## 3 Motivation
The 4 + 2 EC setting means that the number of DataNodes that store data cells is four, and the number of DataNodes that store parity cells is two, and for 128 KB data, the I/O size of each cell is 32 KB through encoding, and the number of I/Os is six. Similarly, the 8 + 2 EC setting is expressed as 10 16 KB I/Os. Finally, the 16 + 2 EC setting is expressed to 18 8 KB I/Os, in which overall system performance degradation occurs due to waiting I/Os in the primary queue, which are not processed, as a result of very-tiny-sized I/O requests. Next, the recovery problems occurring in the EC-based HDFS are discussed in detail. The data and parity cells generated in the EC-based HDFS are distributed and stored in different disks, which is similar to the replication case, to ensure availability. As described above, if a single cell is stored in multiple disks, it is classified into clustering storage and nonclustering storage modes according to cell distribution and storage method. The clustering storage mode means that required disks are clustered in advance and cells are distributed and stored only within the cluster when storing cells, which is used in GlusterFS, Ceph, and so forth among various EC-based distributed file systems. The nonclustering storage mode means that all disks are recognized as one cluster, and files are distributed and stored in arbitrary disks; this is typically used in EC-based HDFS. Figure 4 shows examples of clustering and nonclustering storage modes, which display the 4 + 2 EC storage with six DataNodes, each containing four disks. The clustering storage mode in Figure 4 selects one disk only from each of six DataNodes, thereby designating a total of four clusters and distributing and storing cells within the designated groups, whereas the nonclustering storage mode stores cells in arbitrary disks from among all disks. The clustering storage mode easily manages resources and stores files because cell allocation is performed at the cluster level. However, it has a drawback of limiting the recovery performance because recovery is performed only at the cluster level. The nonclus \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**EC Volume** & **2 + 2** & **4 + 2** & **8 + 2** & **16 + 2** \\
**DataNode** & & & & & \\ \hline DataNode I/O size & 64 KB & 32 KB & 16 KB & 8 KB \\ DataNode I/O count & 4 & 6 & 10 & 18 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The 128 KB I/O process size in the DataNode according to the EC setting. Figure 4: Examples of clustering (**left**) and nonclustering (**right**) storage modes. tering storage mode struggles to manage resources because cells are allocated randomly throughout all disks, but its recovery performance is not limited, because recovery is performed throughout all disks. Figure 5 shows the disk usage in DataNode 1 during single-thread fault recovery when a fault occurs in disk 4 of DataNode 6 in Figure 4.  
As shown in Figure 5, I/Os occur only in disk 4, which is the same cluster as that of the fault disk during recovery time in the clustering storage mode, whereas I/Os occur in disks 2 and 4 sequentially according to the fault file. Since a single thread performs recovery, recovery performance is similar, but there is a difference in disks utilized during recovery. Figure 6 shows the disk usage in DataNode 1 during multithread fault recovery when a fault occurs in disk 4 of DataNode 6. As shown in Figure 6, since I/O occurs only in disk 4, which is the same cluster as that of the fault disk during recovery in the clustering storage mode, performance improvement was minimal despite of the use of multithreads. The recovery performance increases as the recovery is performed in multithreads in the nonclustering storage mode, and many disks are utilized in the recovery. However, the mean recovery performance is 94 MB/s in the nonclustering storage mode, which is very low compared with the overall system performance. In Section 4, the efficient data distribution and storage method and parallel recovery technique in the EC-based HDFS are presented.