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Bigtable: A Distributed Storage System for Structured Data
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In recent years, we have seen an overwhelming number of TV commercials that promise that the Cloud can help with many problems, including some family issues. What stands behind the terms “Cloud” and “Cloud Computing,” and what we can actually expect from this phenomenon? A group of students of the Computer Systems Technology department and Dr. T. Malyuta, whom has been working with the Cloud technologies since its early days, will provide an overview of the business and technological aspects of the Cloud.
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In recent years, we have seen an overwhelming number of TV commercials that promise that the Cloud can help with many problems, including some family issues. What stands behind the terms “Cloud” and “Cloud Computing,” and what we can actually expect from this phenomenon? A group of students of the Computer Systems Technology department and Dr. T. Malyuta, whom has been working with the Cloud technologies since its early days, will provide an overview of the business and technological aspects of the Cloud.
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Bigtable: A Distributed Storage System for Structured Data
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In recent years, we have seen an overwhelming number of TV commercials that promise that the Cloud can help with many problems, including some family issues. What stands behind the terms “Cloud” and “Cloud Computing,” and what we can actually expect from this phenomenon? A group of students of the Computer Systems Technology department and Dr. T. Malyuta, whom has been working with the Cloud technologies since its early days, will provide an overview of the business and technological aspects of the Cloud.
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In recent years, we have seen an overwhelming number of TV commercials that promise that the Cloud can help with many problems, including some family issues. What stands behind the terms “Cloud” and “Cloud Computing,” and what we can actually expect from this phenomenon? A group of students of the Computer Systems Technology department and Dr. T. Malyuta, whom has been working with the Cloud technologies since its early days, will provide an overview of the business and technological aspects of the Cloud.
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This is an introductory presentation given at DevFest Madrid 2010 by Google Developer Advocate Chris Schalk. It introduces new Google cloud technologies: Google Storage, Google Prediction API and BigQuery.
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Data Lake, Business Intelligence, Enterprise Data Warehouse, Big Data Pipeline, Online Machine Learning, Lambda Architecture, Streaming, Spark, Kafka, Storm, Flink, Hadoop, Mesos and SMACK stack are some of the things you hear about when you want to dive into building a data pipeline. The Big Data Landscape cannot fit on a single screen as seen in the presentation. This is in addition to all the Big Data & Machine Learning offerings AWS has been introducing over the past few years which address many pain points highlighted by the various communities and help you get up and running faster. The objective of this talk is to provide the audience with a framework which helps them define their pipeline problems, isolate components and pick the right tools for the right job. We will talk about: 1. A consistent definition of BIG in big data 2. The lineage of fundamental tools in the ecosystem 3. First principles of a big data pipeline based on the lambda (not lambda functions) and kappa architectures 4. Distinguishing between big data and online machine learning pipelines 5. Technology choices based on first principles, open source solutions and AWS offerings 6. Demo: Serverless, Managed Big Data Pipeline and real-time dashboard on AWS (orchestrated via Terraform) Presented at: https://www.meetup.com/Vancouver-Amazon-Web-Services-User-Group/events/245946651/
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Many Spring projects exist that leverage XML for their configuration and bean definitions. Most Java web applications use a web.xml to configure their servlets, filters and listeners. This session shows you how you can eliminate XML by configuring your Spring beans with JavaConfig and annotations. It also shows how you can remove your web.xml and configure your web components with Java.
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Google's BigTable
1.
Google’s BigTable Out
of the Slipstream :: July 3, 2008
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Architecture GFS SSTables
Tables Chubby Clusters Tablets Tablet Servers
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Table Structure Columns
Timestamp / version Key Table Indexes Column Families Expando Columns
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Google App Engine
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Indexes
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Data Viewer
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Data Viewer
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Data Viewer
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