Book Image

Google Cloud Platform for Architects

By : Vitthal Srinivasan, Loonycorn , Judy Raj
Book Image

Google Cloud Platform for Architects

By: Vitthal Srinivasan, Loonycorn , 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)
13
Logging and Monitoring

Legacy versus standard SQL

BigQuery, like many other GCP services, has been widely used within Google for several years. That usage initially relied on a non-standard variant of SQL, which is now called legacy SQL. Legacy SQL is pretty powerful and pretty easy to use in some specific cases, but it has a big downside: it is not standard!

To remedy that, BigQuery has added support for standard SQL 2011, with some extensions that have to do with nested and repeated fields. The query examples shown next are in standard SQL.

How can you tell at a glance whether a query is written in legacy SQL or standard SQL? Just look at the syntax used to specify tables or project names.

  • In legacy SQL: Use square brackets to start and end the table name, and use a colon (:) to delimit dataset and table names:
[bigquery-public-data:samples:natality]
  • In standard SQL: Use the backtick character...