Existing connector implementations are normally available for common data sources and sinks with the option of creating ones own connector. When you are starting your kafka broker you can define a bunch of properties in conf/server.properties file. We are deploying HDInsight 4.0 with Spark 2.4 to implement Spark Streaming and HDInsight 3.6 with Kafka NOTE: Apache Kafka … The default group always exists and does not need to be listed in the topic.creation.groups property in the connector configuration. A topic is identified by its name. The application used in this tutorial is a streaming word count. 3 replicas are common configuration. The following are the source connector configuration properties that are used in association with the topic.creation.enable=true worker For each Topic, you may specify the replication factor and the number of partitions. Kafka - Create Topic : All the information about Kafka Topics is stored in Zookeeper. Kafka integration with HDInsight is the key to meeting the increasing needs of enterprises to build real time pipelines of a stream of records with low latency and high through put. But if there is a necessity to delete the topic then you can use the following command to delete the Kafka topic. I want to create a topic in Kafka (kafka_2.8.0-0.8.1.1) through java. Kafka Connectors are ready-to-use components, which can help import data from external systems into Kafka topics and export data from Kafka topics into external systems. But I want to create a topic through java api. It is working fine if I create a topic in command prompt, and If I push message through java api. Of course, the replica number has to be smaller or equals to your broker number. kafka-topics --zookeeper localhost:2181 --topic test --delete So, to create Kafka Topic, all this information has to be fed as arguments to the shell script, /kafka-topics.sh. HDInsight Realtime Inference In this example, we can see how to Perform ML modeling on Spark and perform real time inference on streaming data from Kafka on HDInsight. Generally, It is not often that we need to delete the topic from Kafka. One of the property is auto.create.topics.enable if you set this to true (by default) kafka will automatically create a topic when you send a message to a non existing topic. Kafka version 1.1.0 (in HDInsight 3.5 and 3.6) introduced the Kafka Streams API. Easily run popular open source frameworks—including Apache Hadoop, Spark, and Kafka—using Azure HDInsight, a cost-effective, enterprise-grade service for open source analytics. If you need you can always create a new topic and write messages to that. The partition number will be defined by the default settings in this same file. Effortlessly process massive amounts of data and get all the benefits of the broad … Including default in topic.creation.groups results in a Warning. With HDInsight Kafka’s support for Bring Your Own Key (BYOK), encryption at rest is a one step process handled during cluster creation. Kafka stream processing is often done using Apache Spark or Apache Storm. After a long search I found below code, For a topic with replication factor N, Kafka can tolerate up to N-1 server failures without losing any messages committed to the log. Customers should use a user-assigned managed identity with the Azure Key Vault (AKV) to achieve this. It reads text data from a Kafka topic, extracts individual words, and then stores the word and count into another Kafka topic.