davidradl commented on code in PR #860: URL: https://github.com/apache/flink-web/pull/860#discussion_r3412013090
########## docs/content/posts/2026-06-14-announcing-native-s3-fs.md: ########## @@ -0,0 +1,200 @@ +--- +title: "Introducing Flink's Native S3 FileSystem: Built for Performance, Designed for Production" +date: "2026-06-14T08:00:00.000Z" +slug: "announcing-native-s3-fs" +url: "/2026/06/14/announcing-native-s3-fs/" +authors: +- gabor: + name: "Gabor Somogyi" +- samrat: + name: "Samrat Deb" +aliases: +- /news/2026/06/14/announcing-native-s3-fs.html +--- + +Apache Flink relies on the underlying filesystem for much of its work: reading and writing application data, materializing streaming sinks, and storing checkpoints and savepoints for recovery. For years, S3 support in Flink meant choosing between two Hadoop-based plugins, each with its own trade-offs and configuration quirks. With Flink 2.3, there is a better option. + +Today we're introducing `flink-s3-fs-native`, A ground-up, Hadoop-free S3 filesystem built specifically for Flink. It ships as an experimental opt-in plugin in Flink 2.3, is already running in production at scale at major technology companies, and delivers measurable, reproducible performance gains. + + +**At a glance** + +| | | +|---|---| +| **~2x faster checkpoints** | 48.8 s average vs 90.1 s with the Presto plugin; up to 4.5x at small state sizes | +| **Drop-in replacement** | Swap the JAR, keep your existing `flink-conf.yaml`, restart your cluster | +| **No Hadoop dependency** | ~13 MB JAR vs ~30–93 MB; no CVE triage on Hadoop transitive dependencies | +| **AWS SDK v2** | Async-first I/O; AWS SDK v1 entered maintenance mode December 2025 | +| **One plugin for everything** | Exactly-once sinks and fast checkpoints — no trade-offs, no compromises | + + +## Two Plugins, One Filesystem, and No Good Answer + +If you've configured S3 for Flink before, you likely know that Flink ships two S3 filesystem plugins, and both register on the same `s3://` scheme. Only one can be active at a time. Choosing between them has been a source of confusion for years. + +The **Hadoop plugin** wraps Hadoop's S3A client. It supports `RecoverableWriter`, which enables exactly-once sinks. Unfortunately it pulls in the full `hadoop-common` dependency tree and AWS SDK v1. Configuration uses Hadoop-native keys (`fs.s3a.*`) mirrored to Flink-style keys (`s3.*`) through a compatibility layer. + +The **Presto plugin** was historically recommended for checkpointing because of its faster read path. But it does not support `RecoverableWriter`, which means exactly-once file sinks don't work with it. It carries known [bugs around directory deletion](https://github.com/prestodb/presto/issues/17416) that require Flink-side workarounds. It also depends on `hadoop-common` and AWS SDK v1 under the hood. + +Both share a common base layer that adapts a Hadoop `FileSystem` into a Flink `FileSystem`. This adaptation layer adds indirection, limits Flink-specific optimizations, and ties the implementation to Hadoop's configuration model and SDK lifecycle. + +As a result, you could have exactly-once sinks or a lighter read path, but not both. In addition, you are carrying Hadoop dependency hell. Review Comment: nit: hell -> challenges -- 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]
