Jeremy Meyer heads up the Professional Services and Education team at GridGain Systems. He is a computer scientist, philosopher, coder, hobbyist, very rare blogger and writer, as well as a lover of good design and good puzzles.
This eight-minute GridGain University Micro Learning Unit explores the importance of colocation and affinity to the performance of Apache Ignite data query and computation.
The two largest sources of latency in any distributed system are network latency and disk access. In traditional client server applications, data is constantly moved over the network, and it's usually accessed from…
This six-minute Micro Learning Unit explores how distributed data is implemented in Apache Ignite and identifies solutions to three key data challenges: hardware capacity, hardware reliability, and performance issues.
Capacity: It’s more efficient to scale data capacity horizontally than vertically. For example, extremely fast CPUs typically cost several times as much as two slightly slower…
GridGain recently published a micro-learning unit on GridGain University that delves into the different data loading strategies for Apache Ignite. These strategies include initial/regular batch load from files, database loading, real-time streaming, and ETL (Extract Transform & Load).
Here is an overview of some of the key strategies. Watch the full 9-minute video here.
Initial /…