Getting Started

Announcing the release of Apache Samza 1.2.0

We’re thrilled to announce the release of Apache Samza 1.2.0.

Today Samza forms the backbone of hundreds of real-time production applications across a multitude of companies, such as LinkedIn, VMWare, Slack, Redfin among many others. Samza provides leading support for large-scale stateful stream processing with:

  • First class support for local state (with RocksDB store). This allows a stateful application to scale up to 1.1 Million events/sec on a single machine with SSD.

  • Support for incremental checkpointing of state instead of full snapshots. This enables Samza to scale to applications with very large state.

  • A fully asynchronous programming model that makes parallelizing remote calls efficient and effortless.

  • High level API for expressing complex stream processing pipelines in a few lines of code.

  • Beam Samza Runner that marries Beam’s best in class support for EventTime based windowed processing and sophisticated triggering with Samza’s stable and scalable stateful processing model.

  • A fully pluggable model for input sources (e.g. Kafka, Kinesis, DynamoDB streams etc.) and output systems (HDFS, Kafka, ElastiCache etc.).

  • A Table API that provides a common abstraction for accessing remote or local databases and allowing developers are able to “join” an input event stream with such a Table.

  • Flexible deployment model for running the applications in any hosting environment and with cluster managers other than YARN.

  • Features like canaries, upgrades and rollbacks that support extremely large deployments with minimal downtime.

New Features, Upgrades and Bug Fixes:

This release brings the following features, upgrades, and capabilities:

  • Upgrade to Kafka 2

  • Beam integration with tables and integration with CouchBase

  • Async high level API

  • Bug fixes

Full list of the jiras addressed in this release can be found here.

Upgrading your application to Apache Samza 1.2.0

Kafka upgrade

SAMZA-2127 Upgrade to Kafka 2.0

Async API for high level

SAMZA-2055 Design and Implement async API for high level

SAMZA-2172 Async High Level API does not schedule StreamOperatorTasks on separate threads


SAMZA-2192 Add StartpointVisitor implementation for EventHub.

SAMZA-2189 Integrate startpoint resolution workflow with SamzaContainer startup sequence.

SAMZA-2179 Move the StartpointVisitor abstraction to SystemAdmin interface.

SAMZA-2046 Startpoints - Fanout of SSP-only keyed Startpoints to SSP+TaskName

SAMZA-2132 Startpoint - flatten serialized key

Table API

SAMZA-2185 Ability to expose remote data source specific features in remote table

SAMZA-2156 Couchbase Table Support for Samza Table API

SAMZA-2153 Config for TableRetryPolicy

SAMZA-2134 Enable remote table rate limiter by default

SAMZA-2116 Make sendTo operators non-terminal

Bug Fixes, Testing and Stability improvments

SAMZA-2202 Modify topic creation s.t. all log compacted topics are created with a 5MB message size limit.

SAMZA-2181 Ensure consistency of coordinator store creation and initialization

SAMZA-2178 Utils to directly inject custom IME to InMemorySystem streams

SAMZA-2176 Ignore the configurations with serialized null values from coordinator stream.

SAMZA-2171 Encapsulate creation and loading of metadata streams

SAMZA-2170 Enabling writing of both new and old format offset files for stores and side-input-stores

SAMZA-2169 Preventing task-shuffle after task mode addition

SAMZA-2161 Move ChangelogPartitionManager and CoordinatorStream ConfigReader to MetadataStore

SAMZA-2135 Provide a way inject ExternalContext to TestRunner

Sources downloads

A source download of Samza 1.2.0 is available here, and is also available in Apache’s Maven repository. See Samza’s download page for details and Samza’s feature preview for new features.

Community Developments

Future Samza meetups can be found at Stream Processing with Apache Kafka & Apache Samza meetup/symposium


It’s a great time to get involved. You can start by reviewing the tutorials, signing up for the mailing list, and grabbing some newbie JIRAs.

We’d like to close by thanking everyone who’s been involved in the project. It’s been a great experience to be involved in this community, and we are lookng forward to its continued growth.

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