Recent technological advancements have led to a deluge of data from distinctive domains (e.g., health care and scientific sensors, user-generated data, Internet and financial companies, and supply chain systems) over the past two decades. The term big data was coined to capture the meaning of this emerging trend. In addition to its sheer volume, big data also exhibits other unique characteristics as compared with traditional data. For instance, big data is commonly unstructured and require more real-time analysis. This development calls for new system architectures for data acquisition, transmission, storage, and large-scale data processing mechanisms. In this paper, we present a literature survey and system tutorial for big data analytics platforms, aiming to provide an overall picture for nonexpert readers and instill a do-it-yourself spirit for advanced audiences to customize their own big-data solutions. First, we present the definition of big data and discuss big data challenges. Next, we present a systematic framework to decompose big data systems into four sequential modules, namely data generation, data acquisition, data storage, and data analytics. These four modules form a big data value chain. Following that, we present a detailed survey of numerous approaches and mechanisms from research and industry communities. In addition, we present the prevalent Hadoop framework for addressing big data challenges. Finally, we outline several evaluation benchmarks and potential research directions for big data systems.

Toward Scalable Systems for Big Data Analytics: A Technology Tutorial

Data storage operations, including content-indexing, containerized deduplication, and policy-driven storage, are performed within a cloud environment. The systems support a variety of clients and cloud storage sites that may connect to the system in a cloud environment that requires data transfer over wide area networks, such as the Internet, which may have appreciable latency and/or packet loss, using various network protocols, including HTTP and FTP. Methods are disclosed for content indexing data stored within a cloud environment to facilitate later searching, including collaborative searching. Methods are also disclosed for performing containerized deduplication to reduce the strain on a system namespace, effectuate cost savings, etc. Methods are disclosed for identifying suitable storage locations, including suitable cloud storage sites, for data files subject to a storage policy. Further, systems and methods for providing a cloud gateway and a scalable data object store within a cloud environment are disclosed, along with other features.

Data object store and server for a cloud storage environment, including data deduplication and data management across multiple cloud storage sites

Performing data management operations on replicated data in a computer network. Log entries are generated for data management operations of an application executing on a source system. Consistency point entries are used to indicate a time of a known good, or recoverable, state of the application. A destination system is configured to process a copy of the log and consistency point entries to replicate data in a replication volume, the replicated data being a copy of the application data on the source system. When the replicated data represents a known good state of the application, as determined by the consistency point entries, the destination system(s) may perform a storage operation (e.g., snapshot, backup) to copy the replicated data and to logically associate the copied data with a time information (e.g., time stamp) indicative of the source system time when the application was in the known good state.

Systems and methods for performing data replication

A method is provided for modifying an image. The method comprises displaying an image, the image comprising a portion of an object; and determining if an edge of the object is in a location within the portion. The method further comprises detecting movement, in a member direction, of an operating member with respect to the edge. The method still further comprises moving, if the edge is not in the location, the object in an object direction corresponding to the detected movement; and modifying, if the edge is in the location, the image in response to the detected movement, the modified image comprising the edge in the location.

Information processing apparatus, information processing method and program

A system and method are provided for performing storage operations relating to a first secondary copy of electronic data. A storage policy or storage preferences may dictate that a replication copy should be used in storage operations performed to a particular client, sub-client, data, media or other item. Based on the storage policy, when a new client, sub-client, data, media or other item is received, a media agent determines whether there is a replication copy of the item. In the absence of a replication copy, one may be created. The replication copy may be provided by a third party application, or created by the client or a storage management system component. Information regarding the replication copy and its corresponding first secondary copy may be stored in a database. To optimize use of system resources, storage operations relating to the first secondary copy may be performed using the replication copy instead of the first secondary copy.

Systems and methods for performing replication copy storage operations

In a method of and a system for deduplicating backed-up data backup clients create respective backup tables comprising a list of files and respective file types to be backed up. A backup server receives backup tables from the backup clients. The backup server merges the received backup tables to form a merged backup table. The backup server sorts the merged backup table according to file type from a file type yielding a best deduplication ratio to a file type yielding a worst deduplication ratio, thereby forming a sorted backup table. The backup server requests the files listed in the sorted backup table, in order, from the backup clients. The backup server deduplicates files received from the backup clients, in order, using deduplication parameters optimized according to file type. The method calculates an updated deduplication ratio for each deduplicated file type. Examples of deduplication parameters include chunking techniques and hashing techniques.

Method of and system for deduplicating backed up data in a client-server environment

A method of adaptively selecting an optimum data deduplication chunking method receives a request to deduplicate a file, wherein the file has a file type. The method searches a table of file types, wherein the table includes, for each file type, a chunking method, a deduplication ratio, and a depulication ratio threshold. The method selects a chunking method for the file according to the table. The method chunks the file using the selected chunking method. The method deduplicates the chunked file according to prior art deduplication methods. The method calculates a deduplication ratio for the file type and updates the table with the calculated deduplication ratio for the file type. If the calculated deduplication ratio for the file type is less than the deduplication ratio threshold for the file type, the method selects a new chunking method for the file type and updates the table of file types with the new chunking method for the file type.

Method of and system for adaptive selection of a deduplication chunking technique

A method for deduplicating and managing data blocks within a file system includes adding a deduplication identifier to each pointer pointing to a data block to indicate whether the data block is deduplicated, detecting duplicate data blocks, determining whether one of the duplicate data blocks has been deduplicated, when detected, determining that one duplicate data block is a master copy when it is determined that one duplicate data block has been deduplicated, selecting one of the duplicate data blocks to be a master copy when it is determined that the duplicate data blocks have not been deduplicated, and setting the deduplication identifier of the selected duplicate data block to indicate deduplication, and determining that the other duplicate data block is a new duplicate data block and setting the deduplication identifier of the other duplicate data block to indicate deduplication and directing the respective pointer to the master copy.

File system with internal deduplication and management of data blocks

A load balancing method and system for identifying an input/output (I/O) network path from a set off I/O network paths is provided by the invention. The set off I/O network paths connect a host system via a network to a storage subsystem. The host system comprises at least one host bus adapter (HBA) and the storage subsystem comprises at least one I/O device and the network comprises at least one network device. Each of the HBA, the I/O device and the network device comprise at least one I/O port. For each I/O port of each HBA, an HBA port limit is determined. Additionally the set of I/O network paths which connect the I/O port of each of the HBA via the I/O ports of the network device to the I/O port of the I/O device is identified. Then a fabric utilization limit is determined for each I/O network path and a HBA port utilization is determined for each I/O port of the at least one HBA. All network paths are discarded for which the HBA port utilization is greater than the HBA port limit. For each of the remaining paths a network path distance is determined. All I/O network paths for which the network path distance is greater than the path distance limit are discarded. Then for each of the remaining paths a fabric utilization is determined. All I/O network paths for which the fabric utilization is greater than the fabric utilization limit are discarded and the I/O network path is determined from the remaining network paths.

Load distribution in storage area networks

A method and system for client backup data management and storage using virtual tape libraries (VTLs). A VTL controller executing a software method receives metadata that distinguishes among a plurality of different versions of backup data. The VTL controller determines a latest version of the backup data. The VTL controller determines a migration set of zero or more versions of the backup data. The latest version and any version included in the migration set are included in the plurality of different versions. The VTL controller determines that a storage of the latest version in a first storage medium (e.g., magnetic disk) of the VTL is complete. The VTL controller migrates the migration set to a second storage medium (e.g., magnetic tape) of the VTL if the migration set includes at least one version of the backup data.

Managing storage and migration of backup data

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