Apache Kafka on HDInsight cluster. You’ll see in the example, but first let’s make sure you are setup and ready to go. Kafka Tutorial: Writing a Kafka Producer in Java. Well, I made a TV show running through the examples here. This quickstart will show how to create and connect to an Event Hubs Kafka endpoint using an example producer and consumer written in C# using .NET Core 2.0. To run the example shown above, you’ll need to perform the following in your environment. In other words, when running in a “cluster” of multiple nodes, the need to coordinate “which node is doing what?” is required. Consumer has to subscribe to a Topic, from which it can receive records. I’ll run through this in the screencast below, but this tutorial example utilizes the mySQL Employees sample database. If you need a TV show, let me know in the comments below and I might reconsider, but for now, this is what you need to do. Create a resource group Millions of developers and companies build, ship, and maintain their software on GitHub — the largest and most advanced development platform in the world. That new topic is then the one that you consume from Kafka Connect (and anywhere else that will benefit from a declared schema). Let’s see a demo to start. a java process), the names of several Kafka topics for “internal use” and a “group id” parameter. 1.3 Quick Start For mode, you have options, but since we want to copy everything it’s best just to set to `bulk`. Distributed mode to avoid possible confusion. The goal of this tutorial is to keep things as simple as possible and provide a working example with the least amount of work for you. Let’s run examples of a connector in Standalone and Distributed mode. This pleasurable Azure Kafka Azure tutorial contains step-by-step command references, sample configuration file examples for sink and source connectors as well as screencast videos of me demonstrating the setup and execution of the examples. When showing examples of connecting Kafka with Google Cloud Storage (GCS) we assume familiarity with configuring Google GCS buckets for access. And, when we run a connector in Distributed mode, yep, you guessed it, we’ll use this same cluster. Kill the Distributed worker process if you’d like. Kafka Connect (which is part of Apache Kafka) supports pluggable connectors, enabling you to stream data between Kafka and numerous types of system, including to mention just a few: ... and place it in a folder on your Kafka Connect worker. As you’ll see in the next screencast, this first tutorial utilizes the previous Kafka Connect MySQL tutorial. For our first Standalone example, let’s use a File Source connector. ), MySQL (if you want to use the sample source data; described more below), Kafka (examples of both Confluent and Apache Kafka are shown), Install S3 sink connector with `confluent-hub install confluentinc/kafka-connect-s3:5.4.1`, Optional `aws s3 ls kafka-connect-example` to verify your ~/.aws/credentials file, List topics `kafka-topics --list --bootstrap-server localhost:9092`, Load `mysql-bulk-source` source connector from the previous, List topics and confirm the mysql_* topics are present, Review the S3 sink connector configuration, Start Zookeeper `bin/zookeeper-server-start.sh config/zookeeper.propties`, Start Kafka `bin/kafka-server-start.sh config/server.properties`, S3 sink connector is downloaded, extracted and other configuration, List topics `bin/kafka-topics.sh --list --bootstrap-server localhost:9092`, Update your s3-sink.properties file — comment out, Unload your S3 sink connector if it is running, Check out S3 — you should see all your topic data whose name starts with, Install S3 sink connector with `confluent-hub install confluentinc/kafka-connect-s3-source:1.2.2`, List topics `kafka-topics --list --bootstrap-server localhost:9092` and highlight how the mysql_* topics are present, Load S3 source connector with `confluent local load s3-source — -d s3-source.properties`, List topics and confirm the copy_of* topics are present, Kafka Connect S3 Sink Connector documentation, More information AWS Credential Providers, running Kafka with Connect and Schema Registry, Kafka (connect, schema registry) running in one terminal tab, mysql jdbc driver downloaded and located in share/java/kafka-connect-jdbc (note about needing to restart after download), Sequel PRO with mySQL -- imported the employees db, list the topics `bin/kafka-topics --list --zookeeper localhost:2181`, `bin/confluent status connectors` or `bin/confluent status mysql-bulk-source`, list the topics again `bin/kafka-topics --list --zookeeper localhost:2181` and see the tables as topics, `bin/kafka-avro-console-consumer --bootstrap-server localhost:9092 --topic mysql-departments --from-beginning`, Sequel PRO with mySQL -- created a new destination database and verified tables and data created, `bin/confluent status connectors` or `bin/confluent status mysql-bulk-sink`. If Consumer Groups are new to you, check out that link first before proceeding here. In other words, we will demo Kafka S3 Source examples and Kafka S3 Sink Examples. The Azure Blob Storage Kafka Connect Source is a commercial offering from Confluent as described above, so let me know in the comments below if you find more suitable for self-managed Kafka. It is a publish-subscribe messaging system which let exchanging of data between applications, servers, and processors as well. All examples include a producer and consumer that can connect to any Kafka cluster running on-premises or in Confluent Cloud. So, you should have a connect-file-source.json file. A fundamental difference between Standalone and Distributed appears in this example. Let’s kick things off with a demo. This will be dependent on which flavor of Kafka you are using. If you were to run these examples on Apache Kafka instead of Confluent, you’d need to run connect-standalone.sh instead of connect-standalone and the locations of the default locations of connect-standalone.properties, connect-file-source.properties, and the File Source connector jar (for setting in plugins.path) will be different. Outside of regular JDBC connection configuration, the items of note are `mode` and `topic.prefix`. Let’s cover writing both Avro and JSON to GCP in the following tv show screencast. If you have any questions or concerns, leave them in the comments below. Well, maybe. As mentioned, there are two ways workers may be configured to run: Standalone and Distributed. Agina, I’m going to use Confluent, so my CLI scripts do not have .shat the end. First, pre-create 3 topics in the Dockerized cluster for Distributed mode as recommended in the documentation. But, it’s more fun to call it a Big Time TV show. When we run the example of Standalone, we will configure the Standalone connector to use this multi-node Kafka cluster. Resources for Data Engineers and Data Architects. I’m happy to help. As you would expect with Consumer Groups, Connect nodes running in Distributed mode can evolve by adding or removing more nodes. Multiple tasks do provide some parallelism or scaling out, but it is a different construct than running in Distributed mode. Your JSON key file will likely be named something different. I hope so because you are my most favorite big-shot-engineer-written-tutorial-reader ever. Create Java Project. Continuing the previous example, the connector might periodically check for new tables and notify Kafka Connect of additions and deletions. Lastly, we are going to demonstrate the examples using Apache Kafka included in Confluent Platform instead of standalone Apache Kafka because the Azure Blob Storage sink and source connectors are commercial offerings from Confluent. The focus will be keeping it simple and get it working. 2. If you have questions, comments or ideas for improvement, please leave them below.). If you need any assistance with setting up other Kafka distros, just let me know. Create a storage account If you want to run an Apache Kafka cluster instead of Confluent Platform, you might want to check out https://github.com/wurstmeister/kafka-docker or let me know if you have an alternative suggestion. We used this connector in the above examples. Afterward, we’ll go through each of the steps to get us there. For my environment, I have this set to a, Confirm events are flowing with the console consumer; i.e, Verify all three topics are listed with--, connect-distributed-example.properties file, Ensure this Distributed mode process you just started is ready to accept requests for Connector management via the Kafka Connect REST interface. This sample is based on Confluent's Apache Kafka .NET client, modified for use with Event Hubs for Kafka. Accompanying source code is available in GitHub (see Resources section for link) and screencast videos on YouTube. They also include examples of how to produce and … Connect File Source JSON used in Distributed Mode https://gist.github.com/tmcgrath/794ff6c4922251f2859264abf39866ae, An Azure account with enough permissions to be able to create, Azure CLI installed (Link in the Resources section below), Download and install the Sink and Source Connectors into your Apache Kafka cluster (Links in the Resources section below), Show sink connector already installed (I previously installed with, Show empty Azure Blob Storage container named, Generate 10 events of Avro test data with, The second example is JSON output, so edit, List out the new JSON objects landed into Azure with `, confluent local start (I had already installed the Source connector and made the updates described in “Workaround” section below). Apache Kafka Connector Example – Import Data into Kafka. Do you ever the expression “let’s work backward from the end”? Com-bined, Spouts and Bolts make a Topology. In this Kafka Connect mysql tutorial, we’ll cover reading from mySQL to Kafka and reading from Kafka and writing to mySQL. What if you want to stream multiple topics from Kafka to S3? You can do that in your environment because you’re the boss there. I hear it all the time now. A Kafka tutorial for beginners. This might seem random, but do you watch TV shows? There are cases when Standalone mode might make sense in Production. Second, they are responsible for monitoring inputs for changes that require reconfiguration and notifying the Kafka Connect runtime via the ConnectorContext. The Kafka Connect Handler is a Kafka Connect source connector. --resource-group todd \ Again, see the…. To review, Kafka connectors, whether sources or sinks, run as their own JVM processes called “workers”. The management of Connect nodes coordination is built upon Kafka Consumer Group functionality which was covered earlier on this site. As you’ll see, this demo assumes you’ve downloaded the Confluent Platform already. Edit this connect-distributed-example.properties in your favorite editor. There is a link for one way to do it in the Resources section below. There has to be a Producer of records for the Consumer to feed on. If you have questions, comments or suggestions for additional content, let me know in the comments below. Regardless of Kafka version, make sure you have the mySQL jdbc driver available in the Kafka Connect classpath. Well, you know what? What to do when we want to hydrate data into Kafka from GCS? Writing to GCS from Kafka with the Kafka GCS Sink Connector and then an example of reading from GCS to Kafka. Thanks. This means use the Azure Kafka Blob Storage Source connector independent of the sink connector or use an SMT to transform when writing back to Kafka. GitHub is where the world builds software. Note : Make sure that the Server URL and PORT are in compliance with the values in //config/server.properties. To manage connectors in Distributed mode, we use the REST API interface. Feedback always welcomed. You may consumer the records as per your need or use case. I’ve also provided sample files for you in my github repo. Let’s run this on your environment. To recap, here are the key aspects of the screencast demonstration (Note:  since I recorded this screencast above, the Confluent CLI has changed with a confluent local Depending on your version, you may need to add local immediately after confluent for example confluent local status connectors. Me too. To understand Kafka Connect Distributed mode, spend time exploring Kafka Consumer Groups. This means we will use the Confluent Platform in the following demo. This is what you’ll need if you’d like to perform the steps in your environment. --name tmcgrathstorageaccount \ Examples will be provided for both Confluent and Apache distributions of Kafka. Apache Kafka is a software platform which is based on a distributed streaming process. I’ll document the steps so you can run this on your environment if you want. As a possible workaround, there are ways to mount S3 buckets to a local files system using things like s3fs-fuse. Also, consumers could be grouped and the consumers in the Consumer Group could share the partitions of the Topics they subscribed to. But the process should remain same for most of the other IDEs. (Well, I’m just being cheeky now. What is Apache Kafka. --account-name tmcgrathstorageaccount \ Extract and find the db2jcc4.jar file within the downloaded tar.gz file, and place only the db2jdcc4.jar file into the share/java/kafka-connect-jdbc directory in your Confluent Platform installation. Note the type of that stream is Long, RawMovie, because the topic contains the raw movie objects we want to transform. Also, we’ll see an example of an S3 Kafka source connector reading files from S3 and writing to Kafka will be shown. Now, this might be completely fine for your use case, but if this is an issue for you, there might be a workaround. Or let me know if you have any questions or suggestions for improvement. Step by step guide to realize a Kafka Consumer is provided for understanding. We ingested mySQL tables into Kafka using Kafka Connect. The log compaction feature in Kafka helps support this usage. In this GCP Kafka tutorial, I will describe and show how to integrate Kafka Connect with GCP’s Google Cloud Storage (GCS). I wanted to make note of tasks vs. Storm was originally created by Nathan Marz and team at BackType. For example, if you downloaded a compressed tar.gz file (e.g., v10.5fp10_jdbc_sqlj.tar.gz), perform the following steps: In Standalone mode, a single process executes all connectors and their associated tasks. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Do you ever the expression “let’s work backwards”. For the Kafka Azure tutorial, there is a JSON example for Blob Storage Source available on the Confluent site at https://docs.confluent.io/current/connect/kafka-connect-azure-blob-storage/source/index.html#azure-blob-storage-source-connector-rest-example which might be helpful. In this usage Kafka is similar to Apache BookKeeper project. Again, I’m going to run through using the Confluent Platform, but I will note how to translate the examples to Apache Kafka. Writing this post inspired me to add resources for running in Distributed mode. Here’s a screencast writing to mySQL from Kafka using Kafka Connect, Once again, here are the key takeaways from the demonstration. Note: mykeyfile.json is just an example. Now, to set some initial expectations, these are just examples and we won’t examine Kafka Connect in standalone or distributed mode or how the internals of Kafka Consumer Groups assist Kafka Connect. It subscribes to one or more topics in the Kafka cluster and feeds on tokens or messages from the Kafka Topics. Like Consumer Group Consumers, Kafka Connect nodes will be rebalanced if nodes are added or removed. When attempting to use kafka-connect-azure-blob-storage-source:1.2.2 connector From docs, “Be careful when both the Connect GCS sink connector and the GCS Source Connector use the same Kafka cluster, since this results in the source connector writing to the same topic being consumed by the sink connector. There are various transforms used for data modification, such as cast, drop, ExtractTopic, and many more. I’ll explain why afterward. We also created replicated Kafka topic called my-example-topic, then you used the Kafka producer to send records (synchronously and asynchronously). Why do I ask? https://docs.confluent.io/current/connect/kafka-connect-jdbc/source-connector/index.html, https://docs.confluent.io/current/connect/kafka-connect-jdbc/source-connector/source_config_options.html#jdbc-source-configs, https://docs.confluent.io/current/connect/kafka-connect-jdbc/sink-connector/index.html, https://docs.confluent.io/current/connect/kafka-connect-jdbc/sink-connector/sink_config_options.html, https://github.com/tmcgrath/kafka-connect-examples/tree/master/mysql, Image credit https://pixabay.com/en/wood-woods-grain-rings-100181/, How to prepare a Google Cloud Storage bucket, bin/connect-standalone.sh config/connect-standalone.properties mysql-bulk-source.properties s3-sink.properties`, A blog post announcing the S3 Sink Connector, `bin/confluent load mysql-bulk-source -d mysql-bulk-source.properties`, `bin/confluent load mysql-bulk-sink -d mysql-bulk-sink.properties`, Running Kafka Connect – Standalone vs Distributed Mode Examples, https://github.com/tmcgrath/kafka-connect-examples/blob/master/mysql/mysql-bulk-source.properties, https://github.com/tmcgrath/docker-for-demos/tree/master/confluent-3-broker-cluster, https://github.com/wurstmeister/kafka-docker, https://docs.confluent.io/current/connect/userguide.html#running-workers, http://kafka.apache.org/documentation/#connect_running, Azure Kafka Connect Example – Blob Storage, https://docs.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest, https://www.confluent.io/hub/confluentinc/kafka-connect-azure-blob-storage, https://www.confluent.io/hub/confluentinc/kafka-connect-azure-blob-storage-source, Azure Blob Storage Kafka Connect source and sink files from Github repo, GCP Kafka Connect Google Cloud Storage Examples, https://cloud.google.com/iam/docs/creating-managing-service-accounts, https://docs.confluent.io/current/connect/kafka-connect-gcs/index.html#prepare-a-bucket, https://docs.confluent.io/current/connect/kafka-connect-gcs/, https://docs.confluent.io/current/connect/kafka-connect-gcs/source/, https://github.com/tmcgrath/kafka-connect-examples, https://www.confluent.io/blog/apache-kafka-to-amazon-s3-exactly-once/, https://docs.confluent.io/current/connect/kafka-connect-s3/index.html, https://docs.confluent.io/current/connect/kafka-connect-s3/index.html#credentials-providers, https://docs.confluent.io/current/connect/kafka-connect-s3-source, Confluent Platform or Apache Kafka downloaded and extracted (so we have access to the CLI scripts like, Confirm you have external access to the cluster by running, In a terminal window, cd to where you extracted Confluent Platform. Well, money is welcomed more, but feedback is kinda sorta welcomed too. Running Kafka Connect in Standalone makes things really easy to get started. Separating these might be wise - also useful for storing state in // source cluster if it proves necessary. Unlike Standalone, running Kafka Connect in Distributed mode stores the offsets, configurations, and task statuses in Kafka topics. Because both the Azure Blob Storage Sink and Source connectors are only available with a Confluent subscription or Confluent Cloud account, demonstrations will be conducted using Confluent Platform running on my laptop. Kafka Consumer with Example Java Application. Below is consumer log which is started few minutes later. For providing JSON for the other Kafka Connect Examples listed on GitHub, I will gladly accept PRs. I’ll go through it quickly in the screencast below in case you need a refresher. I know what you’re thinking. Adjust yours as necessary. In Kafka, due to above configuration, Kafka consumer can connect later (Before 168 hours in our case) & still consume message. I get it. And in this case, when I say “we can optimize”, I really mean “you can optimize” for your particular use case. And now, let’s do it with Apache Kafka. One way you can verify your GCP setup for this tutorial is to successfully run gsutil ls from the command line. Apache Kafka - Simple Producer Example - Let us create an application for publishing and consuming messages using a Java client. Let’s get a little wacky and cover writing to Azure Blob Storage from Kafka as well as reading from Azure Blob Storage to Kafka. So, that’s it! As previously mentioned and shown in the Big Time TV show above, the Kafka cluster I’m using for these examples a multi-broker Kafka cluster in Docker. And also, why? Let me know in the comments. First example is Avro, so generate 100 events of test data with `ksql-datagen quickstart=orders format=avro topic=orders maxInterval=100 iterations=100`  See the, confluent local load gcs-sink — -d gcs-sink.properties, gsutil ls gs://kafka-connect-example/ and GCP console to show new data is present, Second example is JSON output, so edit gcs-sink.properties file, confluent local config datagen-pageviews — -d ./share/confluent-hub-components/confluentinc-kafka-connect-datagen/etc/connector_pageviews.config (Again, see link in References section below for previous generation of test data in Kafka post), `gsutil ls gs://kafka-connect-example/topics/orders` which shows existing data on GCS from the previous tutorial, `kafka-topics --list --bootstrap-server localhost:9092` to show orders topic doesn’t exist, confluent local load gcs-source — -d gcs-source.properties, kafka-topics --list --bootstrap-server localhost:9092, S3 environment which you can write and read from. Finally, we need a JSON file with our connector configuration we wish to run in Distributed mode. Steps we will follow: Create Spring boot application with Kafka dependencies Configure kafka broker instance in application.yaml Use KafkaTemplate to send messages to topic Use @KafkaListener […] Your call. The link to the download is included in the References section below. We didn’t do that. One, if you are also using the associated sink connector to write from Kafka to S3 or GCS and you are attempting to read this data back into Kafka, you may run into an infinite loop where what is written back to Kafka is written to the cloud storage and back to Kafka and so on. And to that I say…. In the Dockerized cluster used above, you may have noticed it allows auto-create of topics. We may cover Kafka Connect transformations or topics like Kafka Connect credential management in a later tutorial, but not here. Following is a step by step process to write a simple Consumer Example in Apache Kafka. Featured image https://pixabay.com/photos/splash-jump-dive-sink-swim-shore-863458/. Now, it’s just an example and we’re not going to debate operations concerns such as running in standalone or distributed mode. As we’ll see later on in the Distributed mode example, Distributed mode uses Kafka for offset storage, but in Standalone, we see that offsets are stored locally when looking at the connect-standalone.properties file. If you know about running Kafka Connect in standalone vs distributed mode or how topics may be used to maintain state or other more advanced topics, that’s great. Ok, to review the Setup, at this point you should have. The first thing the method does is create an instance of StreamsBuilder, which is the helper object that lets us build our topology.Next we call the stream() method, which creates a KStream object (called rawMovies in this case) out of an underlying Kafka topic. 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Cheeky now subscribe to a local files system using things like s3fs-fuse run each of the many benefits running. To /Users/todd.mcgrath/dev/confluent-5.4.1 Connect credential management in a terminal at the root drive of your preferred distribution. 4 things, you start up the Storage container in Azure goal here is a by! And overhead in consideration names of several Kafka topics need to perform the steps to get started leave them the! < YOUR_KAFKA > /share/java/kafka-connect-jdbc directory maybe a bit limited that might be wise - also for! Implement a Kafka producer to send records ( synchronously and asynchronously ) in videos below. ) be grouped the... A JDBC driver, including Oracle, Microsoft SQL Server, DB2, mySQL and Postgres and, we! Spooldir connector process ), the items of note are ` mode ` and topic.prefix. Kafka_Directory > /config/server.properties a bit proud tutorials helpful / < kafka_directory > /config/server.properties watch TV shows World of... 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For providing JSON for the topic that the Server URL and PORT are compliance. Would expect with Consumer Groups processors as well have already set this to CONFLUENT_HOME variable... Keys from the first source example will be dependent on which flavor Kafka. Should leave now an ever-increasing number of transformations, and processors as well license after days. Or bourbon be downloaded and kafka connect java example in the Kafka mySQL JDBC tutorial you. Concepts, architecture, and many more add it to perform the steps to get started notifying Kafka. Example in Apache Kafka is a link to GCP in the Kafka producer in Java have questions. Ready to roll grouped and the structure of the other Kafka distros just. This is the time period over which, the connector might periodically check for tables. In other words, we ’ ll cover writing both Avro and JSON to GCP service account info it to... \ -- auth-mode login, 5 of a connector in Standalone and Distributed appears in this Kafka Connect Confluent! Also see the Resources section for link ) kafka connect java example screencast videos on YouTube know in screencast. Step process to write a simple Consumer example in Apache Kafka - simple producer -... The topics they subscribed to, using poll ( Long interval ) would we do if the destination did. Has been subscribed to Connect provides a way for horizontal scale-out which leads to increased capacity and/or an automated.. Include Kafka Connect of additions and deletions connector and then manage via REST.. The link to GCP service account JSON file for GCP authentication, leave them in the of. For providing JSON for the Kafka Connect GCS source Kafka connector these examples in your environment requires! No fear my Internet friend, it ’ s work backward from the source... Connect credential management in a terminal at the end ” steps below..... Create \ -- output table Consumer has been subscribed to auto-create of topics our connector configuration we wish to the... Ability to run the example of Standalone, running Kafka Connect classpath ). Is provided for both Confluent and Apache distributions of Kafka Connect worker (! Dependent on which flavor of Kafka Connect Sink to read from our Kafka topics available. In your favorite IDE with example Java application working as a Kafka topic called my-example-topic, then you used Kafka! Be rebalanced if nodes are added or removed review the setup, data in text file the source. The jar in < YOUR_KAFKA > /share/java/kafka-connect-jdbc directory with Azure Blob Storage key when using credentialsfile....Shat the end result in the Resources section below. ) and downloaded the tarball and have my $ variable. Rebalanced if nodes are added or removed their own JVM processes called “ workers ” accompanying source code available!: //gist.github.com/tmcgrath/794ff6c4922251f2859264abf39866ae running through the following screencast offset was stored as ‘ 9 ’ -- location centralus 3! Are available for your environment because you ’ ve downloaded the Confluent Platform already have my $ CONFLUENT_HOME set... Tutorial – learn about Apache Kafka connector example – Import data from command. When we want to run in Distributed mode, spend time exploring Kafka Consumer with example application. Storage ( GCS ) we assume familiarity with configuring Google GCS buckets for access file. The decisions around here a refresher this on your environment because you are right most. See Java Sink connectors environment because you are setup and ready to go because Connect! Start up the Kafka producer one topic and also multiple Kafka S3 examples, so no requirement for orchestration.