The Suppression buffer stores the full record context, not just the key and value,
so its changelog/restore loop will also need to preserve this information.
This change is a precondition to that, creating an option to register a
state restore callback to receive the full consumer record.
Reviewers: Bill Bejeck <bill@confluent.io>, Matthias J. Sax <matthias@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
This is Part 2 of suppression.
Part 1 was #5567
In an effort to control the scope of the review, this PR is just the tests for buffered suppression.
Reviewers: Bill Bejeck <bill@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
Part 1 of the suppression API.
* add the DSL suppress method and config objects
* add the processor, but only in "identity" mode (i.e., it will forward only if the suppression spec says to forward immediately)
* add tests
Reviewers: Matthias J. Sax <matthias@confluent.io>, Bill Bejeck <bill@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
This patch implements KIP-336. It adds a default implementation to the Serializer/Deserializer interface to support the use of headers and it deprecates the ExtendedSerializer and ExtendedDeserializer interfaces for later removal.
Reviewers: Satish Duggana <sduggana@hortonworks.com>, John Roesler <john@confluent.io>, Jason Gustafson <jason@confluent.io>
What changes were proposed in this pull request?
atLeast(0) in StreamsConfig, ProducerConfig and ConsumerConfig were replaced by SEND_BUFFER_LOWER_BOUND and RECEIVE_BUFFER_LOWER_BOUND from CommonClientConfigs.
How was this patch tested?
Three unit tests were added to KafkaStreamsTest
Reviewers: Guozhang Wang <guozhang@confluent.io>, John Roesler <john@confluent.io>, Matthias J. Sax <mjsax@apache.org>
Increasing the number of unique keys, to increase likelihood that the test exposes KAFKA-7192.
Reviewers: Apurva Mehta <apurva@confluent.io>, Guozhang Wang <guozhang@confluent.io>, Bill Bejeck <bill@confluent.io>, John Roesler <john@confluent.io>
Removed ignore annotations from the upgrade tests. This PR includes the following changes for updating the upgrade tests:
* Uploaded new versions 0.10.2.2, 0.11.0.3, 1.0.2, 1.1.1, and 2.0.0 (in the associated scala versions) to kafka-packages
* Update versions in version.py, Dockerfile, base.sh
* Added new versions to StreamsUpgradeTest.test_upgrade_downgrade_brokers including version 2.0.0
* Added new versions StreamsUpgradeTest.test_simple_upgrade_downgrade test excluding version 2.0.0
* Version 2.0.0 is excluded from the streams upgrade/downgrade test as StreamsConfig needs an update for the new version, requiring a KIP. Once the community votes the KIP in, a minor follow-up PR can be pushed to add the 2.0.0 version to the upgrade test.
* Fixed minor bug in kafka-run-class.sh for classpath in upgrade/downgrade tests across versions.
* Follow on PRs for 0.10.2x, 0.11.0x, 1.0.x, 1.1.x, and 2.0.x will be pushed soon with the same updates required for the specific version.
Reviewers: Eno Thereska <eno.thereska@gmail.com>, John Roesler <vvcephei@users.noreply.github.com>, Guozhang Wang <wangguoz@gmail.com>, Matthias J. Sax <matthias@confluent.io>
Reviewers: Guozhang Wang <guozhang@confluent.io>, John Roessler <john@confluent.io>, Bill Bejeck <bill@confluent.io>, Eno Thereska <enother@amazon.com>
Currently, scala.Serdes.String, for example, invokes Serdes.String() once and caches the result.
However, the implementation of the String serde has a non-empty configure method that is variant in whether it's used as a key or value serde. So we won't get correct execution if we create one serde and use it for both keys and values.
Reviewers: Bill Bejeck <bill@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
* Refactor the StreamThread main loop, in the following:
1. Fetch from consumer and enqueue data to tasks.
2. Check if any tasks should be enforced process.
3/ Loop over processable tasks and process them for N iterations, and then check for 1) commit, 2) punctuate, 3) need to call consumer.poll
4. Even if there is not data to process in this iteration, still need to check if commit / punctuate is needed
5. Finally, try update standby tasks.
*Add an optimization to only commit when it is needed (i.e. at least some process() or punctuate() was triggered since last commit).
*Found and fixed a ProducerFencedException scenario: producer.send() call would never throw a ProducerFencedException directly, but it may throw a KafkaException whose "cause" is a ProducerFencedException.
Reviewers: Matthias J. Sax <matthias@confluent.io>, John Roesler <john@confluent.io>, Bill Bejeck <bill@confluent.io>
Reviewers: Matthias J. Sax <matthias@confluent.io>, Guozhang Wang <guozhang@confluent.io>, Bill Bejeck <bill@confluent.io>, Kamal Chandraprakash <kamal.chandraprakash@gmail.com>
Previously, we depicted creating a Jackson serde for every pojo class, which becomes a burden in practice. There are many ways to avoid this and just have a single serde, so we've decided to model this design choice instead.
Reviewers: Viktor Somogyi <viktorsomogyi@gmail.com>, Bill Bejeck <bill@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
This PR fixes the previously recursive call of Streams Scala peek
Reviewers: Joan Goyeau <joan@goyeau.com>, Guozhang Wang <guozhang@confluent.io>, John Roesler <john@confluent.io>
Changes:
1. Add org.apache.kafka.streams.processor.internals.metrics.CumulativeCount analogous to Count, but not a SampledStat
2. Use CumulativeCount for -total metrics in streams instead of Count
Testing strategy:
Add a test in StreamsMetricsImplTest which fails on old, incorrect behavior
The contribution is my original work and I license the work to the project under the project's open source license.
Reviewers: Guozhang Wang <guozhang@confluent.io>, John Roesler <john@confluent.io>
Update to KIP-328.
Reviewers: Matthias J. Sax <matthias@confluent.io>, Guozhang Wang <guozhang@confluent.io>, Ted Yu <yuzhihong@gmail.com>, Kamal Chandraprakash <kamal.chandraprakash@gmail.com>
Plus minor javadoc cleanups.
Reviewers: Matthias J. Sax <matthias@confluent.io>,Guozhang Wang <guozhang@confluent.io>, John Roesler <john@confluent.io>
Due to lack of conversion to kstream Predicate, existing filter method in KTable.scala would result in StackOverflowError.
This PR fixes the bug and adds testing for it.
Reviewers: Guozhang Wang <guozhang@confluent.io>, John Roesler <john@confluent.io>
Join in the Scala streams API is currently unusable in 2.0.0 as reported by @mowczare:
#5019 (comment)
This due to an overload of it with the same signature in the first curried parameter.
See compiler issue that didn't catch it: https://issues.scala-lang.org/browse/SI-2628
Reviewers: Debasish Ghosh <dghosh@acm.org>, Guozhang Wang <guozhang@confluent.io>, John Roesler <john@confluent.io>
This PR adds valueChangingOperation and mergeNode to StreamsGraphNode#toString
Reviewers: Matthias J. Sax <matthias@confluent.io>, Bill Bejeck <bill@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
Updated two integration tests to use IntegrationTestUtils#waitUntilFinalKeyValueRecordsReceived to eliminate flaky test results.
Also, I updated IntegrationTestUtils#waitUntilFinalKeyValueRecordsReceived method to support having results with the same key present with different values.
For testing, I ran the current suite of streams tests.
Reviewers: Matthias J. Sax <matthias@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
1) As titled, add a rewriteTopology that 1) sets application id, 2) maybe disable caching, 3) adjust for source KTable. This optimization can hence be applied for both DSL or PAPI generated Topology.
2) Defer the building of globalStateStores in rewriteTopology so that we can also disable caching. But we still need to build the state stores before InternalTopologyBuilder.build() since we should only build global stores once for all threads.
3) Added withCachingDisabled to StoreBuilder, it is a public API change.
4) [Optional] Fixed unit test config setting functionalities, and set the necessary config to shorten the unit test latency (now it reduces from 5min to 3.5min on my laptop).
Reviewers: Matthias J. Sax <matthias@confluent.io>, John Roesler <john@confluent.io>, Bill Bejeck <bill@confluent.io>, Ted Yu <yuzhihong@gmail.com>
This PR adds the optimization of eliminating multiple repartition topics when the KStream resulting from a key-changing operation executes other methods using the new key and reduces the repartition topics to one.
Note that this PR leaves in place the optimization for re-using a source topic as a changelog topic for source KTable instances. I'll have another follow-up PR to move the source topic optimization to a method within InternalStreamsBuilder so it can be performed in the same area of the code.
Additionally, the current value of StreamsConfig.OPTIMIZE is all and we'll need to have another KIP to change the value to 2.1.
An integration test RepartitionOptimizingIntegrationTest which asserts the same results for an optimized topology with one repartition topic as the un-optimized version with four repartition topics.
Reviewers: Matthias J. Sax <matthias@confluent.io>, John Roesler <john@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
Part I of KIP-238:
* add grace period to Windows
* deprecate retention/maintainMs and segmentInterval from Windows
* record expired records in the store with a new metric
* record late record drops as a new metric instead of as a "skipped record"
Reviewers: Matthias J. Sax <matthias@confluent.io>, Bill Bejeck <bill@confluent.io>, Guozhang Wang <wangguoz@gmail.com>
John Roesler
Bill Bejeck
Guozhang Wang
Lee Dongjin
Eugen Feller
Viktor Somogyi
Aleksei Izmalkin
Matthias J. Sax
Joan Goyeau
Manikumar Reddy O
Ewen Cheslack-Postava
huxi
tedyu
Sam Lendle
Kamal Chandraprakash
Mickael Maison
Koen De Groote