alpinegizmo commented on code in PR #27841:
URL: https://github.com/apache/flink/pull/27841#discussion_r3024912959
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docs/content/docs/deployment/filesystems/s3.md:
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@@ -64,94 +64,267 @@ env.configure(config);
Note that these examples are *not* exhaustive and you can use S3 in other
places as well, including your [high availability setup]({{< ref
"docs/deployment/ha/overview" >}}) or the [EmbeddedRocksDBStateBackend]({{< ref
"docs/ops/state/state_backends" >}}#the-rocksdbstatebackend); everywhere that
Flink expects a FileSystem URI (unless otherwise stated).
-For most use cases, you may use one of our `flink-s3-fs-hadoop` and
`flink-s3-fs-presto` S3 filesystem plugins which are self-contained and easy to
set up.
-For some cases, however, e.g., for using S3 as YARN's resource storage dir, it
may be necessary to set up a specific Hadoop S3 filesystem implementation.
+## S3 FileSystem Implementations
-### Hadoop/Presto S3 File Systems plugins
+Flink provides three independent S3 filesystem implementations, each with
different trade-offs:
-{{< hint info >}}
-You don't have to configure this manually if you are running [Flink on
EMR](https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-flink.html).
-{{< /hint >}}
-
-Flink provides two file systems to talk to Amazon S3, `flink-s3-fs-presto` and
`flink-s3-fs-hadoop`.
-Both implementations are self-contained with no dependency footprint, so there
is no need to add Hadoop to the classpath to use them.
+- **Native S3 FileSystem** (`flink-s3-fs-native`): Built directly on AWS SDK
v2 with async I/O and parallel transfers, this implementation supports both
checkpointing and the FileSystem sink.
[Benchmarks](https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=406620396)
show ~2x higher checkpoint throughput (~200 MB/s vs ~90 MB/s) compared to the
Presto implementation at state sizes up to 15 GB. **Experimental** in Flink
2.3; the API and behavior may change in future releases.
Review Comment:
Good idea
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