Lynn reviews a Hadoop architecture which is domain specific, for bioinformatics, using ADAM with Hadoop Spark on AWS.
- [Instructor] In this next scenario,…we're going to look at genomic variant pipelining…that includes Hadoop and Spark.…In earlier movies in this course,…we talked about augmenting the Hadoop library,…such as Spark,…with additional open source or commercial libraries…and actually showed and talked a little bit…about ADAM for genomic processing.…You may remember that the ADAM set of libraries…which wrap around Spark…include domain specific implementations of items…such as schemas for the incoming files…which are of a specific format.…
You can see SAM, BAM, or VCF.…These files will be coming in…from genomic sequencing machines…such as those made by Illumina.…These is a simplified pipeline.…You see the source files coming directly into Amazon S3.…This is an Amazon implementation…and then the focus here is showing…that the ADAM libraries are running on top of…an Amazon EMR cluster which is running Spark.…In the real world, you would probably have a number…of pre-processing steps before the files were processed…by the Spark cluster.…
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: Spark architecture for genomics