## 6 Performance Evaluation
### Data Recovery Performance  
The data recovery performance was compared between the basic EC-based HDFS and disk I/O load distribution and random block placement and the matrix recycle-applied EC based HDFS, which was proposed in this study. The I/O load distribution technique-applied EC-based HDFS was named EC HDFS-LR (load reducing).  
In the experiment, all file systems employed the same 4 + 2 EC volume, and the recovery performance according to changes in recovery threads was measured when one disk failed. In addition, the EC HDFS and EC HDFS-LR employed nonclustering block placement using the round robin algorithm when placing the blocks.  
As shown in Figure 22, the performance of EC HDFS was slightly improved as the number of recovery threads increased. The performance of the EC HDFS-LR was rapidly improved until the number of recovery threads was five, which started the reduction of improvement, and after six threads, the performance did not improve. However, the performance of the EC HDFS-LR was about two times better than that of the EC HDFS. Figure 23 shows the disk usage in a specific DataNode when running six recovery threads in the EC HDFS and in the EC HDFS-LR.  
As shown in Figure 23, the recovery performance was 50 MB/s on average in the EC HDFS, whereas more disks were utilized in the recovery than that of the EC HDFS. Thus,  
Figure 23: Disk usage of the EC HDFS (**left**) and the EC HDFS-LR (**right**).  
Figure 22: Comparison of recovery performance according to the number of recovery threads.  
the recovery performance of the EC HDFS-LR was around 180 MB/s, which was 2.5 times larger than that of the EC HDFS.  
Figure 24 shows the performance comparison when applying the sequential and random block placement techniques to the EC HDFS and EC HDFS-LR. When applying the sequential block placement, performance was improved by about 40% compared with that of applying the random block placement. In particular, when the random block placement was applied to the EC HDFS-LR, the performance was improved further.  
Figure 25 shows the memory usage when single and multiple faults occur in 2 + 2 EC, 4 + 2 EC, and 8 + 2 EC, while the matrix recycle technique is applied and the encoding and decoding word size is set to 32 bytes. Here, single fault means that a fault occurs in only one data cell, and multiple faults mean that faults occur in two data cells simultaneously.  
The memory size in the structure where the K + M EC volume is used increases as the K value increases. The memory size used increases as the number of faults increases in the same EC attributes, because the number of used matrices becomes large. However,  
Figure 24: Performance comparison according to the block placement technique between the EC HDFS and the EC HDFS-LR.  
Figure 25: Memory size (KB) needed for matrix storage.  
the used memory size is 140 KB in the 8 + 2 EC volume structure. That is, a severe problem does not occur even if matrices are recycled in the matrix pool because the matrix size is small.  
Figure 26 shows the results of 100,000 fault recoveries when one disk fault and two disk faults occur randomly in the 4 + 2 EC volume structure.  
When a single disk fault occurred, 100,000 repetitions of fault recovery were performed, and the recovery time when recycling the matrices was about 2.6 times faster. When two disk faults occurred, 100,000 repetitions of fault recovery were performed, and the recovery time when recycling the matrices was about three times faster. That is, a faster recovery time can be ensured if two or more disk faults occur and the volume of the EC system is set to large.