# Study on Effective Temporal Data Retrieval Leveraging Complex Indexed Architecture
## 6 Performance Evaluation
### Experiment 5--null management
The second module presence reference the Master indexing, which removes the impact of the whole table scanning, if no suitable index is used. In that case, block values are extracted from any suitable B+tree by scanning the leaf layer of the index. Master index selection used in this experiment was dynamic meaning, that the optimizer autonomously selects the best suitable index with minimal estimated costs reflected by the memory loading (I/O operations from the database), whole size, and costs of the scanning. Note, that the index must cover all data rows, otherwise it cannot be marked as Master. The third accessible module reflects NULL management directly in the index set. Thanks to the presence of this module, any index can be selected as Master. In this case, the existing index set does not been to be enhanced, but if the condition is based on the undefined or untrusted value, the existing index can be used, as well. By using the NULL management module, many times, the original index can be directly used with no necessity to block identification (BLOCKID) extraction. The fourth module uses range spatial partitioning using the defined regions. It follows the temporal data partitioning, as well, thus the data image valid at the defined timepoint or interval is placed in the same data partition, thus the evaluation is easier and significantly less demanding, whereas the number of searched data is minimized. Moreover, if the data interval is spread across multiple partitions, the background process launches more workers to process the data in parallel. Afterward, the result set is created by the unification of the sets (UNION ALL operation). The fifth module expresses the autoindexing option, by which the existing index set is dynamically analyzed, new indexes are created and removed autonomously with regards to the whole performance of the current states. By using the Master indexing module, peaks created by the autoindexing can be flattened. The reason is, that the autoindexing is just the reactive module based on the changed query types. Moreover, the index must be built to be usable, which demands additional processing time and system sources. If the system is so dynamic with really various query types  
Figure 23: Data retrieval—NULL management layer. evolving rapidly over the time, the autoindexing module does not even provide benefits, whereas the costs of the index set handling can be higher in comparison with the total contribution. In this case, based on the number of uses of the given index (provided by the statistics), the system evaluates that the benefit of the autoindexing module is minimal and is automatically deallocated. At the same time, however, the system is monitored and, if the benefits exceed the costs, it switches on automatically. The last module is post-indexing, which extracts the index balancing operation into a separate transaction. Thanks to that, a particular Insert operation can be ended sooner by reaching the transaction Commit earlier. Thus, the data are produced for the environment by lowering the processing delays. Figure 24 shows the architecture with the relevance of the individual modules. The experiment uses the assumption, that all preceding modules are present in the system. Thus, by introducing NULL management, Epsilon, and Master index modules are already there. Note, that index set consists of the spatial and temporal reflection only. There is no additional index present unless created by the autoindexing. The reference model does not use any already defined modules (reference 100%). Reflecting the sensor-based data about the drivers defined in [28] reflecting principles covered in [40; 41; 42], Epsilon definition lowers the processing time demands to 87%. Evaluation is done in the preprocessing layer of the database system, individual background processes are contacted only if it reflects the relevant change. Master index extension requires only 81%. Its benefit is based on the fragmentation, which is present at 10%, of which 3% of the blocks are empty.