Bay Area Big Data Meetups: Splice Machine Presenting at Spark/TensorFlow, Hadoop and Java Meetups in November
November 1, 2016
Splice Machine is presenting at three Bay Area meetups this month:
- Advanced Spark & TensorFlow meetup at Splice Machine in San Francisco on Thursday, November 3 at 6:00pm
- San Francisco Hadoop User Group meetup at Splice Machine in San Francisco on Tuesday, November 8 at 6:00pm
- Silicon Valley Java User Group meetup at Google West Campus in Mountain View on Wednesday, November 16 at 6:00pm
At the Advanced Spark & TensorFlow meetup, Splice Machine’s CEO, Monte Zweben, will discuss ACID, Spark and TensorFlow. In addition to Monte’s presentation, Susan Eraly of Skymind will present “Deep Dive into Deep Learning for Java (DL4J), N-Dimensional Array for Java (ND4J), and JavaCPP” and Chris Fregly of PipelineIO will present “Deep Dive into Spark ML + TensorFlow + TensorFrames + Kubernetes + Docker + CUDA 8 + GPU/CPU Unified Memory Model.” Chris will also demonstrate a teaser for the next meetup, “Demo One-Click Deploy of Spark ML and TensorFlow AI Models from Jupyter Notebooks to NetflixOSS-based Production Microservices”
Presentations and videos will be posted shortly: Advanced Spark & TensorFlow meetup
The San Francisco Hadoop User Group meetup will focus on the architecture of an open source RDBMS powered by HBase and Spark. Splice Machine’s CEO Monte Zweben will discuss open-source databases that combine the benefits of modern Lambda Architectures with the full expressiveness of ANSI-SQL. Like a traditional Lambda Architecture, it employs separate compute engines for different workloads but without the “duct tape” of a typical approach. This talk describes this architecture and implementation.
Presentations and videos will be posted shortly: San Francisco Hadoop User Group meetup
Finally, at the Silicon Valley Java User Group, our presentation will also focus on the architecture of an open source RDBMS powered by HBase and Spark. At this meetup, Jun Yuan, principal engineer at Splice Machine, will discuss the architecture and implementation of Splice Machine V2.0, which differs from most other clustered SQL systems such as Impala, SparkSQL, and Hive because it combines analytical processing with a distributed Multi-Value Concurrency Method that provides fine-grained concurrency which is required to power real-time applications. This talk will also highlight the Splice Machine storage representation, transaction engine, cost-based optimizer, and present the detailed execution of operational queries on HBase, and the detailed execution of analytical queries on Spark.
If you are interested in attending this meetup, please RSVP here!
We’re also be updating this page with links to any videos or slide shares following the meetups.