Realtime Advanced Analytics: Spark Streaming+Kafka, MLlib/GraphX, SQL/DataFrames

[Replay for the Peninsula/South Bay]

We'll present a real-world, open source, advanced analytics and machine learning pipeline using all "15" Open Source technologies listed below.

This Meetup is based on my recent "Top-5" Hadoop Summit/Data Science talk called "Spark After Dark". Spark After Dark is a mock online dating site that uses Spark, Spark SQL, DataFrames, MLlib, GraphX, Cassandra, and ElasticSearch - among many other technologies listed below - to generate quality, real-time dating recommendations for its users.

Here are the Spark After Dark slides: http://www.slideshare.net/cfregly/spark-after-dark-real-time-advanced-analytics-and-machine-learning-with-spark

All code - and the entire pipeline runtime - will be dockerized and made publicly available on Github and the Docker Hub Registry.

Technologies to be demo'd:

1. Apache Zeppelin and Spark-Notebook (notebook-based development)
2. Apache Spark SQL/DataFrames (Ad hoc Data Analysis and ETL)
3. Apache Spark Streaming + Apache Kafka (Real-time Collection of Live Data from Interactive Demo)
4. Spark Streaming + Real-time Machine Learning (K-Means Clustering, Log/Lin Regression)
5. Apache Spark MLlib + GraphX (Generate personalized and non-personalized recommendations using various algorithms and feature engineering techniques including one hot encoding)
6. MLlib + PMML Integration (Open Standard Markup Language for Predictive Models)
7. Zeppelin + Python-based scikit-learn Machine Learning + Advanced Visualizations with matplotlib and ggplot
8. Spark R (Distributed R algorithmns)
9. Apache Spark JDBC/ODBC Thrift Server (Beeline and Tableau Analytics Explorer Integration)
10. Tachyon (Off-heap storage)
11. Spark + Cassandra
12. Spark + ElasticSearch (Distributed Search Engine)
13. Logstash (Log Agent + Collection)
14. Kibana (ElasticSearch-based Analytics Explorer UI)
15. HDFS + Parquet (Columnar Storage Format, Tight Compression, Lightning Fast Columnar Aggregations)

Reminder that we've Docker-ized everything for you to take home.

Here's the Github Repo and Docker Hub Registry links:

1. https://github.com/fluxcapacitor
2. https://registry.hub.docker.com/repos/fluxcapacitor/

Feel free to clone and contribute! Every contributor will be made a committer.

Bonus: Free 30-day Trial @ www.databricks.com

Databricks Cloud Notebook-based Development and Cluster Management.

Thanks, Databricks!

See everyone soon!