Published 9/2023
Created by DE Simplified
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 27 Lectures ( 1h 35m ) | Size: 805 MB
Automate DDL & DML SQL Generation For JSON Data Files & Save 95% Manual Effort
What you’ll learn
How to automate JSON Data ingestion from named stages to snowflake table using Snowpark Python API
How to use infer-schema to automate JSON data ingestion activities.
How to build automation utilities using Snowpark Python API
How to build end to end data onboarding tool using Snowpark Python API
Requirements
Basic working knowledge with Python Programming Language
Working knowledge with Snowflake Cloud Data Warehouse
Basic working knowledge with Snowpark Python API
Description
In many situations, Snowflake gets lots of JSON data files and JSON entities, and data development teams write complex stored procedures to make DDL and DML SQL scripts to process and flatten the JSON data entities. Creating & building DDL & DML statement manually is a time consuming and error prone process. This also hampers overall development process.This tutorial helps you create a simple and sophisticated utility using Snowflake’s Snowpark Python API. This python utility uses Infer-schema table function along with Python JSON library to figure out JSON structures and helps to create all your landing/bronze/silver layer snowflake object requirements. With Python-Jinja2 templates, it doesn’t just create DDL commands; it also makes copy commands, streams, tasks, and stored procedures. This makes it easy to automate moving data from your external storage to your bronze/silver layers.This tutorial will explain the current challenges and how to solve this problemWe’ll look at the Infer Schema Table Function and its limits in detecting JSON structures.We’ll discuss the usual patterns and repetition when making DDL & DML statements for JSON entities.You’ll learn how to create a simple data ingestion solution using Snowpark and Python without writing any SQL codeWe’ll show you how to put this design into practice with the Snowpark Python API.Finally, we’ll demonstrate the whole process using multiple JSON data examples, and you’ll see how it can quickly load a large number of records in under 2 minutes.
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