Learning Spark

Jules Damji, Brooke Wenig, Tathagata Das, Denny Lee

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dc.contributor.author	Jules Damji, Brooke Wenig, Tathagata Das, Denny Lee
dc.date.accessioned	2023-08-24T11:39:27Z
dc.date.available	2023-08-24T11:39:27Z
dc.date.issued	2020-08-25
dc.identifier.issn	978-1492050049
dc.identifier.uri	http://elib.ipa.government.bg:8080/xmlui/handle/123456789/1276
dc.description	Data is bigger, arrives faster, and comes in a variety of formatsâ??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, youâ??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	bg_BG
dc.description.abstract	Локация на изданието: книгата се намира в централния офис на ИПА.	bg_BG
dc.language.iso	en	bg_BG
dc.publisher	O'Reilly Media	bg_BG
dc.relation.isformatof	Сигн; 718
dc.title	Learning Spark	bg_BG
dc.title.alternative	2nd Edition	bg_BG
dc.type	Book	bg_BG