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Google Cloud Platform for Architects

Google Cloud Platform for Architects

By : Vitthal Srinivasan, Loonycorn Ravi, Judy Raj
3.1 (12)
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Google Cloud Platform for Architects

Google Cloud Platform for Architects

3.1 (12)
By: Vitthal Srinivasan, Loonycorn Ravi, Judy Raj

Overview of this book

Using a public cloud platform was considered risky a decade ago, and unconventional even just a few years ago. Today, however, use of the public cloud is completely mainstream - the norm, rather than the exception. Several leading technology firms, including Google, have built sophisticated cloud platforms, and are locked in a fierce competition for market share. The main goal of this book is to enable you to get the best out of the GCP, and to use it with confidence and competence. You will learn why cloud architectures take the forms that they do, and this will help you become a skilled high-level cloud architect. You will also learn how individual cloud services are configured and used, so that you are never intimidated at having to build it yourself. You will also learn the right way and the right situation in which to use the important GCP services. By the end of this book, you will be able to make the most out of Google Cloud Platform design.
Table of Contents (19 chapters)
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13
Logging and Monitoring

Working with the BigQuery console

BigQuery can be accessed using both GUI and command line. To access BigQuery using a GUI console:

  1. Click on the menu button on the top-left corner of the console and select BigQuery from the drop-down menu. You will encounter a new console looking something like this:
  1. Click on the COMPOSE QUERY button to enable the text area where queries can be written:
  1. To query a public dataset, paste the following text into the text area:
#standardSQL 
SELECT 
 weight_pounds, state, year, gestation_weeks 
FROM 
 `bigquery-public-data.samples.natality` 
ORDER BY weight_pounds DESC LIMIT 10; 
  1. Click the RUN QUERY button to run the query and observe the results, which will look like this:

Here as we can see, a public dataset named samples.natality is queried and 3.49 GB of data takes as low as 3.4 seconds to be processed. This speed and simplicity makes...

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