base on Demo applications and code examples for Apache Kafka's Streams API. # Kafka Streams Examples > [!NOTE] > This repo is replaced with [Confluent Tutorials for Apache Kafka](https://github.com/confluentinc/tutorials). We still "keep the lights on", but we don't improve existing examples any longer, nor do we add new example. This project contains code examples that demonstrate how to implement real-time applications and event-driven microservices using the Streams API of [Apache Kafka](http://kafka.apache.org/) aka Kafka Streams. For more information take a look at the [**latest Confluent documentation on the Kafka Streams API**](http://docs.confluent.io/current/streams/), notably the [**Developer Guide**](https://docs.confluent.io/platform/current/streams/developer-guide/index.html) --- Table of Contents * [Available examples](#available-examples) * [Examples: Runnable Applications](#examples-apps) * [Examples: Unit Tests](#examples-unit-tests) * [Examples: Integration Tests](#examples-integration-tests) * [Docker Example: Kafka Music demo application](#examples-docker) * [Examples: Event Streaming Platform](#examples-event-streaming-platform) * [Requirements](#requirements) * [Apache Kafka](#requirements-kafka) * [Confluent Platform](#requirements-confluent-platform) * [Using IntelliJ or Eclipse](#requirements-ide) * [Java](#requirements-java) * [Scala](#requirements-scala) * [Packaging and running the examples](#packaging-and-running) * [Development](#development) * [Version Compatibility Matrix](#version-compatibility) * [Where to find help](#help) --- <a name="available-examples"/> # Available examples This repository has several branches to help you find the correct code examples for the version of Apache Kafka and/or Confluent Platform that you are using. See [Version Compatibility Matrix](#version-compatibility) below for details. There are three kinds of examples: * **Examples under [src/main/](src/main/)**: These examples are short and concise. Also, you can interactively test-drive these examples, e.g. against a local Kafka cluster. If you want to actually run these examples, then you must first install and run Apache Kafka and friends, which we describe in section [Packaging and running the examples](#packaging-and-running). Each example also states its exact requirements and instructions at the very top. * **Examples under [src/test/](src/test/)**: These examples should test applications under [src/main/](src/main/). Unit Tests with TopologyTestDriver test the stream logic without external system dependencies. The integration tests use an embedded Kafka clusters, feed input data to them (using the standard Kafka producer client), process the data using Kafka Streams, and finally read and verify the output results (using the standard Kafka consumer client). These examples are also a good starting point to learn how to implement your own end-to-end integration tests. * **Ready-to-run Docker Examples**: These examples are already built and containerized. <a name="examples-apps"/> ## Examples: Runnable Applications Additional examples may be found under [src/main/](src/main/java/io/confluent/examples/streams/). | Application Name | Concepts used | Java 8+ | Java 7+ | Scala | | --------------------------- | -------------------------------------------------------- | ------- | ------- | ----- | | WordCount | DSL, aggregation, stateful | [Java 8+ example](src/main/java/io/confluent/examples/streams/WordCountLambdaExample.java) | | [Scala Example](src/main/scala/io/confluent/examples/streams/WordCountScalaExample.scala) | | MapFunction | DSL, stateless transformations, `map()` | [Java 8+ example](src/main/java/io/confluent/examples/streams/MapFunctionLambdaExample.java) | | [Scala Example](src/main/scala/io/confluent/examples/streams/MapFunctionScalaExample.scala) | | SessionWindows | Sessionization of user events, user behavior analysis | | [Java 7+ example](src/main/java/io/confluent/examples/streams/SessionWindowsExample.java) | GlobalKTable | `join()` between `KStream` and `GlobalKTable` | [Java 8+ example](src/main/java/io/confluent/examples/streams/GlobalKTablesExample.java) | | | | GlobalStore | "join" between `KStream` and `GlobalStore` | [Java 8+ example](src/main/java/io/confluent/examples/streams/GlobalStoresExample.java) | | | | PageViewRegion | `join()` between `KStream` and `KTable` | [Java 8+ example](src/main/java/io/confluent/examples/streams/PageViewRegionLambdaExample.java) | [Java 7+ example](src/main/java/io/confluent/examples/streams/PageViewRegionExample.java) | | | PageViewRegionGenericAvro | Working with data in Generic Avro format | [Java 8+ example](src/main/java/io/confluent/examples/streams/PageViewRegionLambdaExample.java) | [Java 7+ example](src/main/java/io/confluent/examples/streams/PageViewRegionExample.java) | | | WikipediaFeedSpecificAvro | Working with data in Specific Avro format | [Java 8+ example](src/main/java/io/confluent/examples/streams/WikipediaFeedAvroLambdaExample.java) | [Java 7+ example](src/main/java/io/confluent/examples/streams/WikipediaFeedAvroExample.java) | | | SecureKafkaStreams | Secure, encryption, client authentication | | [Java 7+ example](src/main/java/io/confluent/examples/streams/SecureKafkaStreamsExample.java) | | | Sum | DSL, stateful transformations, `reduce()` | [Java 8+ example](src/main/java/io/confluent/examples/streams/SumLambdaExample.java) | | | | WordCountInteractiveQueries | Interactive Queries, REST, RPC | [Java 8+ example](src/main/java/io/confluent/examples/streams/interactivequeries/WordCountInteractiveQueriesExample.java) | | | | KafkaMusic | Interactive Queries, State Stores, REST API | [Java 8+ example](src/main/java/io/confluent/examples/streams/interactivequeries/kafkamusic/KafkaMusicExample.java) | | | | ApplicationReset | Application Reset Tool `kafka-streams-application-reset` | [Java 8+ example](src/main/java/io/confluent/examples/streams/ApplicationResetExample.java) | | | | Microservice | Microservice ecosystem, state stores, dynamic routing, joins, filtering, branching, stateful operations | [Java 8+ example](src/main/java/io/confluent/examples/streams/microservices) | | | <a name="examples-unit-tests"/> ## Examples: Unit Tests The stream processing of Kafka Streams can be **unit tested** with the `TopologyTestDriver` from the `org.apache.kafka:kafka-streams-test-utils` artifact. The test driver allows you to write sample input into your processing topology and validate its output. See the documentation at [Testing Streams Code](https://docs.confluent.io/current/streams/developer-guide/test-streams.html). <a name="examples-integration-tests"/> ## Examples: Integration Tests We also provide several **integration tests**, which demonstrate end-to-end data pipelines. Here, we spawn embedded Kafka clusters and the [Confluent Schema Registry](https://github.com/confluentinc/schema-registry), feed input data to them (using the standard Kafka producer client), process the data using Kafka Streams, and finally read and verify the output results (using the standard Kafka consumer client). Additional examples may be found under [src/test/](src/test/java/io/confluent/examples/streams/). > Tip: Run `mvn test` to launch the tests. | Integration Test Name | Concepts used | Java 8+ | Java 7+ | Scala | | ----------------------------------- | ------------------------------------------- | ------- | ------- | ----- | | WordCount | DSL, aggregation, stateful | [Java 8+ Example](src/test/java/io/confluent/examples/streams/WordCountLambdaIntegrationTest.java) | | [Scala Example](src/test/scala/io/confluent/examples/streams/WordCountScalaIntegrationTest.scala) | | WordCountInteractiveQueries | Interactive Queries, REST, RPC | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/interactivequeries/WordCountInteractiveQueriesExampleTest.java) | | | Aggregate | DSL, `groupBy()`, `aggregate()` | [Java 8+ Example](src/test/java/io/confluent/examples/streams/AggregateTest.java) | | [Scala Example](src/test/scala/io/confluent/examples/streams/AggregateScalaTest.scala) | | CustomStreamTableJoin | DSL, Processor API, Transformers | [Java 8+ Example](src/test/java/io/confluent/examples/streams/CustomStreamTableJoinIntegrationTest.java) | | | | EventDeduplication | DSL, Processor API, Transformers | [Java 8+ Example](src/test/java/io/confluent/examples/streams/EventDeduplicationLambdaIntegrationTest.java) | | | | GlobalKTable | DSL, global state | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/GlobalKTablesExampleTest.java) | | | GlobalStore | DSL, global state, Transformers | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/GlobalStoresExampleTest.java) | | | HandlingCorruptedInputRecords | DSL, `flatMap()` | [Java 8+ Example](src/test/java/io/confluent/examples/streams/HandlingCorruptedInputRecordsIntegrationTest.java) | | | | KafkaMusic (Interactive Queries) | Interactive Queries, State Stores, REST API | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/interactivequeries/kafkamusic/KafkaMusicExampleTest.java) | | | MapFunction | DSL, stateless transformations, `map()` | [Java 8+ Example](src/test/java/io/confluent/examples/streams/MapFunctionLambdaIntegrationTest.java) | | | | MixAndMatch DSL + Processor API | Integrating DSL and Processor API | [Java 8+ Example](src/test/java/io/confluent/examples/streams/MixAndMatchLambdaIntegrationTest.java) | | | | PassThrough | DSL, `stream()`, `to()` | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/PassThroughIntegrationTest.java) | | | PoisonPill | DSL, `flatMap()` | [Java 8+ Example](src/test/java/io/confluent/examples/streams/HandlingCorruptedInputRecordsIntegrationTest.java) | | | | ProbabilisticCounting\*\*\* | DSL, Processor API, custom state stores | | | [Scala Example](src/test/scala/io/confluent/examples/streams/ProbabilisticCountingScalaIntegrationTest.scala) | | Reduce (Concatenate) | DSL, `groupByKey()`, `reduce()` | [Java 8+ Example](src/test/java/io/confluent/examples/streams/ReduceTest.java) | | [Scala Example](src/test/scala/io/confluent/examples/streams/ReduceScalaTest.scala) | | SessionWindows | DSL, windowed aggregation, sessionization | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/SessionWindowsExampleTest.java) | | | StatesStoresDSL | DSL, Processor API, Transformers | [Java 8+ Example](src/test/java/io/confluent/examples/streams/StateStoresInTheDSLIntegrationTest.java) | | | | StreamToStreamJoin | DSL, `join()` between KStream and KStream | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/StreamToStreamJoinIntegrationTest.java) | | | StreamToTableJoin | DSL, `join()` between KStream and KTable | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/StreamToTableJoinIntegrationTest.java) | [Scala Example](src/test/scala/io/confluent/examples/streams/StreamToTableJoinScalaIntegrationTest.scala) | | Sum | DSL, aggregation, stateful, `reduce()` | [Java 8+ Example](src/test/java/io/confluent/examples/streams/SumLambdaIntegrationTest.java) | | | | TableToTableJoin | DSL, `join()` between KTable and KTable | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/TableToTableJoinIntegrationTest.java) | | | UserCountsPerRegion | DSL, aggregation, stateful, `count()` | [Java 8+ Example](src/test/java/io/confluent/examples/streams/UserCountsPerRegionLambdaIntegrationTest.java) | | | | ValidateStateWithInteractiveQueries | Interactive Queries for validating state | | [Java 8+ Example](src/test/java/io/confluent/examples/streams/ValidateStateWithInteractiveQueriesLambdaIntegrationTest.java) | | | | GenericAvro | Working with data in Generic Avro format | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/GenericAvroIntegrationTest.java) | [Scala Example](src/test/scala/io/confluent/examples/streams/GenericAvroScalaIntegrationTest.scala) | | SpecificAvro | Working with data in Specific Avro format | | [Java 7+ Example](src/test/java/io/confluent/examples/streams/SpecificAvroIntegrationTest.java) | [Scala Example](src/test/scala/io/confluent/examples/streams/SpecificAvroScalaIntegrationTest.scala) | \*\*\*demonstrates how to probabilistically count items in an input stream by implementing a custom state store ([CMSStore](src/main/scala/io/confluent/examples/streams/algebird/CMSStore.scala)) that is backed by a [Count-Min Sketch](https://en.wikipedia.org/wiki/Count%E2%80%93min_sketch) data structure (with the CMS implementation of [Twitter Algebird](https://github.com/twitter/algebird)) <a name="examples-docker"/> # Docker Example: Kafka Music demo application This containerized example launches: * Confluent's Kafka Music demo application for the Kafka Streams API, which makes use of [Interactive Queries](http://docs.confluent.io/current/streams/developer-guide.html) * a single-node Apache Kafka cluster with a single-node ZooKeeper ensemble * a [Confluent Schema Registry](https://github.com/confluentinc/schema-registry) instance The Kafka Music application demonstrates how to build of a simple music charts application that continuously computes, in real-time, the latest charts such as latest Top 5 songs per music genre. It exposes its latest processing results -- the latest charts -- via Kafka’s [Interactive Queries](http://docs.confluent.io/current/streams/developer-guide.html#interactive-queries) feature via a REST API. The application's input data is in Avro format, hence the use of Confluent Schema Registry, and comes from two sources: a stream of play events (think: "song X was played") and a stream of song metadata ("song X was written by artist Y"). You can find detailed documentation at https://docs.confluent.io/current/streams/kafka-streams-examples/docs/index.html. <a name="event-streaming-platform"/> # Examples: Event Streaming Platform For additional examples that showcase Kafka Streams applications within an event streaming platform, please refer to the [examples GitHub repository](https://github.com/confluentinc/examples). <a name="requirements"/> # Requirements <a name="requirements-kafka"/> ## Apache Kafka The code in this repository requires Apache Kafka 0.10+ because from this point onwards Kafka includes its [Kafka Streams](https://github.com/apache/kafka/tree/trunk/streams) library. See [Version Compatibility Matrix](#version-compatibility) for further details, as different branches of this repository may have different Kafka requirements. > **For the `master` branch:** To build a development version, you typically need the latest `trunk` version of Apache Kafka > (cf. `kafka.version` in [pom.xml](pom.xml) for details). The following instructions will build and locally install > the latest `trunk` Kafka version: > > ```shell > $ git clone [email protected]:apache/kafka.git > $ cd kafka > $ git checkout trunk > > # Now build and install Kafka locally > $ ./gradlew clean && ./gradlewAll install > ``` <a name="requirements-confluent-platform"/> ## Confluent Platform The code in this repository requires [Confluent Schema Registry](https://github.com/confluentinc/schema-registry). See [Version Compatibility Matrix](#version-compatibility) for further details, as different branches of this repository have different Confluent Platform requirements. * [Confluent Platform Quickstart](http://docs.confluent.io/current/quickstart.html) (how to download and install) * [Confluent Platform documentation](http://docs.confluent.io/current/) > **For the `master` branch:** To build a development version, you typically need the latest `master` version of Confluent Platform's > Schema Registry (cf. `confluent.version` in [pom.xml](pom.xml), which is set by the upstream > [Confluent Common](https://github.com/confluentinc/common) project). > The following instructions will build and locally install the latest `master` Schema Registry version, which includes > building its dependencies such as [Confluent Common](https://github.com/confluentinc/common) and > [Confluent Rest Utils](https://github.com/confluentinc/rest-utils). > Please read the [Schema Registry README](https://github.com/confluentinc/schema-registry) for details. > > ```shell > $ git clone https://github.com/confluentinc/common.git > $ cd common > $ git checkout master > > # Build and install common locally > $ mvn -DskipTests=true clean install > > $ git clone https://github.com/confluentinc/rest-utils.git > $ cd rest-utils > $ git checkout master > > # Build and install rest-utils locally > $ mvn -DskipTests=true clean install > > $ git clone https://github.com/confluentinc/schema-registry.git > $ cd schema-registry > $ git checkout master > > # Now build and install schema-registry locally > $ mvn -DskipTests=true clean install > ``` Also, each example states its exact requirements at the very top. <a name="requirements-ide"/> ## Using IntelliJ or Eclipse If you are using an IDE and import the project you might end up with a "missing import / class not found" error. Some Avro classes are generated from schema files and IDEs sometimes do not generate these classes automatically. To resolve this error, manually run: ```shell $ mvn -Dskip.tests=true compile ``` If you are using Eclipse, you can also right-click on `pom.xml` file and choose _Run As > Maven generate-sources_. <a name="requirements-java"/> ## Java 17+ IntelliJ IDEA users: * Open _File > Project structure_ * Select "Project" on the left. * Set "Project SDK" to Java 17. * Set "Project language level" to "17 - Sealed types, always-strict floating-point semantics" <a name="requirements-scala"/> ## Scala > Scala is required only for the Scala examples in this repository. If you are a Java developer you can safely ignore > this section. If you want to experiment with the Scala examples in this repository, you need a version of Scala that supports Java 17. <a name="packaging-and-running"/> # Packaging and running the Application Examples The instructions in this section are only needed if you want to interactively test-drive the [application examples](#examples-apps) under [src/main/](src/main/). > **Tip:** If you only want to run the integration tests (`mvn test`), then you do not need to package or install > anything -- just run `mvn test`. These tests launch embedded Kafka clusters. The first step is to install and run a Kafka cluster, which must consist of at least one Kafka broker as well as at least one ZooKeeper instance. Some examples may also require a running instance of Confluent schema registry. The [Confluent Platform Quickstart](http://docs.confluent.io/current/quickstart.html) guide provides the full details. In a nutshell: ```shell # Ensure you have downloaded and installed Confluent Platform as per the Quickstart instructions above. #Generate a Cluster UUID $ KAFKA_CLUSTER_ID="$(bin/kafka-storage.sh random-uuid)" #Format Log Directories $ bin/kafka-storage.sh format --standalone -t $KAFKA_CLUSTER_ID -c config/kraft/reconfig-server.properties # Start the Kafka broker $ ./bin/kafka-server-start ./etc/kafka/server.properties # In a separate terminal, start Confluent Schema Registry $ ./bin/schema-registry-start ./etc/schema-registry/schema-registry.properties # Again, please refer to the Confluent Platform Quickstart for details such as # how to download Confluent Platform, how to stop the above three services, etc. ``` The next step is to create a standalone jar ("fat jar") of the [application examples](#examples-apps): ```shell # Create a standalone jar ("fat jar") $ mvn clean package # >>> Creates target/kafka-streams-examples-8.0.0-0-standalone.jar ``` > Tip: If needed, you can disable the test suite during packaging, for example to speed up the packaging or to lower > JVM memory usage: > > ```shell > $ mvn -DskipTests=true clean package > ``` You can now run the application examples as follows: ```shell # Run an example application from the standalone jar. Here: `WordCountLambdaExample` $ java -cp target/kafka-streams-examples-8.0.0-0-standalone.jar \ io.confluent.examples.streams.WordCountLambdaExample ``` The application will try to read from the specified input topic (in the above example it is ``streams-plaintext-input``), execute the processing logic, and then try to write back to the specified output topic (in the above example it is ``streams-wordcount-output``). In order to observe the expected output stream, you will need to start a console producer to send messages into the input topic and start a console consumer to continuously read from the output topic. More details in how to run the examples can be found in the [java docs](src/main/java/io/confluent/examples/streams/WordCountLambdaExample.java#L31) of each example code. If you want to turn on log4j while running your example application, you can edit the [log4j.properties](src/main/resources/log4j.properties) file and then execute as follows: ```shell # Run an example application from the standalone jar. Here: `WordCountLambdaExample` $ java -cp target/kafka-streams-examples-8.0.0-0-standalone.jar \ -Dlog4j.configuration=file:src/main/resources/log4j.properties \ io.confluent.examples.streams.WordCountLambdaExample ``` Keep in mind that the machine on which you run the command above must have access to the Kafka/ZooKeeper clusters you configured in the code examples. By default, the code examples assume the Kafka cluster is accessible via `localhost:9092` (aka Kafka's ``bootstrap.servers`` parameter) and the ZooKeeper ensemble via `localhost:2181`. You can override the default ``bootstrap.servers`` parameter through a command line argument. <a name="development"/> # Development This project uses the standard maven lifecycle and commands such as: ```shell $ mvn compile # This also generates Java classes from the Avro schemas $ mvn test # Runs unit and integration tests $ mvn package # Packages the application examples into a standalone jar ``` <a name="version-compatibility"/> # Version Compatibility Matrix | Branch (this repo) | Confluent Platform | Apache Kafka | | ----------------------------------------|--------------------|-------------------| | [master](../../../tree/master/)\* | 8.0.0-SNAPSHOT | 4.0.0-SNAPSHOT | | [7.9.x](../../../tree/7.9.x/) | 7.9.0-SNAPSHOT | 3.9.0 | | [7.8.0-post](../../../tree/7.8.0-post/) | 7.8.0 | 3.8.0 | | ... | | | | [7.1.0-post](../../../tree/7.1.0-post/) | 7.1.0 | 3.1.0 | Older version prior to 7.1.0 are [not supported any longer](https://docs.confluent.io/platform/current/installation/versions-interoperability.html). \*You must manually build the `4.0` version of Apache Kafka and the `8.0.0` version of Confluent Platform. See instructions above. The `master` branch of this repository represents active development, and may require additional steps on your side to make it compile. Check this README as well as [pom.xml](pom.xml) for any such information. <a name="help"/> # Where to find help * Looking for documentation on Apache Kafka's Streams API? * We recommend to read the [Kafka Streams chapter](https://docs.confluent.io/current/streams/) in the [Confluent Platform documentation](https://docs.confluent.io/current/). * Watch our talk [Rethinking Stream Processing with Apache Kafka](https://www.youtube.com/watch?v=ACwnrnVJXuE) * Running into problems to use the demos and examples in this project? * First, you should check our [FAQ wiki](https://github.com/confluentinc/kafka-streams-examples/wiki/FAQ) for an answer first. * If the FAQ doesn't help you, [create a new GitHub issue](https://github.com/confluentinc/kafka-streams-examples/issues). * Want to ask a question, report a bug in Kafka or its Kafka Streams API, request a new Kafka feature? * For general questions about Apache Kafka and Confluent Platform, please head over to the [Confluent mailing list](https://groups.google.com/forum/?pli=1#!forum/confluent-platform) or to the [Apache Kafka mailing lists](http://kafka.apache.org/contact). # License Usage of this image is subject to the license terms of the software contained within. Please refer to Confluent's Docker images documentation [reference](https://docs.confluent.io/platform/current/installation/docker/image-reference.html) for further information. The software to extend and build the custom Docker images is available under the Apache 2.0 License. ", Assign "at most 3 tags" to the expected json: {"id":"9110","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"