Martin Skurla

We are recently witnesses of the significant movement and adoption of NoSQL databases. In particular, the graph databases become an important technology as we deal with a high increase of relational data. They not only store graph data structures much more efficiently, but also provide powerful graph traversal capabilities that make them suitable for this kind of data. However we need to ease the exploration and understanding of these large amount of data. Visualizing the graph structure (relationships between nodes and edges) is critical to many situations like: verifying the reliability of new data input, optimizing an architecture based on the shape of the data, and even creating new services based on facts discovered in the data. In this talk, you will learn how to understand the graph structure easily using Gephi & Neo4j! We will go through the installation and showcase of visualization capabilities of Neo4j graph database in Gephi. The talk will cover exploration of general useful features of Gephi applying them on imported Neo4j database.

We are recently witnesses of continuous performance improvements both in hardware and software worlds. However for systems with millions requests and users, performance is still very important. One of not that obvious performance optimizations is Garbage Collection selection and tuning. Garbage Collectors save us a lot of time and shield us from low level memory problems. However to take full advantage of Garbage Collection, we need to make the exploration process easy. Visualizing the Garbage Collection techniques (visualizing events, understanding memory abstraction and fragmentation, history observation) is critical for mentioned performance tuning, lowering the memory allocation, consumption and GC pauses. This talk will introduce Garbage Collection in nutshell, but especially abstractions and terms defined in GCSpy project and summarize the porting process of GCSpy to NetBeans platform. We will look at advantages of NetBeans platform, summarize faced challenges and current status of the project and further ideas. I am looking for ideas to improve the GC visualization even more, other VM support (at least partial) and architecture overview.