diff --git a/docs/streams/architecture.html b/docs/streams/architecture.html index 75d6d3dfb86a1..3ef9dfeed1f90 100644 --- a/docs/streams/architecture.html +++ b/docs/streams/architecture.html @@ -116,7 +116,7 @@
Kafka Streams provides so-called state stores, which can be used by stream processing applications to store and query data,
- which is an important capability when implementing stateful operations. The Kafka Streams DSL, for example, automatically creates
+ which is an important capability when implementing stateful operations. The Kafka Streams DSL, for example, automatically creates
and manages such state stores when you are calling stateful operators such as join() or aggregate(), or when you are windowing a stream.
test-utils module to help you test your application here.
You can run Java applications that use the Kafka Streams library without any additional configuration or requirements. Kafka Streams also provides the ability to receive notification of the various states of the application. The ability to monitor the runtime - status is discussed in the monitoring guide.
+ status is discussed in the monitoring guide.Table of Contents
To catch any unexpected exceptions, you can set an java.lang.Thread.UncaughtExceptionHandler before you start the
application. This handler is called whenever a stream thread is terminated by an unexpected exception:
// Java 8+, using lambda expressions
@@ -208,7 +208,7 @@ Using Kafka Streams within your application code
- Testing a Streams application
+ Testing a Streams application
Kafka Streams comes with a test-utils module to help you test your application here.
- Upgrading from any older version to {{fullDotVersion}} is possible: you will need to do two rolling bounces, where during the first rolling bounce phase you set the config upgrade.from="older version"
+ Upgrading from any older version to {{fullDotVersion}} is possible: if upgrading from 2.3 or below, you will need to do two rolling bounces, where during the first rolling bounce phase you set the config upgrade.from="older version"
(possible values are "0.10.0" - "2.3") and during the second you remove it. This is required to safely upgrade to the new cooperative rebalancing protocol of the embedded consumer. Note that you will remain using the old eager
rebalancing protocol if you skip or delay the second rolling bounce, but you can safely switch over to cooperative at any time once the entire group is on 2.4+ by removing the config value and bouncing. For more details please refer to
KIP-429:
@@ -100,7 +100,7 @@
cogroup() operator (via KIP-150>)
that allows to aggregate multiple streams in a single operation.
Cogrouped streams can also be windowed before they are aggregated.
- We refer to the developer guide for more details.
+ Please refer to the developer guide for more details.
We added a new KStream.toTable() API to translate an input event stream into a changelog stream as per
@@ -711,7 +711,7 @@