Data Stream Analysis

Real-Time Streaming with Apache Kafka, Spark, and Storm: Create Platforms That Can Quickly Crunch Data and Deliver Real-Time Analytics to Users

Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications

Building Data Pipelines Using Apache Beam: Deliver Unified Batch and Streaming Pipelines for Real-World Production Across Dataflow, Flink, and Spark

Real-Time Data Processing: Harnessing the Power of Streaming Data

Fast Data Processing with Spark 2: Accelerate your data for rapid insight

Spark: The Definitive Guide: Big Data Processing Made Simple

Streaming Architecture: New Designs Using Apache Kafka and MapR Streams

Big Data Processing Using Spark in Cloud

Practical Data Engineering with Apache Projects: Solving Everyday Data Challenges with Spark, Iceberg, Kafka, Flink, and More

Dataflow Processing

Mastering Data Engineering and Analytics with Databricks: A Hands-on Guide to Build Scalable Pipelines Using Databricks, Delta Lake, and MLflow (English Edition)

Spark in Action: Covers Apache Spark 3 with Examples in Java, Python, and Scala

Data Lake Development with Big Data: Explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies

Learning Spark LightningFast B

Stream Processing with Apache