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Please use ide. Skip to content. Change Language. Related Articles. Why Apache Kafka is so Fast? How to install Jupyter Notebook on Windows? View Discussion. Improve Article. Save Article. Like Article. Last Updated : 28 Jun, Next Why Apache Kafka is so Fast? Here is a summary of some notable changes: KIP adds support for prefixed ACLs, simplifying access control management in large secure deployments.
Bulk access to topics, consumer groups or transactional ids with a prefix can now be granted using a single rule. Access control for topic creation has also been improved to enable access to be granted to create specific topics or topics with a prefix. Host name verification is now enabled by default for SSL connections to ensure that the default SSL configuration is not susceptible to man-in-the-middle attacks. You can disable this verification if required.
You can now dynamically update SSL truststores without broker restart. With this new feature, you can store sensitive password configs in encrypted form in ZooKeeper rather than in cleartext in the broker properties file. The replication protocol has been improved to avoid log divergence between leader and follower during fast leader failover. We have also improved resilience of brokers by reducing the memory footprint of message down-conversions.
By using message chunking, both memory usage and memory reference time have been reduced to avoid OutOfMemory errors in brokers. Kafka clients are now notified of throttling before any throttling is applied when quotas are enabled. This enables clients to distinguish between network errors and large throttle times when quotas are exceeded. We have added a configuration option for Kafka consumer to avoid indefinite blocking in the consumer. We have dropped support for Java 7 and removed the previously deprecated Scala producer and consumer.
Kafka Connect includes a number of improvements and features. KIP enables you to control how errors in connectors, transformations and converters are handled by enabling automatic retries and controlling the number of errors that are tolerated before the connector is stopped. More contextual information can be included in the logs to help diagnose problems and problematic messages consumed by sink connectors can be sent to a dead letter queue rather than forcing the connector to stop. KIP adds a new extension point to move secrets out of connector configurations and integrate with any external key management system.
The placeholders in connector configurations are only resolved before sending the configuration to the connector, ensuring that secrets are stored and managed securely in your preferred key management system and not exposed over the REST APIs or in log files. Scala users can have less boilerplate in their code, notably regarding Serdes with new implicit Serdes. Message headers are now supported in the Kafka Streams Processor API, allowing users to add and manipulate headers read from the source topics and propagate them to the sink topics.
Windowed aggregations performance in Kafka Streams has been largely improved sometimes by an order of magnitude thanks to the new single-key-fetch API. We have further improved unit testibility of Kafka Streams with the kafka-streams-testutil artifact. Here is a summary of some notable changes: Kafka 1. ZooKeeper session expiration edge cases have also been fixed as part of this effort. Controller improvements also enable more partitions to be supported on a single cluster.
Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Read, write, and process streams of events in a vast array of programming languages. Large ecosystem of open source tools: Leverage a vast array of community-driven tooling.
Support mission-critical use cases with guaranteed ordering, zero message loss, and efficient exactly-once processing. Thousands of organizations use Kafka, from internet giants to car manufacturers to stock exchanges.
More than 5 million unique lifetime downloads. Kafka is one of the five most active projects of the Apache Software Foundation, with hundreds of meetups around the world.
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