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    Snowpark : Data Engineering With Snowflake.

    Posted By: ELK1nG
    Snowpark : Data Engineering With Snowflake.

    Snowpark : Data Engineering With Snowflake.
    Published 2/2023
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 1.89 GB | Duration: 4h 18m

    Learn fundamentals of Snowflake-snowpark API.

    What you'll learn

    Connect Snowpark API with snowflake.

    Basic read and write operations using Snowpark.

    Do's and Don'ts while using Snowpark.

    Building data components and basic data pipeline.

    Requirements

    Basic knowledge on python.

    Description

    What is Snowpark ?With Snowpark, Snowflake allows developers to write code in their preferred language.Along with Snowflake’s original SQL interface now snowflake allows you to write code in,         1. Python         2. Scala         3. JavaSome of the key features of Snowpark are,Your code will be pushed to snowflake leveraging the compute power of snowflake warehouses.You will not end up exporting data to different environment but rather your code is shipped to the data.You can build complex data pipelines or data products using SnowparkSnowpark also address below overheads in conventional data pipelines,Long startup time of node clusters: Systems like Hadoop and Spark requires cluster of nodes to process data. Most of the time it takes 5-10 minutes to just start the cluster. In case of Snowpark we will be using snowflake warehouse to process our data.Problem of small files , Problem of using right joins to shuffle data across nodes, Problem of garbage collection. uncertainty when the compute nodes goes down.All the above problems are well handled with Snowpark.What you will learn ?You will learn the basics of SNOWPARK API.     > Basic read and write operations.    > Read data from s3 and load that to snowflake table.    > We will do deep analysis of how SNOWPARK API works.    > Do's and Don'ts of SNOWPARK.    > Build data components to process data.    > Build data pipeline to process data.

    Overview

    Section 1: Introduction

    Lecture 1 Snowpark introduction

    Lecture 2 Test connection

    Lecture 3 Snowpark-demo part 1

    Lecture 4 Snowpark-demo part2

    Section 2: Snowpark– Read operations

    Lecture 5 Create dataframe–part1

    Lecture 6 Create dataframe–part2

    Lecture 7 Apply schema

    Lecture 8 Create dataframe–part3

    Lecture 9 Create dataframe–part4

    Lecture 10 Read from table–part1

    Lecture 11 Read from s3 csv

    Lecture 12 Read from s3 json

    Section 3: Assignments– Read operation

    Section 4: Snowpark–-Write operations

    Lecture 13 Basic write operation

    Lecture 14 Write from s3 to table–json

    Lecture 15 Write from s3 to table–csv

    Section 5: Assignments – write operations

    Section 6: Assignments– Read and write semistructured data.

    Section 7: Snowpark–Copy commands

    Lecture 16 Write using copy

    Section 8: Transformations and query

    Lecture 17 Aggregation in snowpark

    Lecture 18 Group by –part 1

    Lecture 19 Group by –part 2

    Lecture 20 Window function

    Lecture 21 Joins

    Lecture 22 Using in clause

    Section 9: Assignments–-Transformation and query

    Lecture 23 Prepare data

    Section 10: Building generic components

    Lecture 24 Download resources

    Lecture 25 Create snow connection component– part1

    Lecture 26 Create snow connection component–part2

    Lecture 27 Copy to snowflake table

    Lecture 28 Creating configuration file

    Lecture 29 Collect rejects

    Lecture 30 Copy semi structured data part 1

    Lecture 31 Copy semi structured data part 2

    Lecture 32 Map columns

    Lecture 33 Map columns solution

    Lecture 34 Summary

    Developers who want's to lean Snowflake-Snowpark.