EAN: 9781492050049

LEARNING SPARK - JULES S DAMJI BROOKE WENIG TAT...

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

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