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Data Ingestion with Python Cookbook

Data Ingestion with Python Cookbook

By : Gláucia Esppenchutz
4.5 (4)
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Data Ingestion with Python Cookbook

Data Ingestion with Python Cookbook

4.5 (4)
By: Gláucia Esppenchutz

Overview of this book

Data Ingestion with Python Cookbook offers a practical approach to designing and implementing data ingestion pipelines. It presents real-world examples with the most widely recognized open source tools on the market to answer commonly asked questions and overcome challenges. You’ll be introduced to designing and working with or without data schemas, as well as creating monitored pipelines with Airflow and data observability principles, all while following industry best practices. The book also addresses challenges associated with reading different data sources and data formats. As you progress through the book, you’ll gain a broader understanding of error logging best practices, troubleshooting techniques, data orchestration, monitoring, and storing logs for further consultation. By the end of the book, you’ll have a fully automated set that enables you to start ingesting and monitoring your data pipeline effortlessly, facilitating seamless integration with subsequent stages of the ETL process.
Table of Contents (17 chapters)
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1
Part 1: Fundamentals of Data Ingestion
9
Part 2: Structuring the Ingestion Pipeline

Ingesting partitioned data

The practice of partitioning data is not recent. It was implemented in databases to distribute data across multiple disks or tables. Actually, data warehouses can partition data according to the purpose and use of the data inside. You can read more here: https://www.tutorialspoint.com/dwh/dwh_partitioning_strategy.htm.

In our case, partitioning data is related to how our data will be split into small chunks and processed.

In this recipe, we will learn how to ingest data that is already partitioned and how it can affect the performance of our code.

Getting ready

This recipe requires an initialized SparkSession. You can create your own or use the code provided at the beginning of this chapter.

The data required to complete the steps can be found here: https://github.com/PacktPublishing/Data-Ingestion-with-Python-Cookbook/tree/main/Chapter_7/ingesting_partitioned_data.

You can use a Jupyter notebook or a PySpark shell session to execute the...

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