Oreilly - Kafka Streams in Action, Second Edition, Video Edition

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Oreilly - Kafka Streams in Action, Second Edition, Video Edition

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文件列表

  • 090. Chapter 14. Testing.mp4 101.3 MB
  • 032. Chapter 4. Consuming records with the KafkaConsumer.mp4 77.3 MB
  • 022. Chapter 3. What is a schema, and why do you need one.mp4 76.5 MB
  • 064. Chapter 9. Windowing and timestamps.mp4 69.7 MB
  • 053. Chapter 7. Adding stateful operations to Kafka Streams.mp4 67.2 MB
  • 084. Chapter 12. Using Spring to build Kafka-enabled applications.mp4 65.2 MB
  • 055. Chapter 7. State stores in Kafka Streams.mp4 51.1 MB
  • 042. Chapter 5. Building and deploying your own connector.mp4 50.9 MB
  • 031. Chapter 4. Producing records with the KafkaProducer.mp4 47.2 MB
  • 050. Chapter 6. Choosing which events to process.mp4 45.8 MB
  • 088. Chapter 13. Learning about Interactive Queries.mp4 44.6 MB
  • 062. Chapter 8. Table joins.mp4 44.3 MB
  • 054. Chapter 7. Stream-stream joins.mp4 43.5 MB
  • 077. Chapter 11. More about streaming queries.mp4 43.0 MB
  • 048. Chapter 6. Masking credit card numbers and tracking purchase rewards in a retail sales setting.mp4 40.6 MB
  • 099. appendix C. Protocol Buffers.mp4 37.4 MB
  • 100. appendix C. JSON Schema.mp4 35.9 MB
  • 072. Chapter 10. Digging deeper into the Processor API with a stock analysis processor.mp4 35.1 MB
  • 033. Chapter 4. Exactly-once delivery in Kafka.mp4 34.6 MB
  • 047. Chapter 6. Hello World for Kafka Streams.mp4 31.8 MB
  • 071. Chapter 10. The Processor API.mp4 29.3 MB
  • 085. Chapter 12. Spring Kafka Streams.mp4 29.1 MB
  • 014. Chapter 2. Segments.mp4 28.9 MB
  • 076. Chapter 11. ksqlDB.mp4 28.4 MB
  • 078. Chapter 11. Persistent vs. push vs. pull queries.mp4 24.0 MB
  • 081. Chapter 11. ksqlDB advanced features.mp4 23.9 MB
  • 012. Chapter 2. Topics and partitions.mp4 22.4 MB
  • 039. Chapter 5. Getting started with Kafka Connect.mp4 22.3 MB
  • 066. Chapter 9. Final windowed results.mp4 21.9 MB
  • 023. Chapter 3. Subject name strategies.mp4 21.7 MB
  • 003. Chapter 1. Welcome to the Kafka event streaming platform.mp4 19.9 MB
  • 073. Chapter 10. Data-driven aggregation.mp4 19.5 MB
  • 035. Chapter 4. Handling multiple event types in a single topic.mp4 19.2 MB
  • 092. appendix A. Schema compatibility workshop.mp4 18.8 MB
  • 027. Chapter 3. Schema Registry (de)serializers.mp4 18.7 MB
  • 057. Chapter 8. The KTable API.mp4 18.5 MB
  • 026. Chapter 3. Schema references and multiple events per topic.mp4 18.3 MB
  • 013. Chapter 2. Sending your first messages.mp4 18.2 MB
  • 037. Chapter 5. Kafka Connect.mp4 16.7 MB
  • 017. Chapter 2. Leaders and followers.mp4 15.8 MB
  • 060. Chapter 8. KTable aggregations.mp4 15.7 MB
  • 040. Chapter 5. Applying Single Message Transforms.mp4 15.4 MB
  • 105. appendix D. Processing records.mp4 15.0 MB
  • 079. Chapter 11. Creating Streams and Tables.mp4 14.5 MB
  • 041. Chapter 5. Adding a sink connector.mp4 14.3 MB
  • 083. Chapter 12. Spring Kafka.mp4 14.3 MB
  • 024. Chapter 3. Schema compatibility.mp4 13.9 MB
  • 102. appendix D. Consumer and producer clients in Kafka Streams.mp4 13.7 MB
  • 025. Chapter 3. Schema references.mp4 13.1 MB
  • 006. Chapter 1. Introducing the Apache Kafka event streaming platform.mp4 13.1 MB
  • 104. appendix D. Threads in Kafka Streams StreamThread.mp4 13.0 MB
  • 080. Chapter 11. Schema Registry integration.mp4 12.3 MB
  • 103. appendix D. Assigning, distributing, and processing events.mp4 12.0 MB
  • 007. Chapter 1. A concrete example of applying the Kafka event streaming platform.mp4 10.9 MB
  • 065. Chapter 9. Handling out order data with grace literally.mp4 10.8 MB
  • 068. Chapter 9. The TimestampExtractor.mp4 10.0 MB
  • 093. appendix A. Forward compatibility.mp4 9.9 MB
  • 030. Chapter 4. Kafka clients.mp4 9.8 MB
  • 036. Chapter 4. Summary.mp4 9.0 MB
  • 018. Chapter 2. Checking for a healthy broker.mp4 8.9 MB
  • 052. Chapter 7. Streams and state.mp4 8.8 MB
  • 098. appendix C. Working with Avro, Protobuf, and JSON Schema.mp4 8.7 MB
  • 049. Chapter 6. Interactive development.mp4 8.5 MB
  • 021. Chapter 3. Schema Registry.mp4 8.5 MB
  • 015. Chapter 2. Tiered storage.mp4 8.4 MB
  • 082. Chapter 11. Summary.mp4 8.3 MB
  • 051. Chapter 6. Summary.mp4 8.2 MB
  • 044. Part 3.mp4 8.0 MB
  • 028. Chapter 3. Serialization without Schema Registry.mp4 7.8 MB
  • 061. Chapter 8. GlobalKTable.mp4 7.6 MB
  • 074. Chapter 10. Integrating the Processor API and the Kafka Streams API.mp4 7.4 MB
  • 034. Chapter 4. Using the Admin API for programmatic topic management.mp4 7.4 MB
  • 087. Chapter 13. Kafka Streams Interactive Queries.mp4 7.3 MB
  • 094. appendix A. Full compatibility.mp4 7.3 MB
  • 038. Chapter 5. Integrating external applications into Kafka.mp4 6.4 MB
  • 009. Chapter 2. Kafka brokers.mp4 6.4 MB
  • 069. Chapter 9. Stream time.mp4 6.3 MB
  • 067. Chapter 9. Timestamps in Kafka Streams.mp4 6.0 MB
  • 016. Chapter 2. Cluster metadata.mp4 5.5 MB
  • 005. Chapter 1. An event stream example.mp4 5.5 MB
  • 091. Chapter 14. Summary.mp4 5.5 MB
  • 058. Chapter 8. KTables are stateful.mp4 5.1 MB
  • 008. Chapter 1. Summary.mp4 5.1 MB
  • 029. Chapter 3. Summary.mp4 4.7 MB
  • 011. Chapter 2. Fetch requests.mp4 4.7 MB
  • 020. Part 2.mp4 4.2 MB
  • 004. Chapter 1. What is an event.mp4 4.2 MB
  • 045. Chapter 6. Developing Kafka Streams.mp4 4.2 MB
  • 010. Chapter 2. Produce requests.mp4 4.1 MB
  • 063. Chapter 8. Summary.mp4 3.5 MB
  • 070. Chapter 9. Summary.mp4 3.4 MB
  • 086. Chapter 12. Summary.mp4 3.4 MB
  • 059. Chapter 8. The KTable API.mp4 3.3 MB
  • 101. appendix D. Understanding Kafka Streams architecture.mp4 3.2 MB
  • 002. Part 1.mp4 3.0 MB
  • 001. Part 1.mp4 3.0 MB
  • 056. Chapter 7. Summary.mp4 2.9 MB
  • 096. appendix B. Confluent command-line interface.mp4 2.7 MB
  • 046. Chapter 6. Kafka Streams DSL.mp4 2.6 MB
  • 043. Chapter 5. Summary.mp4 2.4 MB
  • 089. Chapter 13. Summary.mp4 2.4 MB
  • 075. Chapter 10. Summary.mp4 2.3 MB
  • 019. Chapter 2. Summary.mp4 1.9 MB
  • 095. appendix B. Confluent resources.mp4 1.9 MB
  • 097. appendix B. Confluent local.mp4 794.4 kB

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