{pdf download} Learning Spark: Lightning-Fast Data Analytics
Learning Spark: Lightning-Fast Data Analytics. Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee
Learning-Spark-Lightning-Fast-Data.pdf
ISBN: 9781492050049 | 300 pages | 8 Mb
- Learning Spark: Lightning-Fast Data Analytics
- Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee
- Page: 300
- Format: pdf, ePub, fb2, mobi
- ISBN: 9781492050049
- Publisher: O'Reilly Media, Incorporated
Free download books from amazon Learning Spark: Lightning-Fast Data Analytics
Data is getting bigger, arriving faster, and coming in varied formats—and it all needs to be processed at scale for analytics or machine learning. How can you process such varied data workloads efficiently? Enter Apache Spark.Updated to emphasize new features in Spark 2.x., this second edition shows data engineers and 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 discourse, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level APIs: DataFrames and Datasets Peek under the hood of the Spark SQL engine to understand Spark transformations and performance Inspect, tune, and debug your 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 Use open source Pandas framework Koalas and Spark for data transformation and feature engineering
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Learning Spark Lightning-Fast Big Data Analytics by Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia; O'Reilly Media.
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Learning Spark - Lightning-Fast Data Analytics. Bereich: eBooks. We welcome you to the second edition of Learning Spark. It's been five years since the first
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Learning Spark: Lightning-Fast Big Data Analysis. by Holden Karau , Andy Konwinski, et al.
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Engineers and data scientists will both learn different details from this book, but will both be able to apply Spark to solve large distributed problems in their
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