I want to create a topic in Kafka (kafka_2.8.0-0.8.1.1) through java. A topic is identified by its name. For each Topic, you may specify the replication factor and the number of partitions. When you are starting your kafka broker you can define a bunch of properties in conf/server.properties file. After a long search I found below code, Generally, It is not often that we need to delete the topic from Kafka. 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. 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. Effortlessly process massive amounts of data and get all the benefits of the broad … 3 replicas are common configuration. With HDInsight Kafka’s support for Bring Your Own Key (BYOK), encryption at rest is a one step process handled during cluster creation. But I want to create a topic through java api. The application used in this tutorial is a streaming word count. For a topic with replication factor N, Kafka can tolerate up to N-1 server failures without losing any messages committed to the log. But if there is a necessity to delete the topic then you can use the following command to delete the Kafka topic. 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. Of course, the replica number has to be smaller or equals to your broker number. The following are the source connector configuration properties that are used in association with the topic.creation.enable=true worker 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. We are deploying HDInsight 4.0 with Spark 2.4 to implement Spark Streaming and HDInsight 3.6 with Kafka NOTE: Apache Kafka … Kafka - Create Topic : All the information about Kafka Topics is stored in Zookeeper. Customers should use a user-assigned managed identity with the Azure Key Vault (AKV) to achieve this. Including default in topic.creation.groups results in a Warning. It reads text data from a Kafka topic, extracts individual words, and then stores the word and count into another Kafka topic. It is working fine if I create a topic in command prompt, and If I push message through java api. Existing connector implementations are normally available for common data sources and sinks with the option of creating ones own connector. kafka-topics --zookeeper localhost:2181 --topic test --delete If you need you can always create a new topic and write messages to that. 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. The partition number will be defined by the default settings in this same file. Kafka stream processing is often done using Apache Spark or Apache Storm. So, to create Kafka Topic, all this information has to be fed as arguments to the shell script, /kafka-topics.sh. The default group always exists and does not need to be listed in the topic.creation.groups property in the connector configuration. Always create a topic through java api listed in the topic.creation.groups property in the connector.! 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