klion26 commented on code in PR #3667: URL: https://github.com/apache/amoro/pull/3667#discussion_r2212473296
########## README.md: ########## @@ -80,21 +92,27 @@ For details, please refer to: [Iceberg Docs](https://iceberg.apache.org/docs/lat Amoro support multiple processing engines for Mixed format as below: -| Processing Engine | Version | Batch Read | Batch Write | Batch Overwrite | Streaming Read | Streaming Write | Create Table | Alter Table | -|-------------------|------------------------|-------------|-------------|-----------------|----------------|-----------------|--------------|-------------| -| Flink | 1.15.x, 1.16.x, 1.17.x | ✔ | ✔ | ✖ | ✔ | ✔ | ✔ | ✖ | -| Spark | 3.1, 3.2, 3.3 | ✔ | ✔ | ✔ | ✖ | ✖ | ✔ | ✔ | -| Hive | 2.x, 3.x | ✔ | ✖ | ✔ | ✖ | ✖ | ✖ | ✔ | -| Trino | 406 | ✔ | ✖ | ✔ | ✖ | ✖ | ✖ | ✔ | +| Processing Engine | Version | Batch Read | Batch Write | Batch Overwrite | Streaming Read | Streaming Write | Create Table | Alter Table | +|-------------------|------------------------|------------|-------------|-----------------|----------------|-----------------|--------------|-------------| +| Flink | 1.15.x, 1.16.x, 1.17.x | ✔ | ✔ | ✖ | ✔ | ✔ | ✔ | ✖ | Review Comment: why do we need to change the format here? ########## README.md: ########## @@ -38,10 +38,12 @@ </p> Apache Amoro (incubating) is a Lakehouse management system built on open data lake formats. -Working with compute engines including Flink, Spark, and Trino, Amoro brings pluggable and self-managed features for Lakehouse to provide out-of-the-box data warehouse experience, +Working with compute engines including Flink, Spark, and Trino, Amoro brings pluggable and self-managed features for +Lakehouse to provide out-of-the-box data warehouse experience, Review Comment: IIUC, we should not break the line in markdown, there are many places that add a line break, and we should revert that. ########## README.md: ########## @@ -38,10 +38,12 @@ </p> Apache Amoro (incubating) is a Lakehouse management system built on open data lake formats. -Working with compute engines including Flink, Spark, and Trino, Amoro brings pluggable and self-managed features for Lakehouse to provide out-of-the-box data warehouse experience, +Working with compute engines including Flink, Spark, and Trino, Amoro brings pluggable and self-managed features for +Lakehouse to provide out-of-the-box data warehouse experience, Review Comment: Why does this change needed? -- 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]
