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Snowflake Snowpark Application Developer

Building Scalable Data Applications with Snowpark on Snowflake
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Duration

1 Day

Level

Intermediate Level

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Official Course

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This one-day course covers key Snowpark features for developing applications in Snowflake and is intended for
practitioners who will be building Snowpark application solutions in Snowflake. The emphasis of this course is
on a variety of application developer capabilities rather than core programming skills. The course consists of
lectures, demos, labs, and discussions.

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• Data Engineers
• Data Scientists
• Data Application Developers
• Database Architects
• Database Administrators
• Data Analysts with programming experience

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• What is Snowpark?
• Snowpark Uses
• Snowpark Architecture
• Snowpark Setup

• DataFrames are Immutable
• A Table is a Mutable DataFrame
• Creating a Table
• Deleting Rows From a Table
• Updating Rows in a Table
• Merging Rows in a Table
• Understanding Views

  • Creating and Registering UDFs
  • Creating and Using Python User-defined Table Functions (UDTFs)

• Lambda Example
• Anonymous Python Stored Procedures: Really?
• CALL (with Anonymous Procedure)
• Using sproc(… ) as a Decorator
• Authoring a Stored Procedure Using DDL

• Additional Overhead and Costs
• Steps to using Snowsight Python Worksheets
• Test Handler

• Proper Testing
• Create a Non-Vectorized UDF and Use it in a Transformation
• Test a Non-Vectorized UDF and Measure Performance
• Create a Vectorized UDF and Use it in a Transformation

• Steps in Processing Unstructured Data
• Stages
• Directory Tables
• Access URLs
• Encryption for Internal Stages
• Processing Unstructured Data in UDFs
• Registering the UDF
• Invoking the UDF
• Unstructured Data Best Practices

• Logging Introduction
• Log Entries vs Trace Events
• Event Tables
• Setting Log Levels
• Logging From Objects
• Emitting Trace Events
• Querying Over Log Messages

• Creating a Notebook
• Notebook Cell Basics
• Running Notebook Cells
• Editing Cells
• Import Python Packages
• Running SQL and Python Cells

• Snowflake Notebooks
• Introduction to Pandas on Snowflake

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  • Completion of “Snowpark DataFrame Programming” or prior knowledge and experience with DataFrame
    programming: Creation, Transformation, Actions, PySpark, UDFs, and Stored Procedures.
  • Prior knowledge and experience with Snowflake accounts, roles, virtual warehouses, databases, tables,
    and views.
  • Previous data warehouse knowledge and experience.
  • Proficiency in writing code in Python.
  • Familiarity with Snowflake objects and basic SQL.
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