Learning Spark
- Downloads：1395
- Type：Epub+TxT+PDF+Mobi
- Create Date：2021-08-20 06:55:24
- Update Date：2025-09-06
- Status：finish
- Author：Jules S. Damji
- ISBN：1492050040
- Environment：PC/Android/iPhone/iPad/Kindle
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Summary
Data is bigger， arrives faster， and comes in a variety of formats--and it all needs to be processed at scale for analytics or machine learning。 But how can you process such varied workloads efficiently？ Enter Apache Spark。
Updated to include Spark 3。0， this second edition shows data engineers and data scientists why structure and unification in Spark matters。 Specifically， this book explains how to perform simple and complex data analytics and employ machine learning algorithms。 Through step-by-step walk-throughs， code snippets， and notebooks， you'll be able to:
Learn Python， SQL， Scala， or Java high-level Structured APIs
Understand Spark operations and SQL Engine
Inspect， tune， and debug Spark operations with Spark configurations and Spark UI
Connect to data sources: JSON， Parquet， CSV， Avro， ORC， Hive， S3， or Kafka
Perform analytics on batch and streaming data using Structured Streaming
Build reliable data pipelines with open source Delta Lake and Spark
Develop machine learning pipelines with MLlib and productionize models using MLflow
Updated to include Spark 3。0， this second edition shows data engineers and data scientists why structure and unification in Spark matters。 Specifically， this book explains how to perform simple and complex data analytics and employ machine learning algorithms。 Through step-by-step walk-throughs， code snippets， and notebooks， you'll be able to:
Learn Python， SQL， Scala， or Java high-level Structured APIs
Understand Spark operations and SQL Engine
Inspect， tune， and debug Spark operations with Spark configurations and Spark UI
Connect to data sources: JSON， Parquet， CSV， Avro， ORC， Hive， S3， or Kafka
Perform analytics on batch and streaming data using Structured Streaming
Build reliable data pipelines with open source Delta Lake and Spark
Develop machine learning pipelines with MLlib and productionize models using MLflow
Reviews
Syed Ashrafulla
，
This is a good soup-to-nuts book on Spark features。 I didn't read many of the GitHub examples since I was on an e-reader， but I'll do so now that I'm done。 I think this is a lot better than the Coursera courses。 The treatment， when detailed， was just detailed enough （for example， with optimization for shuffling）。 As a textbook， I'm not sure how to improve the book actually。 Hence the five stars。 This is a good soup-to-nuts book on Spark features。 I didn't read many of the GitHub examples since I was on an e-reader， but I'll do so now that I'm done。 I think this is a lot better than the Coursera courses。 The treatment， when detailed， was just detailed enough （for example， with optimization for shuffling）。 As a textbook， I'm not sure how to improve the book actually。 Hence the five stars。 。。。more
Gishu Pillai
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I switched to this book after “Spark: The definitive guide” got too heavy for me mid-way through the book。This one is a much easier read。 However it skimmed few topics like aggregations & windowing functions - I would have liked some more elaboration there。 Loved the optimization/tuning tips chapter。I breezed through the later chapters as I wasn’t interested at the moment with MLLib。 Not a definite 5/5 but a good companion book when you are ready to wrestle with Spark。
Reference
google book https://www.google.com/search?tbm=bks&q=Learning Spark
hathitrust digital library https://babel.hathitrust.org/cgi/ls?q1=Learning Spark&field1=ocr&a=srchls&ft=ft&lmt=ft
The British Library https://bll01.primo.exlibrisgroup.com/discovery/search?query=any,contains,Learning Spark&tab=LibraryCatalog&search_scope=Not_BL_Suppress&vid=44BL_INST:BLL01&lang=en&offset=0