# Study on Effective Temporal Data Retrieval Leveraging Complex Indexed Architecture
## 6 Performance Evaluation
### Summary  
Data retrieval is a complex staged process, each stage influences the performance. In principle, any incorrect decision done on any layer cannot be corrected later. The first level covers architecture. In this paper, we deal with sensor data management operated to monitor driver activity, over time forming temporal architecture. Based on the defined environment and 5.4 million rows, it is evident, that the data changes are not always present for each attribute synchronously. If the heterogeneity of the specification is present, the problem can be even deeper, whereas some data portions do not change their values at all forming the code list principles. Another problem is correlated with the data, which do not need to be monitored over time. Thus, in any environment, where such prerequisites are present, the proposed solution is relevant. Based on the results, the size of the whole structure can be reduced up to 66% for the group extension architecture. The data retrieval process can significantly benefit, as well, whereas the change identification is directly evident for the attribute (column) or group granularity. Reflecting the performance and environment, demands are lowered using 63% for attribute and 61% for the group, which is reflected by the group decomposition necessity. Undefined values form another complex problem, whereas they are not located in the index structures. For data retrieval, therefore, sequential data block scanning is necessary to be done. By using proposed NULL modules and categorization, processing demands in terms of time can be lowered up to 27% or 28%, respectively. Finally, complex architecture is evaluated covering all the proposed segments summarized in Figure 24. The usage of the proposed solutions can be found in almost any environment necessary to monitor sensor data over time. In the industry environment, the individual manufacturing process needs to be monitored by the sensors, which produce relevant data with various granularity and precision. If the measured data value is provided with delay and the sensor is broken or the communication channel fails, even temporarily, undefined values are produced, which must be handled with care. The proposed solution can be, similarly, used for traffic monitoring, for the positional data processing of the vehicles, or flight efficiency and position monitoring. Area of patient monitoring can benefit by using the proposed architecture, as well. In this paper, moreover, data retrieval extension clauses are proposed, by which the user experience benefits. The process of the data to be obtained is significantly simplified. The following paragraph shows the benefit of the proposed solutions. The first example deals with the Epsilon management, only rows, that express the change above 1% that will be part of the result set. In the existing syntax, it is necessary to use the flowing window frame to obtain the previous value of the sensor particular for the object. Note, that it cannot be done directly, thus the nested Select statement needs to be used. Moreover, if  
Figure 25: Whole system modularization—data retrieval performance. the window does not reflect only the direct predecessor, a more complex solution must be specified. The second code shows the usage of the Epsilon clause definition, which simplifies the specification, however, the performance is the same:  
Select object, BD, value  
From  
(Select object, BD, value,  
lag(value, 1\(<\)offset, null\(<\)=default)  
over(partition by object order by BD) as predecessor  
From data_tab  
Where abs(value, predecessor)\(>\)1;  
By using proposed Select statement definition, the same results are obtained:  
Select object, BD, value  
From data_tab  
Where Epsilon_definition(value, 1);  
The following code shows the statement to monitor the vehicle in the Slovakia region during the year 2020 by monitoring delays. Whereas several new road segments were opened, as well as some existing are closed due to the reconstruction, current Model_reflection is used.