eBook
Learning Spark
| Title: | Learning Spark |
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| 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 APIsUnderstand Spark operations and SQL EngineInspect, tune, and debug Spark operations with Spark configurations and Spark UIConnect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or KafkaPerform analytics on batch and streaming data using Structured StreamingBuild reliable data pipelines with open source Delta Lake and SparkDevelop machine learning pipelines with MLlib and productionize models using MLflow |
| Authors: | Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee |
| Resource Type: | eBook. |
| Subjects: | Machine learning, Big data, Data mining--Computer programs |
| Categories: | COMPUTERS / Data Science / General, COMPUTERS / Business & Productivity Software / General, COMPUTERS / Languages / Java, COMPUTERS / Programming / Open Source, COMPUTERS / Mathematical & Statistical Software, MATHEMATICS / Mathematical Analysis, MATHEMATICS / Complex Analysis |
| Database: | eBook Index |
| ISBN: | 9781492050049 9781492050018 |
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