Abstract:
A system for deploying big data software in a multi-instance node. The optimal CPU memory and core configuration for a single instance database is determined. After determining an optimal core-memory ratio for a single instance execution, the software is deployed in multi-instance mode on single machine by applying the optimal core-memory ratio for each of the instances. The multi-instance database may then be deployed and data may be loaded in parallel for the instances.
Abstract:
A system for deploying big data software in a multi-instance node. The optimal CPU memory and core configuration for a single instance database is determined. After determining an optimal core-memory ratio for a single instance execution, the software is deployed in multi-instance mode on single machine by applying the optimal core-memory ratio for each of the instances. The multi-instance database may then be deployed and data may be loaded in parallel for the instances.
Abstract:
An adapter retrieves graph data from one or more graph databases and adapts the data to be shown through a visualization tool. The adapter may be used to convert multiple formats of graph data into a format which is readable and useable by the visualization tool. The adapter module may make a connection with a graph database and query the database for particular graph data. Once retrieved, the stream of retrieved graph data may be used to populate a template in Java form. From the template, the visualization tool may provide a visualization of the retrieved data.
Abstract:
A system for deploying big data software in a multi-instance node. The optimal CPU memory and core configuration for a single instance database is determined. After determining an optimal core-memory ratio for a single instance execution, the software is deployed in multi-instance mode on single machine by applying the optimal core-memory ratio for each of the instances. The multi-instance database may then be deployed and data may be loaded in parallel for the instances.
Abstract:
A system for deploying big data software in a multi-instance node. The optimal CPU memory and core configuration for a single instance database is determined. After determining an optimal core-memory ratio for a single instance execution, the software is deployed in multi-instance mode on single machine by applying the optimal core-memory ratio for each of the instances. The multi-instance database may then be deployed and data may be loaded in parallel for the instances.