Mastering Apache Spark 2.0

Mastering BigData and Machine Learning with Apache Spark 2.0

  • Section 1: An Introduction to Apache Spark 2.0
    • Introducing Apache Spark 2.0 6 Apache Spark as a Compiler: Joining a Billion Rows on your Laptop
    • Approximate Algorithms in Apache Spark: HyperLogLog Quantiles
    • Apache Spark 2.0 : Machine Learning Model Persistence
    • SQL Subqueries in Apache Spark 2.0 
  • Section 2: Unification of APIs and Structuring Spark: Spark Sessions, DataFrames, Datasets and Streaming
    • Structuring Spark: DataFrames, Datasets, and Streaming
    • A Tale of Three Apache Spark APIs: RDDs, DataFrames and Datasets
    • How to Use SparkSessions in Apache Spark 2.0: A unified entry point for manipulating data with Spark
  • Section 3: Evolution of Spark Streaming 
    • Continuous Applications: Evolving Streaming in Apache Spark 2.0
    • Unifying Big Data Workloads in Apache Spark
  • Section 4: Structured Streaming 
    • Structured Streaming in Apache Spark 2.0
    • How to Use Structured Streaming to Analyze IoT Streaming Data
Published: December 2016
Author img Databricks




Big Data Innovation Summit

us San Francisco, USA April 19-20, 2017

Strata + Hadoop World

us San Jose March 13-16, 2017

Apache Flink Conferance

us San Francisco, USA April 10-11, 2017