Lynn reviews an interactive Hadoop Spark architecture using GCP services.
- [Instructor] Now, here we've got Hadoop Architecture…running on the Google Cloud.…And what I think is of note here, is that you have,…on the left side, both batch and streaming.…And notice, that for the stream data,…the recommended architecture is to use Cloud Pub/Sub.…Of course, if you had requirements around guarantees…of messages in order, do you know what you'd use?…Probably Kafka.…So, you have different options that you can use…for the stream ingest layer.…The batch ingest layer, on the upper left-hand side,…is just using Google Cloud storage.…
Now, the data's coming in, and it's being…aggregated by Google's Cloud data flow service.…What this is, is a productized implementation of…yet another open source set of libraries called Apache Beam.…This is a relatively new service,…and it allows for sophisticated data pipelines…that are scalable to be created.…This is in beta at the time of this recording,…so if you're building a pipeline on the Google Cloud,…you're going to want to look at data flow, as well.…
Author
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
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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: Spark architecture for interactive analytics