Understand Apache Kafka service guarantees and understand when you need this type of streaming ingest service versus others that are available.
- [Instructor] To understand just a bit more…about core Kafka architecture,…take a look at this drawing…and consider some of the key features.…So, Kafka clusters, as I mentioned previously,…generally consist of multiple servers…with multiple processes.…They are associated to consumer groups…who also have multiple processes running on them.…Now, some of the features of Kafka…make it really appealing as an ingest pipeline…for modern Hadoop architectures.…
Those include both Pub/Sub and message queuing.…Many of the ingest services offer only Pub/Sub,…like Google Cloud Pub/Sub,…or only queuing, such as message queuing services.…In addition, in using Kafka,…you have guarantees around in-order messages,…fault tolerance, and of course, support for streaming.…For more information about Kafka,…I found a great resource to be the core Kafka Apache site.…You can go to this link to get to that site…and see examples and more information…about setting up Kafka.…
Author
Lynn Langit
Released
7/5/2017- Relate which file system is typically used with Hadoop.
- Explain the differences between Apache and commercial Hadoop distributions.
- Cite how to set up IDE - VS Code + Python extension.
- Relate the value of Databricks community edition.
- Compare YARN vs. Standalone.
- Review various streaming options.
- Recall how to select your programming language.
- Describe the Databricks environment.
Skill Level Intermediate
Duration
Views
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Introduction
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Welcome53s
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1. Hadoop Core Fundamentals
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Modern Hadoop1m 53s
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Hadoop libraries1m 23s
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Run Hadoop job on GCP1m 52s
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Databricks on AWS2m 32s
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2. Setting Up a Hadoop Dev Environment
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Load data into tables1m 51s
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3. Hadoop Batch Processing
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Processing options1m 2s
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Resource coordinators1m 30s
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Compare YARN vs. Standalone1m 30s
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4. Fast Hadoop Options
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Big data streaming1m 57s
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Streaming options1m 10s
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Apache Spark basics1m 46s
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Spark use cases1m 2s
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5. Spark Basics
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Apache Spark libraries3m 24s
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Spark shell1m 53s
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6. Using Spark
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Tour the notebook5m 29s
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Import and export notebooks2m 56s
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Calculate pi on Spark8m 19s
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Import data2m 50s
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Transformations and actions4m 43s
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Caching and the DAG6m 49s
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7. Spark Libraries
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Spark SQL8m 34s
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SparkR6m 11s
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Spark ML: Preparing data4m 21s
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Spark ML: Building the model3m 50s
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MXNet or TensorFlow2m 30s
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Spark with GraphX2m 12s
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8. Spark Streaming
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Spark streaming4m 21s
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9. Hadoop Streaming
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Pub/Sub on GCP3m 59s
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Apache Kafka1m 26s
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Kafka architecture1m 6s
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Apache Storm1m 30s
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Storm architecture1m 36s
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10. Modern Hadoop Architectures
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Conclusion
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Next steps26s
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Video: Kafka architecture