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. \n
\nUpdated 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: \n
\n
- Learn Python, SQL, Scala, or Java high-level Structured APIs
\n
- Understand Spark operations and SQL Engine
\n
- Inspect, tune, and debug Spark operations with Spark configurations and Spark UI
\n
- Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka
\n
- Perform analytics on batch and streaming data using Structured Streaming
\n
- Build reliable data pipelines with open source Delta Lake and Spark
\n
Також купити книгу Learning Spark: Lightning-Fast Data Analytics 2nd Edition,
Jules Damji, Brooke Wenig, Tathagata Das, Denny Lee можливо по посиланню: