Robustness in HDFS

• “Data Link -Whenever two or more nodes share the same physical medium (for example, several computers plugged

When a file is written in HDFS, it is divided into fixed size blocks. The client first contacts the NameNode, which get the list of DataNode where actual data can be stored. The data blocks are distributed across the Hadoop cluster. Figure \ref{fig.clusternode} shows the architecture of the Hadoop cluster node used for both computation and storage. The MapReduce engine (running inside a Java virtual machine) executes the user application. When the application reads or writes data, requests are passed through the Hadoop \textit{org.apache.hadoop.fs.FileSystem} class, which provides a standard interface for distributed file systems, including the default HDFS. An HDFS client is then responsible for retrieving data from the distributed file system by contacting a DataNode with the desired block. In the common case, the DataNode is running on the same node, so no external network traffic is necessary. The DataNode, also running inside a Java virtual machine, accesses the data stored on local disk using normal file I/O

HDFS uses NameNode operation to realize data consistency. NameNodes utilizes a transactional log file to record all the changes of

Data chaining indicates that the next CCW contains the address of _________ data for the same command, allowing, portions of one record to be written from or read to multiple data areas in

Reduce time to access the required data: DDBMS allows to store copies of a data in multiple branches.

Partitioning strategy: The hierarchical partitioning of data into a set of directories – The placement and replication properties of directories is

Blocks are the logical records which breaks the area used by a partition; clusters are physical bodies of a hard disk. Hard disk is usually broken in to cylinders and cylinders are broken down in to clusters. Most HDD arrive from the factory with a low level pattern where, block size = 512 bytes. The NTFS file system can produce cluster sizes of a multiple of 512 having a default of 8 blocks for every cluster. Size of a block is multiple of size of cluster, such that a logical block will fit a definite number of physical clusters “one file one cluster”. That is, in every cluster will be installed information belonging at most to a single file. As an aftermath, when scripting a file in a hard disk, some cluster remains incompletely filled or fully unused. As the operating system can only write an entire block, it pursues that the idle space should be fit with some strings of bytes that can be used by others. It should be remembered that these data are saved in a disk because of the operating system curbs to write only on an entire block, they could be detected by locating

6.Full state – both routers have the synchronized database and are fully adjacent with each other.

In RAID 3 the disks spin in sync where all the read write operations are done with high performance.

The master server synchronizes continually with its slaves so in the event of failure a slave can be promoted to become the new master, minimizing downtime. Further improvements in performance can be achieved by caching the results from

It takes care of all cluster maintenance tasks and job scheduling operations and allows the programmer to focus on programming the logic of the application. Submitting a MapReduce job to the master node, results in splitting the input file to several chunks which are block sized that are processed by Map and Reduce tasks at parallel. Due to block replication of HDFS, tasks are scheduled to run on nodes where the required chunks of data already exist, minimizing unnecessary transfer of these data.

HFS+ is file system developed by apple to replace their Hierarchical file system as the primary file system used in Mac computers It is also used by IPod and it is referred to as Mac OS extended.

Once the records are linked, a new dataset is generated. This dataset will undergo quality data evaluation before they are outputs for utilization.

During this period, the network identifies the product and assigns the IP address or hostname of the product.

Much work has been done on analyzing and improving the reliability of storage systems. We classify the existing work into two categories based on the target systems studied, and explain why state-of-the-art approaches are limited in helping diagnose the root causes of failures in flash-based storage systems in this section.