# Big Data in Smart City: Management Challenges
## 4 Transformation to Gaminess Big Data Framework
### GANMINESS Management System (GAMINESS Streaming Approach)
The Apache Spark framework offers a core for data modeling and processes based on the machine learning algorithms. Apache Spark allows one to leverage the unique ability to simplify machine learning through a single technology. GAMINESS uses Spark Core, which contains the basic functionality of Spark, including components for task scheduling, memory management, fault recovery, interacting with storage systems, and more. Spark SQL provides support for interacting with Spark via SQL. Spark Streaming enables processing of live data stream. MLlib provides multiple types of machine learning algorithms, including binary classification, regression, clustering, and collaborative filtering in addition to supporting functionality such as model evaluation and data import. The 3 DCityDB is a relational DB which uses PostgreSQL as DBMS for storing and querying the data. For the purpose of the smart city, there is a need to query large 3D datasets. In the proposed model, import of sensor data in the GAMINESS framework was enabled through the use of specific types defined as user defined types. This is the most important extension in the Spark framework regarding the basic module. The 3D city models are available at different levels of detail and provide adequate storage options for collections of 3D city models. Models should be standardized and structured with their semantic data. Taking into account all analyzed literature and presented discussion, the GAMINESS management system has several advantages:

1. biG dAtsMart clty maNagEment SyStem (GAMINESS) is a unique solution that provides the ability to manage a smart city system in respect to big data concepts. \begin{table}
\begin{tabular}{c c} \hline \hline
**CityGML Modules and** & **CityGML Modules and Characteristics Not Supported** \\ \hline CityGML Core & \\ \hline Building & \\ \hline Bridge & No support for ADEs \\ \hline Tunnel & No support for the topological relationships that can be defined, \\ \hline CityFurniture & e.g., relative to terrain and relative to water \\ \hline LandUse & No closure surface \\ \hline Relief & No support for arbitrary coordinate reference systems (CRSs). \\ \hline Relief & Only an EPSG code can be used. Furthermore, all geometries in a given CityJSON must be using the same CRS. \\ \hline Transportation & In CityGML, most objects can have an ID (usually gmlid), that is, \\ \hline CityObjectGroup & one building can have an ID, but also each 3D primitive forming \\ \hline Vegetation & its geometry can have an ID. In CityJSON, only city object types \\ \hline WaterBody & \\ \hline Generics & \\ \hline Address Appearance & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Difference between CityGML and CityJSON data models. Unlike existing solutions (e.g., 3 DCityDB), the model expands the representation of the interior space with navigation parameters by integrating the IndoorGML standard into the existing CityGML standard in the Apache Spark environment. 3. The model represents one of the first studies that combines models that take into account the geospatial component which is mapped into the big data platform (the proposed model gives more efficient results of point cloud data processing than the proposed model within the IQUMULUS project). 4. GAMINESS enables both integration of geospatial and data streamed from sensors based on different standards and their translation to the Apache Spark structure with adequate conversion. 5. The model provides all data to be stored in one smart city system, which allows combination and analysis of data on a DBMS level that provides more complex combinations of data. The store on the big data concept provides maximal performance of the existing system and much faster response with decision-making processes. This is not possible in any smart city-based DBMS in the basic relation database. As a result of this research, a physical model and sensor data are stored together in the GAMINESS management system.