{"product_id":"essential-pyspark-for-scalable-data-analytics-a-beginners-guide-to-harnessing-the-power-and-ease-of-pyspark-3-paperback","title":"Essential PySpark for Scalable Data Analytics: A beginner's guide to harnessing the power and ease of PySpark 3 - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eSreeram Nudurupati\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eGet started with distributed computing using PySpark, a single unified framework to solve end-to-end data analytics at scale\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDiscover how to convert huge amounts of raw data into meaningful and actionable insights\u003c\/li\u003e\n\u003cli\u003eUse Spark's unified analytics engine for end-to-end analytics, from data preparation to predictive analytics\u003c\/li\u003e\n\u003cli\u003ePerform data ingestion, cleansing, and integration for ML, data analytics, and data visualization\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eBook Description: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eApache Spark is a unified data analytics engine designed to process huge volumes of data quickly and efficiently. PySpark is Apache Spark's Python language API, which offers Python developers an easy-to-use scalable data analytics framework.\u003c\/p\u003e\u003cp\u003eEssential PySpark for Scalable Data Analytics starts by exploring the distributed computing paradigm and provides a high-level overview of Apache Spark. You'll begin your analytics journey with the data engineering process, learning how to perform data ingestion, cleansing, and integration at scale. This book helps you build real-time analytics pipelines that enable you to gain insights much faster. You'll then discover methods for building cloud-based data lakes, and explore Delta Lake, which brings reliability and performance to data lakes. The book also covers Data Lakehouse, an emerging paradigm, which combines the structure and performance of a data warehouse with the scalability of cloud-based data lakes. Later, you'll perform scalable data science and machine learning tasks using PySpark, such as data preparation, feature engineering, and model training and productionization. Finally, you'll learn ways to scale out standard Python ML libraries along with a new pandas API on top of PySpark called Koalas.\u003c\/p\u003e\u003cp\u003eBy the end of this PySpark book, you'll be able to harness the power of PySpark to solve business problems.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhat You Will Learn: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUnderstand the role of distributed computing in the world of big data\u003c\/li\u003e\n\u003cli\u003eGain an appreciation for Apache Spark as the de facto go-to for big data processing\u003c\/li\u003e\n\u003cli\u003eScale out your data analytics process using Apache Spark\u003c\/li\u003e\n\u003cli\u003eBuild data pipelines using data lakes, and perform data visualization with PySpark and Spark SQL\u003c\/li\u003e\n\u003cli\u003eLeverage the cloud to build truly scalable and real-time data analytics applications\u003c\/li\u003e\n\u003cli\u003eExplore the applications of data science and scalable machine learning with PySpark\u003c\/li\u003e\n\u003cli\u003eIntegrate your clean and curated data with BI and SQL analysis tools\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho this book is for: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eThis book is for practicing data engineers, data scientists, data analysts, and data enthusiasts who are already using data analytics to explore distributed and scalable data analytics. Basic to intermediate knowledge of the disciplines of data engineering, data science, and SQL analytics is expected. General proficiency in using any programming language, especially Python, and working knowledge of performing data analytics using frameworks such as pandas and SQL will help you to get the most out of this book.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 322\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.67 x 9.25 x 7.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e October 29, 2021\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":44278687924326,"sku":"9781800568877","price":83.36,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0599\/7255\/0758\/files\/dVJuaTg3ZWZNMmoxRmFGVm9SUlhxQT09.webp?v=1766486026","url":"https:\/\/infinitylightwa.com\/products\/essential-pyspark-for-scalable-data-analytics-a-beginners-guide-to-harnessing-the-power-and-ease-of-pyspark-3-paperback","provider":"Infinity Light","version":"1.0","type":"link"}