Managing Snowflake¶

These topics describes the tasks associated with using Snowflake.

• Virtual Warehouses — Key concepts and tasks for creating and using virtual warehouses to execute queries and perform DML operations, such as loading and unloading data:

  • Overview of Warehouses

  • Multi-cluster Warehouses

  • Warehouse Considerations

  • Working with Warehouses

  • Using the Query Acceleration Service

  • Monitoring Warehouse Load

• Databases, Tables & Views — Key concepts and tasks related to understanding and working with Snowflake databases and tables:

  • Understanding Snowflake Table Structures

  • Working with Temporary and Transient Tables

  • Working with External Tables

  • Overview of Views

  • Working with Secure Views

  • Working with Materialized Views

  • Table Design Considerations

  • Cloning Considerations

  • Data Storage Considerations

• Query Data in Snowflake — Key concepts and tasks for executing queries in Snowflake:

  • Working with Joins

  • Understanding How Snowflake Can Eliminate Redundant Joins

  • Working with Subqueries

  • Querying Hierarchical Data

  • Working with CTEs (Common Table Expressions)

  • Querying Semi-structured Data

  • Using Window Functions

  • Identifying Sequences of Rows That Match a Pattern

  • Using Sequences

  • Using Persisted Query Results

  • Computing the Number of Distinct Values

  • Estimating Similarity of Two or More Sets

  • Estimating Frequent Values

  • Estimating Percentile Values

  • Analyzing Queries Using Query Profile

  • Canceling Statements

• Date & Time Data — Reference information and examples for working with dates, times and timestamps, and time zones in Snowflake:

  • Date and Time Input / Output

  • Using Dates and Timestamps

• Semi-structured Data — Key concepts and tasks for working with JSON and other types of semi-structured data:

  • Introduction to Semi-structured Data

  • Supported Formats for Semi-structured Data

  • Considerations for Semi-structured Data Stored in VARIANT

  • Tutorial: JSON Basics

• Unstructured Data — Key concepts and tasks for working with unstructured data:

  • Introduction to Unstructured Data Support

  • Directory Tables

  • REST API for Unstructured Data Support

  • Sharing unstructured Data with a secure view

  • Troubleshooting Processing of Unstructured Data

• Binary Data — Reference information and examples for working with binary data in Snowflake:

  • Binary Input and Output

  • Using Binary Data

• Snowflake Time Travel & Fail-safe — Key concepts and tasks for understanding how Snowflake maintains access to deleted and modified data, and also how Snowflake enables data recovery in the event of loss:

  • Understanding & Using Time Travel

  • Understanding & Viewing Fail-safe

  • Storage Costs for Time Travel and Fail-safe

• Continuous Data Pipelines — Key concepts and tasks for transforming and optimizing loaded data for analysis:

  • Change Tracking Using Table Streams

  • Executing SQL Statements on a Schedule Using Tasks

• Introduction to Business Continuity & Disaster Recovery — Key concepts and tasks for replicating and failing over objects across multiple Snowflake accounts, as well as redirecting client connections, for business continuity and disaster recovery:

  • Introduction to Replication and Failover

  • Redirecting Client Connections

• Sample Data Sets — Key concepts and tasks for using the sample data sets provided with Snowflake:

  • Using the Sample Database

  • Sample Data: TPC-H

  • Sample Data: OpenWeatherMap — Deprecated