Processing Data: Integrating Kafka with Python & Using Consumer Groups
Apache Kafka
| Intermediate
- 12 videos | 1h 24m 27s
- Includes Assessment
- Earns a Badge
Producers and consumers are applications that write events to and read events from Kafka. In this course, you will focus on integrating Python applications with a Kafka environment, implementing consumer groups, and tweaking Kafka configurations. Begin by connecting to Kafka from Python. You will produce to and consume messages from a Kafka topic using Python. Next, discover how to tweak Kafka broker configurations. You will place limits on the size of messages and disable deletion of topics. Then, publish messages to partitioned topics and explore the use of partitioning algorithms to determine the placement of messages on partitions. Explore consumer groups, which allow a set of consumers to process messages published to partitioned Kafka topics in parallel - without any duplication of effort. Finally, learn different ways to optimize Kafka's performance, using configurations for brokers and topics, as well as producer and consumer apps.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this courseCreate a kafka producer and consumer in pythonProcess messages at the consumer using pythonConfigure kafka brokers using properties filesEnable and disable autogeneration of topicsPublish fake data to a kafka topic
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Write out data to a partitioned kafka topic and configure partition splitsRecognize the use cases of consumer groupsCreate and use a consumer groupDescribe the relationship between consumer groups and partitionsRecognize the different options available to improve the performance of a kafka environmentSummarize the key concepts covered in this course
IN THIS COURSE
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1m 32s
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11m 49s
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6m 16s
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9m 48s
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6m 54s
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10m 12s
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7m 22s
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5m 54s
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10m 40s
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6m 49s
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4m 17s
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2m 55s
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