August 2022
Intermediate to advanced
465 pages
12h 20m
English
Content preview from Snowflake: The Definitive Guide
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Chapter 4. Exploring Snowflake SQL Commands, Data Types, and Functions
As we learned in previous chapters, Snowflake was built to store data in an optimized, compressed, columnar format within a relational database. Snowflake’s data end users need to access the stored data and be able to give instructions to perform tasks, call functions, and execute queries on the data. The way that can be accomplished is with the standard programming language for relational databases, Structured Query Language (SQL). Snowflake supports SQL:ANSI, the most common standardized version of SQL. In addition to SQL support for structured data, Snowflake offers native support for semi-structured data formats such as JSON and XML. Snowflake also supports unstructured data.
The main focus of this chapter is on learning the fundamentals of using Snowflake worksheets to execute a variety of SQL commands using different data types and functions. Other than using worksheets in the Snowflake web UI, it is possible to use a Snowflake-native command-line client, known as SnowSQL, to create and execute SQL commands. More detail about SnowSQL will be provided in Chapter 6.
Besides connecting to Snowflake via the web UI or SnowSQL, you can use ODBC and JDBC drivers to access Snowflake data through external applications such as Tableau and Looker. We’ll explore connections to Tableau and Looker in Chapter 12. Native connectors such as Python and Spark can also be used to develop applications for connecting to Snowflake. ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.