cloud-fan opened a new pull request #25651: [SPARK-28948][SQL] support data source v2 in CREATE TABLE USING URL: https://github.com/apache/spark/pull/25651 <!-- Thanks for sending a pull request! Here are some tips for you: 1. If this is your first time, please read our contributor guidelines: https://spark.apache.org/contributing.html 2. Ensure you have added or run the appropriate tests for your PR: https://spark.apache.org/developer-tools.html 3. If the PR is unfinished, add '[WIP]' in your PR title, e.g., '[WIP][SPARK-XXXX] Your PR title ...'. 4. Be sure to keep the PR description updated to reflect all changes. 5. Please write your PR title to summarize what this PR proposes. 6. If possible, provide a concise example to reproduce the issue for a faster review. --> ### What changes were proposed in this pull request? <!-- Please clarify what changes you are proposing. The purpose of this section is to outline the changes and how this PR fixes the issue. If possible, please consider writing useful notes for better and faster reviews in your PR. See the examples below. 1. If you refactor some codes with changing classes, showing the class hierarchy will help reviewers. 2. If you fix some SQL features, you can provide some references of other DBMSes. 3. If there is design documentation, please add the link. 4. If there is a discussion in the mailing list, please add the link. --> Currently Data Source V2 has 2 major use cases: 1. users plug in a custom catalog, which is tightly coupled with its own data. For example, users can plug in a cassandra catalog, and use Spark to read/write cassandra tables directly. 2. users read/write the external data as a table directly via `DataFrameReader/Writer`. Use case 1 is newly introduced in the master branch, which greatly improves the user experience when interacting with external storage systems that have catalogs, e.g. cassandra, JDBC, etc. Use case 2 is the main use case of Data Source V1, which works well if the external storage system doesn't have a catalog, e.g. parquet files on S3. However, use case 2 is incompleted in Data Source V2. Users can register a v1 source as a table in the builtin catalog, e.g. `CREATE TABLE t(i INT) USING parquet`, and then read/write the registered table. This is more convenient than `DataFrameReader/Writer`. However, Data Source V2 doesn't support it well. To support it, this PR updates `TableProvider#getTable` to accept additional partitioning info. The expected behaviors are defined in https://docs.google.com/document/d/1oaS0eIVL1WsCjr4CqIpRv6CGkS5EoMQrngn3FsY1d-Q/edit?usp=sharing ### Why are the changes needed? <!-- Please clarify why the changes are needed. For instance, 1. If you propose a new API, clarify the use case for a new API. 2. If you fix a bug, you can clarify why it is a bug. --> Make Data Source V2 supports the use case that is supported by Data Source V1. ### Does this PR introduce any user-facing change? <!-- If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible. If no, write 'No'. --> Yes, it's a new feature ### How was this patch tested? <!-- If tests were added, say they were added here. Please make sure to add some test cases that check the changes thoroughly including negative and positive cases if possible. If it was tested in a way different from regular unit tests, please clarify how you tested step by step, ideally copy and paste-able, so that other reviewers can test and check, and descendants can verify in the future. If tests were not added, please describe why they were not added and/or why it was difficult to add. --> a new test suite
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