Alexey Zinoviev - Java in production for Data Mining Research projects (Ru)

Java is often criticized for hard parsing CSV datasets, poor matrix and vectors manipulations. This makes it hard to easy and efficiently implement certain types of machine learning algorithms. In many cases data scientists choose R or Python languages for modeling and problem solution and you as a Java developer should rewrite R algorithms in Java or integrate many small Python scripts in Java application. But why so many highload tools like Cassandra, Hadoop, Giraph, Spark are written in Java or executed on JVM? What the secret of successful implementation and running? Maybe we should forget old manufacturing approach of dividing on developers and research engineers in production projects? During the report, we will discuss how to build full Java-stack Data Mining application, deploy it, make charts, integrate with databases, how to improve performance with JVM tuning and etc.
Back to Top