Kafka streams filter. You may also be interested in the Kafka Streams 101 course.

Kafka streams filter. But for that you would have to spend more resources to setup a KSQL server and that involves high availability, replication among other concerns. transforms. split (). It supports a great SQL-like mechanism to filter messages on the server side. condition Predicate. Learn how to test Kafka Streams applications effectively using various testing approaches and tools provided by Apache Kafka. KStream<String, Long> stream = ; // A filter that selects (keeps) only positive numbers // Java 8 Sep 26, 2025 · You create an eventstream, add event data sources to the stream, optionally add transformations to transform the event data, and then route the data to supported destinations. If the requirements change then you change the implementation of Kafka Streams app. condition predicate. This document provides usage information for the Apache Kafka Filter SMT org. 4, Spring for Apache Kafka provides first-class support for Kafka Streams. A KTable is either defined from a single Kafka topic that is consumed message by message or the result of a KTable transformation. This guide will help beginners understand Streams. I need to apply data filter condition on specific field/att Quix Streams is the easiest way I found to build production-ready real-time ML apps. Filter and how to use predicates. You can use the filter operator to apply a predicate on each record in a stream and keep only the records that satisfy the predicate. kafka. Most data processing operations can be expressed in just a few lines of DSL code. LINE uses Apache Kafka as a central datahub for our services to communicate to one another. The primary goal of this piece of software is to allow programmers to create efficient, real-time, streaming applications that could work as Microservices. In short, I mean just get the data as is and filter them using java code instead of doing it at Kafka Level. Kafka Streams Architecture Basically, by building on the Kafka producer and consumer libraries and leveraging the native capabilities of Kafka to offer data parallelism, distributed coordination, fault tolerance, and operational simplicity, Kafka Streams simplifies application development. start() will also cause another Kafka Client to be created and connected as producer, the promise will then resolve after both, the consumer and the producer have been connected to the broker successfully. The Kafka Streams API enables your applications to be queryable. Kafka Consumer provides the basic functionalities to handle messages. On a given application I have . Contribute to LGouellec/streamiz development by creating an account on GitHub. Streams DSL The Kafka Streams DSL (Domain Specific Language) is built on top of the Streams Processor API. Filter. Setting up a Maven Project We are going to use a Kafka Streams Maven Sep 6, 2023 · Kafka Streams is a popular stream processing library and framework that is part of the Apache Kafka ecosystem. Each has its distinct advantages, challenges, and suitability for various scenarios: KStream Conditional Branching: The KStream. Update: If you want to filter at Kafka Level, you can use partitions, while sending message to kafka topic, send messages with prefix 'a Jan 31, 2024 · Introduction Apache Kafka has become the go-to technology for stream processing, often used in combination with its stream-processing library Kafka Streams. 5k 8 127 147 KStream is an abstraction of a record stream of KeyValue pairs, i. A KStream is either defined from one or multiple Kafka topics that are consumed message by message or the result of a KStream transformation. Below image describes the anatomy of an application that uses the Kafka Streams library. KafkaStreams is engineered by the creators of Apache Kafka. Hundreds of billions of messages are produced daily and are used to execute various business logic, threat detection, search indexing and data analysis. Include or drop records that match the filter. It lets them create real-time streaming apps. Then, Kafka Streams adds a sink processor to write the records out to the repartition topic. Dynamic routing is particularly useful when the destination topic for a message depends on its content, enabling us to direct messages based on specific conditions or attributes within the payload. With Quix Streams you get the best of both worlds: an easy-to-use Python API, plus the scalability and robustness of Kafka and Docker. Detail guide with code snippets included. Essentially, the processor topology Sep 1, 2024 · K Streams is a key component of Kafka Streams, a powerful library within the Apache Kafka ecosystem for stream processing. 📱 📧 Demonstration project to showcase how big data and deep learning can be used to filter a stream of messages as either spam or not-spam messages. This section focuses on event filtering for self-managed Apache Kafka event sources. It allows you to build real-time data processing applications and microservices by Jun 18, 2015 · It uses Kafka Streams under the hood, you can define your ksql queries and tables on the server side, the results of which are written to kafka topics, so you could just consume those topics, instead of writing code to create a intermediary filtering consumer. NET Stream processing library for Apache Kafka. In this tutorial we will show a simple Kafka Streams example with Quarkus which shows how to perform stream processing tasks directly within the Kafka ecosystem, leveraging the familiar Kafka infrastructure to process and transform data in real-time When using stream$. Kafka Streams Basics for Confluent Platform In this section we summarize the key concepts of Kafka Streams. confluent. g. By understanding the core concepts, following common and best practices, and using the code examples provided, intermediate - to - advanced software engineers can effectively implement this solution in their projects. NET Stream Processing Library for Apache Kafka 🚀. It's perfect for simple data changes or complex stream processing. Oct 1, 2024 · Queryable Kafka Topics with Kafka Streams In today’s data processing architectures, Apache Kafka is often used at the ingress stage. Jul 26, 2025 · Master kafka: stream processing in Python with practical examples, best practices, and real-world applications 🚀 Kafka Connect Filter (Confluent) SMT Usage Reference for Confluent Cloud or Confluent Platform The following provides usage information for the Confluent SMT io. LINE leverages Kafka Streams to reliably transform and filter topics enabling sub topics consumers can efficiently consume, meanwhile retaining easy maintainability thanks to its sophisticated yet minimal code base. e. How do you filter messages in a Kafka topic to contain only those that you're interested in? In this tutorial, we will filter a stream of book publications down to those by a particular author. - LGouellec/streamiz-samples The Kafka Streams client library of Apache Kafka® provides a filter operator in its DSL. You can use event filtering to control which records from a stream or queue Lambda sends to your function. Figure 2: Kafka Stream Architecture Source Processor: Reads data from a Kafka topic. connect. But I need to consume only certain messages irrespective of the order in which message published. errors. stream(Serdes. So if your message throughput is in the decimal thousands/sec then I would use KStreams, if Confluent Cloud provides ksqlDB, a streaming SQL engine for Kafka. What is the recommend way to do this? Mar 21, 2017 · join stream apache-kafka apache-kafka-streams edited Mar 21, 2017 at 23:07 Matthias J. Dec 27, 2023 · Kafka Refresher: Streams and Transformations Before we look at inverse filters specifically, let‘s level set on Kafka Streams. Dec 1, 2016 · I have a Kafka stream that takes data from a topic, and needs to filter that information to two different topics. Also, with Apache Kafka endpoints available for eventstreams, you can send or consume real-time events by using the Kafka protocol. condition is a predicate specifying JSON Aug 9, 2024 · Kafka Stream是一个用于构建应用程序和微服务的客户端库，其中输入和输出数据存储在Kafka集群中。 它结合了在客户端编写和部署标准Java和Scala应用程序的简单性，以及Kafka服务器端集群技术的优势。 In this tutorial, learn how to split a stream of events into substreams with Kafka Streams, with step-by-step instructions and supporting code. In this tutorial, learn how to filter messages in a Kafka topic with Kafka Streams, with step-by-step instructions and supporting code. This guide demonstrates how to filter Kafka messages based on certain criteria using Spring Kafka, allowing you to handle specific messages efficiently. Kafka Streams also provides real-time stream processing on top of the Kafka Consumer client. Jul 28, 2022 · One more approach is to publish all the data into one topic and then distribute data to other topics (each per consumer) with Kafka Streams application. I receive following messages in kafka 1st second: 1 -> 23 (here 1 is key, 23 is value) 2nd second: 1 -> 445 3rd second: 1 -> Summary Kafka Streams uses RocksDB to maintain local state on a computing node. You'll use SELECTs to exclude events that match a specific criterion. Apache Kafka: A Distributed Streaming Platform. In this tutorial, we’ll explain the features of Kafka Streams to make the stream processing experience simple and easy. Nov 29, 2024 · Kafka in Java Spring Boot with Filter and DLT Apache Kafka is one of the most popularly used distributed event-streaming platforms, designed to handle real-time data feeds with high throughput and … Jul 18, 2022 · In KAFKA Filter is a Stateless Transformation Operation and it is pretty simple to implement it in both KStream and KTable. Oct 1, 2024 · In summary, combining Kafka Streams processors with State Stores and an HTTP server can effectively turn any Kafka topic into a fast read-only key-value store. Jan 8, 2024 · Dynamic routing of messages in Kafka Streams isn’t confined to a single approach but rather can be achieved using multiple techniques. The problem with this method, is because this wasn How to filter messages in a Kafka topic and write to a target Kafka topic using Streaming SQL and KStreams Kafka Streams offers two ways to define the stream processing topology: the Kafka Streams DSL provides the most common data transformation operations such as map, filter, join and aggregations out of the box; the lower-level Processor API allows developers define and connect custom processors as well as to interact with state stores. It enables us to do operations like joins, grouping, aggregation, and filtering of one or more streaming events. Oct 14, 2025 · Kafka Streams: Kafka Streams is a client library for building stream - processing applications. Jul 27, 2021 · Assuming you parameterize and package/containerize a Kafka Streams (or MirrorMaker) application that will route/filter topics, does it really matter what language its in? Oct 15, 2023 · The transaction filter topology demonstrates a simple stateless Kafka data stream processing. Discover step-by-step implementation and best practices. Mar 27, 2020 · I'm new on Scala and I'm trying to filter a KStream[String, JsonNode] based on the second component fields. I have been testing the below code for Kafka streams Producer topic: (this is the first producer topic - which sends the below json data) KafkaProducer&lt;Stri Kafka Streams is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. For example, in the following stream: #time, key 0, A 1, B 2, Learn how to implement Kafka message filtering in a Spring Boot application. Keep in mind that messages which will be produced to Kafka via . For Jul 19, 2025 · Using a Storm bolt to filter data and send it to different Kafka streams is a powerful technique for real - time data processing. Apr 21, 2019 · Continue to help good content that is interesting, well-researched, and useful, rise to the top! To gain full voting privileges, Jul 15, 2021 · Can I apply filter on fields of nested JSON record. It represents a continuous flow of records and is central to building Jul 30, 2025 · Apache Kafka is the most popular open-source distributed and fault-tolerant stream processing system. Learn how to use Kafka headers for use cases like metadata storage, routing, tracing, and more. Description Include or drop records that match the filter. Use a StreamsBuilder to create a stream, then apply filters and a mapping operation to it in this hands-on exercise. This seemed like a creative way of leveraging the DSL functionality. This is your complete guide to Kafka Streams. Partition data wisely to reduce the amount of irrelevant data that consumer instances need to process. Note that filter for a changelog stream works differently than record stream filters, because records with null values (so-called tombstone records) have delete semantics. Nov 29, 2022 · Only Texas car sales records are shown As shown above the Kafka Listener that reads the data only gets data with state:”Texas”, which was what the KStream filter is supposed to be doing. Jan 8, 2024 · In this tutorial, we’ll explore how to dynamically route messages in Kafka Streams. If you would like to do server-side filtering I would recommend using the KSQL. 1. This project contains code examples that demonstrate how to implement real-time applications and event-driven microservices using the Streams API of Apache Kafka aka Kafka Streams. For more detailed information refer to Kafka Streams Architecture for Confluent Platform and the Kafka Streams Developer Guide for Confluent Platform. This guide explores how to implement a streaming pipeline in a Spring Boot application to process data dynamically and distribute messages across multiple Kafka topics based on specific conditions. , map, filter, join). Thus, for tombstones the provided filter predicate is not evaluated but the tombstone record is forwarded directly if required (i. It is highly recommended to read the quickstart first on how to run a Streams application written in Kafka Streams if you have not done so. It provides built - in operators for filtering messages. Read Kafka Streams — How to Calculate Moving Average for Stock Prices in Real-time if you would like Apache Kafka: A Distributed Streaming Platform. 2 Learn how to filter messages in Spring Kafka based on headers in your listener. Feb 23, 2022 · I have a legacy kafka topic where different type of messages get sent, these messages are written with a custom header with a specific key to discriminate the record. First, Kafka Streams creates a filter operator to drop any records that have a null key as you must have a valid key to repartition the data records. Explore use cases, key concepts, and how to optimize your stream processing architecture. It is an optional dependency of the Spring for Apache Kafka project and is not downloaded transitively. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology. branch () method is the conventional means to segregate a stream based on predicates. It begins by consuming messages from a source, such as a Kafka topic. Aug 16, 2022 · What is the easiest way to filter messages based on time. To avoid this, is there any option to filter the events by reading the message Apache Kafka Streams Support Starting with version 1. In Kafka Streams, routing data from a single stream to multiple topics based on certain conditions is a common use case. An important concept of Kafka Streams is that of processor topology. StreamsBui May 6, 2023 · edited rsr-maersk on May 6, 2023 Hi For a topic partition, I see that the I see message ValueDeserializer specified by SetValueDeserializer is hit before a Consumer Filter context specified by UseFilter in the TopicEndpoint rider registration I would like to filter a kafka message based on a header value. You can also poll kafka messages in realtime from latest offset /from Aug 6, 2025 · Kafka Streams API is a powerful, lightweight library provided by Apache Kafka for building real-time, scalable, and fault-tolerant stream processing applications. Is it possible to apply this filter? If yes how can I address those internal nested JSON fields? Thanks in advance. For general information about how event filtering works, see Control which events Lambda sends to your function. Understanding the difference between stateful and stateless processing is Mar 20, 2023 · Kafka Streams is a client library providing organizations with a particularly efficient framework for processing streaming data. Demo applications and code examples for Streamiz, the . My data is JSON not AVRO, no schema registered. In this tutorial, learn how to filter duplicate events per-time window from a Kafka topic with Kafka Streams, with step-by-step instructions and supporting code. Managing Streams Application Topics A Kafka Streams application continuously reads from Kafka topics, processes the read data, and then writes the processing results back into Kafka topics. It is an easy-to-use yet powerful interactive SQL interface for stream processing on Kafka, In this article, we will see how to filter a Kafka stream by date using KSQL. streams. Nov 28, 2023 · Kafka Streams is a powerful and lightweight library provided by Apache Kafka for building real-time streaming applications and microservices. BrokerNotFoundException KIP-1230: Add config for file system permissions KTable is an abstraction of a changelog stream from a primary-keyed table. The Kafka Streams library allows you to perform complex stream processing directly within your Kafka applications by chained transformations. So if I consume all the events and start reading the message, it will require additional effort to process. A Kafka Streams application works by acting both as a producer and a consumer. LINE leverages Kafka Streams to reliably transform and filter topics enabling sub topics consumers can Oct 11, 2022 · I am consuming Kafka events through a Consumer Service by implementing IConsumer interface. By wrong way I mean they used a groupByKey & aggregate to compare previous/current values and then filter out the unchanged values. In this tutorial, learn how to filter messages in a Kafka topic with Flink SQL, with step-by-step instructions and supporting code. Kafka Streams creates the repartition topic under the covers. This operator filters out events that do not match a given predicate: Apr 13, 2020 · I have a single source CSV file containing records of different sizes that pushes every record into one source topic. Dec 22, 2020 · Apache Kafka 2. to("topic-name") to stream the final events of your stream back to another Kafka Topic, the use of . While this method is easy to Jan 31, 2024 · Conclusion Kafka Streams is a versatile library for building scalable, high-throughput, and fault-tolerant real-time stream processing applications. For more information take a look at the latest Confluent documentation on the Kafka Streams API, notably the Developer Guide Using ksqlDB on Confluent Cloud, learn how to filter an event stream into a new topic. apache. The full state of your application is typically split across many distributed instances of your application, and across many state stores that are managed locally by these Feb 5, 2021 · Most examples I found out in the wild of how to deduplicate identical or unchanged messages, I’ve recently discovered, do it the wrong way. When we create a KSQL stream or table, we implicitly get the following pseudo columns in each stream or table. Stream Processor: Applies operations on the incoming data stream (e. Processor topology is the blueprint of Kafka Stream operations on one or more event streams. In this article, we are going discuss deeply what Kafka, Kafka stream Kafka Streams (KStream) is a powerful tool that simplifies real-time data processing and message routing within Apache Kafka. Learn about the fundamental elements of Kafka Streams, including topologies and event streams, as well as some basic operations—mapping and filtering. It makes it easy to read, process, and write data back efficiently. The application may also auto-create other Kafka topics in the Kafka brokers, for example state store changelogs topics. It builds upon important stream processing concepts such as properly distinguishing between event time and processing time, windowing support, exactly-once processing semantics and simple yet efficient management of application state. It allows developers to process and analyze data stored in Kafka topics using simple, high-level operations such as filtering, transforming, and aggregating data. KStream<String, Model> stream = builder. For example CDC data from debezium MySQL connector comes with structure of {“before”:{…},“after”:{…}} I want to compare these updates over specific fields. to Jan 8, 2024 · Kafka Streams provides a duality between Kafka topics and relational database tables. The filter. Essentially, these are collections of data that can be transformed and processed in real-time. You may also be interested in the Kafka Streams 101 course. If a custom partitioner has been configured via StreamsConfig or KStream. Now Using AWS Lambda to process Apache Kafka streams Processing Kafka streams using the Lambda ESM 9 min The Lambda event source mapping resource polls records from one or many partitions and sends them to your Lambda function for processing. Mar 1, 2018 · Allow both the consumers to consume all data, once you get the records filter them using java stream with the filter logic specific to the consumer. I will be getting lots of events (around in lakhs), in these many events I hardly need to consume 100’s only. To use it from a Spring application, the kafka-streams jar must be present on classpath. through(String, Produced), or if the original KTable 's input topic is partitioned differently, please use metadataForKey(String, Object, StreamPartitioner). Sink Processor: Writes the processed data to a Kafka topic. KafkaStreams enables us to consume from Kafka topics, analyze or transform data, and potentially, send it to May 10, 2018 · I have been checking Kafka streams. Jul 19, 2024 · We're trying to use kafka streams for our project to read data from one topic and write to another, and we have a use case to use KafkaHeaders as a mechanism to filter our certain records. Kafka Streams is a client library for processing and analyzing data stored in Kafka. Jan 8, 2024 · Since ksqlDB is an event streaming database, streams and tables are its core abstractions. This will use the default Kafka Streams partitioner to locate the partition. Instrument is great for handling big data in real-time. Mar 5, 2020 · In this part, we will cover stateless operations in the Kafka Streams DSL API - specifically, the functions available in KStream such as filter, map, groupBy etc. E. This can be achieved using the Streams DSL to apply filtering and then directing the results to various topics as needed. . Basic Definition Filter KStream → KStream and KTable → KTable Evaluates a boolean function for each element and retains those for which the function returns true. I want to split the records into different KStreams/KTables from that source to Feb 20, 2025 · Just a plugin at already existing Kafka Connect cluster. Oct 22, 2017 · I am trying to filter for any messages whose key appears more often than a threshold N in a given (hopping) time window of length T. , each record is an independent entity/event in the real world. 6 included KIP-585 which adds support for defining predicates against which transforms are conditionally executed, as well as a Filter Single Message Transform to drop messages - which in combination means that you can conditionally drop messages. For example a user X might buy two items I1 and I2, and thus there might be two records <K:I1>, <K:I2> in the stream. Dec 27, 2023 · What stream branch transformations are and motivational use cases like filtering, routing, and deduplication How Kafka‘s branch() method works under the hood to split streams An end-to-end example walkthrough branching a stream of website clicks Best practices around ordering, stateful operations, and managing resources Learn how to build real-time event-driven applications with Kafka Streams. Each record in this changelog stream is an update on the primary-keyed table with the record key as the primary key. In this guide we will start from scratch on setting up your own project to write a stream processing application using Kafka Streams. It will show how to use it to its fullest potential. A Apache Kafka ships with Kafka Streams for event processing, but if you aren't in the Java ecosystem or if you prefer SQL, you can use ksqlDB to filter streams. Oct 24, 2025 · KIP-1221: Add application-id tag to Kafka Streams state metric next release Kafka 4. By following this guide, you’ve learned the basics and are well on your way to creating sophisticated stream processing applications with Kafka Streams. String(), specificAvroSerde, "not-filtered-topic"); Utilize Kafka Streams or KSQL for real-time stream processing which supports filtering as a first-class feature. 2 (merged): KIP-1034: Dead letter queue in Kafka Streams KIP-1153: Refactor Kafka Streams CloseOptions to Fluent API Style KIP-1195: deprecate and remove org. , if there is anything to be deleted). This class takes an implementation of RecordFilterStrategy in which you implement the filter method to signal that a message is a duplicate and should be discarded. This blog post went in depth on Kafka Streams state stores and RocksDB architecture, explaining the different ways that you can tune RocksDB to resolve potential operational issues that may arise with Kafka Streams. KafVam is a Windows Desktop UI for viewing Kafka topics, messages. Avoid the overhead of standing up ksqlDB, a Kafka Streams app, or an external ETL tool. Mar 13, 2024 · Examines how to correctly implement a Kafka message filtering strategy, both as a general approach and when the consumer needs to recover after deserialization errors are encountered. Sep 16, 2019 · I have a topic with different messages. Jan 30, 2024 · With KSQL and Kafka Streams, you can filter, join, window, and detect patterns on event streams effectively, making Kafka a robust solution for real-time event processing and analytics. As a example, the working Java code is this: import org. It is the recommended for most users, especially beginners. Sax 62. Kafka Streams Interactive Queries for Confluent Platform Interactive Queries allow you to leverage the state of your application from outside your application. Usually, this step is used to enrich and filter the incoming … The Spring for Apache Kafka project also provides some assistance by means of the FilteringMessageListenerAdapter class, which can wrap your MessageListener. Stream processing enables continuous computations over these unbounded streams of events. Kafka Streams is a game-changer for developers. We can transform, filter, aggregate, and join the collections to derive new collections or materialized views using SQL Jan 9, 2023 · 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. Jan 8, 2024 · In this article, we’ll be looking at the KafkaStreams library. dqhcyp gtv4 wmsl zfk4 rfm im6wfc mptw z0cmw cfr0 zd6vcc