Presented By O'Reilly and Cloudera
Make Data Work
5–7 May, 2015 • London, UK

Training provided by Databricks

Apache Spark Advanced Training - SOLD OUT

Olivier Girardot (Lateral Thoughts), Sameer Farooqui (Databricks)
9:00 Tuesday, 05 May 2015
9:00 Wednesday, 06 May 2015
9:00 Thursday, 07 May 2015
Location: Hilton Meeting Room 1-3

This three-day curriculum features advanced lectures and hands-on technical exercises for advanced Spark usage in data exploration, analysis, and building Big Data applications. Course materials emphasize architectural design patterns and best practices for leveraging Spark in the context of other popular, complementary frameworks for building and managing Enterprise data workflows. Those who attend the training will have opportunities during the tutorial to meet and discuss with key members of the Spark development community, including Q&A sessions and whiteboarding for specific questions about use cases. Participants will also receive limited free-tier accounts on Databricks Cloud.

Topics include:

  • Using cloud-based notebooks to develop Enterprise data workflows
  • Spark integration with Cassandra, Kafka, Elasticsearch
  • Advanced use cases with Spark SQL and Spark Streaming
  • Operationalizing Spark on DataStax, Cloudera, MapR, etc.
  • Monitoring and evaluating performance metrics
  • Estimating cluster resource requirements
  • Debugging and troubleshooting Spark apps
  • Cases studies for production deployments of Spark
  • Preparation for Apache Spark developer certification exam

Attendance is limited to 35 participants.


  • Experience coding in Java, Python
  • Some familiarity with Big Data frameworks in general
  • Participated in one or more of the following:
    • Spark Camp at Strata + Hadoop World or Spark Summit
    • Databricks workshops and other comparable Spark training
    • Worked through coding exercises in Learning Spark
    • Experience developing Spark apps in production


  • Laptop (+2GB memory) with wifi connectivity
  • Java JDK 6/7/8 installed
  • Python 2.7 installed

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