Rebinding done by Spiralverse

Learning Spark: Lightning-Fast Data Analytics (2nd Edition) Spiral-Bound |

Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee

$57.07 - Free Shipping

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
Publisher: Ingram Publisher Services
Original Binding: Trade Paperback
Pages: 397 pages
ISBN-10: 1492050040
Item Weight: 1.94 lbs
Dimensions: 7.0 x 1.49 x 9.2 inches
Jules S. Damji is a senior developer advocate at Databricks and an MLflow contributor. He is a hands-on developer with over 20 years of experience and has worked as a software engineer at leading companies such as Sun Microsystems, Netscape, @Home, Loudcloud/Opsware, Verisign, ProQuest, and Hortonworks, building large scale distributed systems. He holds a B.Sc. and an M.Sc. in computer science and an MA in political advocacy and communication from Oregon State University, Cal State, and Johns Hopkins University, respectively.