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The following commit(s) were added to refs/heads/master by this push:
     new cf27972eb10 Update CHANGES.md with new known issues (#39898)
cf27972eb10 is described below

commit cf27972eb10d81df85f25c22757d31073d6a4c9f
Author: Danny McCormick <[email protected]>
AuthorDate: Thu Aug 27 13:34:15 2026 +0000

    Update CHANGES.md with new known issues (#39898)
    
    * Update CHANGES.md with new known issues
    
    Added known issues related to performance regression and memory spikes for 
Java pipelines.
---
 CHANGES.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/CHANGES.md b/CHANGES.md
index 151cbe14aaa..903f65b50a6 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -204,6 +204,8 @@
 
 * (Java) Projects using the Flink runner with Flink 2.1 or later alongside 
libraries requiring `org.lz4:lz4-java` (e.g., Kafka clients) may encounter a 
Gradle capability conflict, because Flink 2.1+ ships `at.yawk.lz4:lz4-java` 
which declares the same capability. To resolve, add a `capabilitiesResolution` 
rule to your `build.gradle` that selects `at.yawk.lz4:lz4-java` 
([#38947](https://github.com/apache/beam/issues/38947)).
 * (Python) Long-running Python pipelines might experience memory growth and 
periodic OOMs ([#39406](https://github.com/apache/beam/issues/39406)).
+* (Java) Pipelines with a moderate to heavy Cloud Storage read workload might 
experience a performance regression 
([#39548](https://github.com/apache/beam/issues/39548)).
+* (Java) Pipelines using the Dataflow Runner and Java versions 17+ may 
experience spiky memory caused by a JVM upgrade in the runner image 
([#39897](https://github.com/apache/beam/issues/39897).
 
 # [2.74.0] - 2026-06-02
 
@@ -249,6 +251,8 @@
 ## Known Issues
 
 * (Python) Long-running Python pipelines might experience memory growth and 
periodic OOMs ([#39406](https://github.com/apache/beam/issues/39406)).
+* (Java) Pipelines with a moderate to heavy Cloud Storage read workload might 
experience a performance regression 
([#39548](https://github.com/apache/beam/issues/39548)).
+* (Java) Pipelines using the Dataflow Runner and Java versions 17+ may 
experience spiky memory caused by a JVM upgrade in the runner image 
([#39897](https://github.com/apache/beam/issues/39897).
 
 # [2.73.0] - 2026-04-29
 

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