Jul 27, 2022
5 min read

What’s New in Apache Pulsar 2.9.3

Jun Ma
Qiang Zhao

The Apache Pulsar community releases version 2.9.3! 53 contributors provided improvements and bug fixes that delivered 200+ commits. Thanks for all your contributions.

The highlight of the 2.9.3 release is introducing 30+ transaction fixes and improvements. Earlier-adoption users of Pulsar transactions have documented long-term use in their production environments and reported valuable findings in real applications. This provides the Pulsar community with the opportunity to make a difference.

This blog walks through the most noteworthy changes. For the complete list including all feature enhancements and bug fixes, check out the Pulsar 2.9.3 Release Notes.

Notable enhancements and bug fixes

Enabled cursor data compression to reduce persistent cursor data size. 14542


The cursor data is managed by the ZooKeeper/Etcd metadata store. When the data size increases, it may take too much time to pull the data, and brokers may end up writing large chunks of data to the ZooKeeper/Etcd metadata store.


Provide the ability to enable compression mechanisms to reduce cursor data size and the pulling time.

Reduced the memory occupied by metadataPositions and avoid OOM. 15137


The map metadataPositions in MLPendingAckStore is used to clear useless data in PendingAck, where the key is the position that is persistent in PendingAck and the value is the max position acked by an operation. It judges whether the max subscription cursor position is smaller than the subscription cursor’s markDeletePosition. If the max position is smaller, then the log cursor will mark to delete the position. It causes two main issues:

  • In normal cases, this map stores all transaction ack operations. This is a waste of memory and CPU.
  • If a transaction that has not been committed for a long time acks a message in a later position, the map will not be cleaned up, which finally leads to OOM (out-of-memory).


Regularly store a small amount of data according to certain rules. For more detailed implementation, refer to PIP-153.

Checked lowWaterMark before appending transaction entries to Transaction Buffer. 15424


When a client sends messages using a previously committed transaction, these messages are visible to consumers unexpectedly.


Add a map to store the lowWaterMark of Transaction Coordinator in Trasanction Buffer, and check lowWaterMark before appending transaction entries to Trasanction Buffer. So when sending messages using an invalid transaction, clients will receive NotAllowedException.

Fixed the consumption performance regression. PR-15162


This performance regression was introduced in 2.10.0, 2.9.1, and 2.8.3. You may find a significant performance drop with message listeners while using Java Client. The root cause is each message will introduce the thread switching from the external thread pool to the internal thread poll and then to the external thread pool.


Avoid the thread switching for each message to improve consumption throughput.

Fixed a deadlock issue of topic creation. PR-15570


This deadlock issue occurred during topic creation by trying to re-acquire the same StampedLock from the same thread when removing it. This will cause the topic to stop service for a long time, and ultimately with a failure in the deduplication or geo-replication check. The workaround is restarting the broker.

Optimized the memory usage of brokers.


Pulsar has some internal data structures, such as ConcurrentLongLongPairHashMap, and ConcurrentLongPairHashMap, which can reduce the memory usage rather than using the Boxing type. However, in earlier versions, the data structures were not supported for shrinking even if the data was removed, which wasted a certain amount of memory in certain situations.

Pull requests


Support the shrinking of the internal data structures, such as ConcurrentSortedLongPairSet, ConcurrentOpenHashMap, and so on.

What’s Next?

If you are interested in learning more about Pulsar 2.9.3, you can download and try it out now!

Pulsar Summit San Francisco 2022 will take place on August 18th, 2022. Register now and help us make it an even bigger success by spreading the word on social media!

For more information about the Apache Pulsar project and current progress, visit the Pulsar website, follow the project on Twitter @apache_pulsar, and join Pulsar Slack!

Get involved

To get started, you can download Pulsar directly or you can spin up a Pulsar cluster with a free 30-day trial of StreamNative Cloud! We also offer technical consulting and expert training to help get your organization started. As always, we are highly responsive to your feedback. Feel free to contact us if you have any questions at any time. We look forward to hearing from you and stay tuned for the next Pulsar release!

Jun Ma
Jun Ma is a technical writer from StreamNative, focusing on the Pulsar open-source documentation. Before joining StreamNative, she has been working in the technology and engineering fields across multi-national companies. She is keen to help users understand complex concepts and bring valuable content to their information experience.
Qiang Zhao
Qiang Zhao is a software engineer at StreamNative. He is an Apache Pulsar Committer and MoP maintainer.


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