in the next part. + +### Separated File Readers/Writers for Different Engines +While Hudi works seamlessly with various query engines, such Spark, Flink, Hive etc., the underlying basic functionality +infrastructures for file reader/writer are not highly abstracted. Out of all the engines, Spark and Hudi are the most +seamlessly integrated. The Spark-Hudi integration leverages Spark's core read/write functionalities a lot. While these +functionalities are well-tested and performant in Spark using cases, they cannot be reused in Hudi's integration with other engines. Review Comment: replied below. -- This is an automated message from the Apache Git Service. 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