kandi X-RAY | kafka-tutorial Summary
kandi X-RAY | kafka-tutorial Summary
A Kafka tutorial to show you the basic concepts of Kafka, how to deploy it to Kubernetes, develop services that consume and produce from/to Kafka topic in Java, and how to stream data with Kafka-Streams. HTML version of the tutorial:
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Trending Discussions on kafka-tutorial
ANSWERAnswered 2021-Oct-28 at 15:45
Strimzi just created the Kubernetes Service of type
Loadbalancer. It is up to your Kubernetes cluster to provision the load balancer and set its external address which Strimzi can use. When the external address is listed as
pending it means the load balancer is not (yet) created. In some public clouds that can take few minutes, so it might be just about waiting for it. But keep in mind that the load balancers are not supported in all environments => and when they are not supported, you cannot really use them. So you really need to double check whether your environment supports them or not. Typically, different clouds would support load balancers while some local or bare-metal environments might not (but it really depends).
I'm also not really sure why did you configured the advertised host and port:
I am trying to specify a topic partition for my Kafka Connect Sink. In particular, I am using the DataStax Apache Kafka Connector.
There is a good amount of documentation and resources related to specifying a topic partition for a Kafka Consumer, for example:
- consumer.How to specify partition to read? [kafka]
However, I haven't been able to find anything at all regarding how to specify what partition a given Kafka Connect Sink Connector reads from.
It seems like the Confluent connector developer docs imply that specifying partition should be possible, but I don't see any config that I can set in the generic Kafka Sink Configuration Properties docs nor in the DSE Kafka Connector configuration docs.
My understanding is that a Kafka Connect Sink is basically a specific implementation of a Kafka Consumer that writes to a given data store. If so, it should be possible to specify a partition, is that correct? Or am I misunderstanding something about how Kafka Connectors work?...
ANSWERAnswered 2021-Aug-27 at 17:48
You cannot specify partitions in the Connect API. It subscribes to all partitions, then distributes consumer instances amongst worker tasks as part of a consumer group.
I have used Kafka in the past, but never the streams API. I am tasked with building a scalable service that accepts websocket connections and routes outbound messages from a central topic to the correct session based on user id.
This looks ridiculously simple using KStream. From one online tutorial:...
ANSWERAnswered 2021-Aug-11 at 20:57
You are correct - messages need to be deserialized, then inspected against a predicate (in application space)
throw away those that are not relevant, I could do that by hand
Sure, you could, but Kafka Streams has useful methods for defining session windows. Plus, you wouldn't need to define a consumer and producer instance to forward to new topics.
is it possible to join multiple streams to one stream without a join / window clause? I just want something similiar as a combined kafka topic, where all messages can be found for further processing....
ANSWERAnswered 2021-Jun-24 at 13:58
To inform all fellows. If you use a insert into select...-statement, a running query will be created and the final stream will receive further updates.
I'm doing this simple windowed aggregation in kafka streams:...
ANSWERAnswered 2021-Jan-06 at 11:13
The suppress operator is based on event-time and as long as no new records arrive the stream is basically frozen.
This post explains how to test this.
For the tests to work you need:
- produce test data
- produce a dummy event with future timestamp to release the window result assert.
Note that each test needs to be isolated (e.g bring Kafka broker and the stream up before and turn off after each individual test or close the test driver).
I need to pushing a JSON file into a Kafka topic, connecting the topic in presto and structuring the JSON data into a queryable table.
I am following this tutorial https://prestodb.io/docs/current/connector/kafka-tutorial.html#step-2-load-data
I am not able to understand how this command will work.
$ ./kafka-tpch load --brokers localhost:9092 --prefix tpch. --tpch-type tiny
Suppose I have created test topic in kafka using producer. How will tpch file will generate of this topic?...
ANSWERAnswered 2020-Dec-18 at 05:10
If you already have a topic, you should skip to step 3 where it actually sets up the topics to query via Presto
kafka-tpch load creates new topics with the specified prefix
I learnt from This blog and this tutorial that in order to test suppression with event time semantics, one should send dummy records to advance stream time. I've tried to advance time by doing just that. But this does not seem to work unless time is advanced for a particular key.
I have a custom
TimestampExtractor which associates my preferred "stream-time" with the records.
My stream topology pseudocode is as follows (I use the Kafka Streams DSL API):
ANSWERAnswered 2020-Jul-13 at 14:40
I’m sorry for the trouble. This is indeed a tricky problem. I have some ideas for adding some operations to support this kind of integration testing, but it’s hard to do without breaking basic stream processing time semantics.
It sounds like you’re testing a “real” KafkaStreams application, as opposed to testing with TopologyTestDriver. My first suggestion is that you’ll have a much better time validating your application semantics with TopologyTestDriver, if it meets your needs.
It sounds to me like you might have more than one partition in your input topic (and therefore your application). In the event that key 1 goes to one partition, and key 3 goes to another, you would see what you’ve observed. Each partition of your application tracks stream time independently. TopologyTestDriver works nicely because it only uses one partition, and also because it processes data synchronously. Otherwise, you’ll have to craft your “dummy” time advancement messages to go to the same partition as the key you’re trying to flush out.
This is going to be especially tricky because your “flatMap().groupByKey()” is going to repartition the data. You’ll have to craft the dummy message so that it goes into the right partition after the repartition. Or you could experiment with writing your dummy messages directly into the repartition topic.
If you do need to test with KafkaStreams instead of TopologyTestDriver, I guess the easiest thing is just to write a “time advancement” message per key, as you were suggesting in your question. Not because it’s strictly necessary, but because it’s the easiest way to meet all these caveats. I’ll also mention that we are working on some general improvements to stream time handling in Kafka Streams that should simplify the situation significantly, but that doesn’t help you right now, of course.
I'm working through the very first section of the Confluent Tutorials: https://kafka-tutorials.confluent.io/kafka-console-consumer-producer-basics/kafka.html. Everything works as described, but I notice there's about 1 second of lag between when I press enter in the producer terminal and when a message is displayed in the consumer terminal. Is it the producer or the consumer who's responsible for this lag/batching? Is there a way to configure things to be more responsive? A quick search turned up the
linger.ms setting, but it seems like recent versions of Kafka default this setting to zero, and it doesn't appear to be overridden in these containers.
ANSWERAnswered 2020-Jul-12 at 20:34
Ok, it looks like setting
--timeout=0 in the producer makes the lag disappear. Looking at the
kafka-console-producer source code,
--timeout defaults to 1000 and gets merged into
LINGER_MS_CONFIG. So even though linger defaults to zero in Kafka generally, it effectively defaults to 1 sec in this command line producer.
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You can use kafka-tutorial like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the kafka-tutorial component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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