Abstract: Systems and processes for managing a data warehouse using an activity graph are disclosed. One example process may include selectively tracking new versions of an entity based on a tracking type, removing entities based on data retention rules, removing entities based on data decay rules, and summarizing decayed data.

Abstract: A method and apparatus for parallelization of data processing. The method including: parsing a data processing flow to split a write table sequence for the data processing flow; generating a plurality of instances of the data processing flow based at least in part on the split write table sequence; and scheduling the plurality of instances for parallelization of data processing.

Abstract: A method can include initiating execution of a database command, the database command associated with a base table with at least one row to copy to a target table, the database command associated with a non-bulk insert mode; making a run-time decision on whether to automatically convert the insert mode from the non-bulk insert mode to a BULK insert mode based on the number of row buffers filled with rows from the base table during execution of the database command; and inserting at least one row into the target table using an insert mode based on the run-time decision.

Abstract: Techniques for Aligned Run-Length Encoding (ARLE) are described. ARLE is an encoding scheme that transforms sets of same-valued consecutive rows into one or more runs, while enforcing boundaries between the runs at set intervals (e.g. every predetermined number of rows). Consecutive rows that contain the same value, but which cross one or more interval boundaries, are encoded as multiple runs that are divided along those interval boundaries. According to one technique, a database server accelerates query processing by setting the interval size to the word size of the processor performing the predicate comparisons. According to another technique, a database server accelerates row lookup by maintaining an offset array that stores the run offsets into the ARLE data of the run that begins each interval.

Abstract: Techniques for enabling fail-safe operations of storage devices are described. A device may be configured to deallocate one or more clusters assigned to an inode by writing an end of chain terminator value into a new last cluster of a file allocation table entry. In one example, a device may update an allocation bitmap subsequent to writing an end of chain terminator value into a new last cluster of a file allocation table entry. In one example, a device may mark remain clusters as free subsequent to writing an end of chain terminator value into a new last cluster of a file allocation table entry. A device may be configured to allocate clusters to an inode by writing file access table entries for newly allocated clusters.

Abstract: Systems and methods are provided for adding new nodes to a computer networked system. The systems and methods may identify a first set of nodes in a networked computer system. The first set of nodes may be included in a first hash computation that clusters the first set of nodes into communities. An application shard space including a first space and a second space may be generated. The first set of nodes may be mapped to application shards in the first space based on the first hash computation. The application shards in the first space may be assigned to a first set of machines of the networked computer system. The second space may be maintained for mappings of nodes not included in the first hash computation to application shards in the second space.

Abstract: A method, system and computer program product for processing hierarchical data is provided. A method for processing hierarchical data in a relational database includes receiving an input parameter in an initial query for querying an array in a hierarchical data object stored in a table of a relational database, and transforming the initial query into a transformed query configured to place all elements of the array into a different table and to apply a sub-query against the table for the input parameter. Once transformed, predicate evaluation logic of a relational engine of the relational database is applied to the transformed query that is then mapped to the initial query. Finally, responsive to receiving a subsequent instance of the initial query, the mapping is referred to in order to replace the initial query with the transformed query and to subsequently apply the predicate evaluation logic to the transformed query.

Abstract: A method, system and computer program product for processing hierarchical data is provided. A method for processing hierarchical data in a relational database includes receiving an input parameter in an initial query for querying an array in a hierarchical data object stored in a table of a relational database, and transforming the initial query into a transformed query configured to place all elements of the array into a different table and to apply a sub-query against the table for the input parameter. Once transformed, predicate evaluation logic of a relational engine of the relational database is applied to the transformed query that is then mapped to the initial query. Finally, responsive to receiving a subsequent instance of the initial query, the mapping is referred to in order to replace the initial query with the transformed query and to subsequently apply the predicate evaluation logic to the transformed query.

Abstract: Systems and a method for expanding a query are described. The method calculates a diversity index for a plurality of query terms that are included in a plurality of other queries associated with the query. The diversity index is a measure of diversity among the plurality of query terms and relates to differences among the plurality of query terms. The method further compares the diversity index to a threshold value. Finally, the method expands the query with one or more of the plurality of query terms based on the comparison.

Abstract: A first work package defining a data analytic plan associated with a given data problem is obtained. The first work package is generated in accordance with an automated data analytics lifecycle and is implemented in a provisioned system. A second work package defining a revised data analytic plan is obtained. A set of differences between the first work package and the second work package is determined. Cost and time parameters, associated with modifying the provisioned system to implement the set of differences between the first work package and the second work package, are computed. The set of differences and the computed cost and time parameters are presented. The provisioned system is automatically re-configured in accordance with at least a portion of the set of differences and based on the computed cost and time parameters.

Abstract: Method and systems personalizing the search results presented to a user in an electronic marketplace. A search query is received and a set of search results related to the search query are obtained. Individual entries of the search results are associated with a category type. The search results are sorted in a number of category groups according to the category type. An entry from each category group is selected and scores are determined for the selected entries. A highest scored entry is assigned to a highest available position in a resultant search result set. The scores for the entries that remain unassigned are increased. For the category group corresponding to the assigned entry, another entry is selected and scored. A highest entry score is assigned the next highest position. The process may continue recursively until all, or a threshold number, of entries have been assigned to the resultant list.

Abstract: This disclosure relates to a method, article of manufacture, and apparatus for generating a snapshot map used to facilitate storage system management. In some embodiments, this includes displaying a snapshot map comprising a set of components, each of the component representing a snapshot configuration characteristic, selecting a component from the set of components, obtaining the snapshot configuration characteristic represented by the selected component, dragging the selected component from the snapshot map, dropping the selected component to a configuration display, generating configurations based on the snapshot configuration characteristic, summarizing in the configuration display the configurations, and confirming the configurations.

Abstract: Ordering data writes includes at least some of a group of local storage devices receiving a first plurality of data writes, waiting for all of the local storage devices to be ready to switch cycles and causing a coordinated and synchronized cycle switch after all of the local storage devices are ready to switch cycles by sending a first command to each of the local storage devices where the first plurality of data writes are associated with a particular cycle on each local storage device in the group. Ordering data writes also includes at least some of the group of local storage devices receiving a second plurality of writes after initiating the coordinated and synchronized cycle switch where all of the second plurality of writes are associated with a cycle different from the particular cycle on each local storage device.

Abstract: A multi-cluster database management system is disclosed that distributes and manages data across a multi-cluster database through the use of cluster partitions. The multi-cluster database management system assigns cluster partitions to clusters of the multi-cluster database. The multi-cluster database management system can evenly or substantially evenly divide the cluster partitions and associated data among the clusters of the multi-cluster database. The multi-cluster database management system can scale in or out by adding or removing clusters from the multi-cluster database when needed or desired. Once a cluster is added or removed, the multi-cluster database management system re-balances the cluster partitions and the associated data across the clusters of the modified multi-cluster database.

Abstract: Methods, devices, and storage media are provided for preserving the context of a server-client session. A server generates an initial context and a context for each user command executed in a first session and sends context to a client with the return for each command. The context describes software, session state, returned data, and/or hardware characteristics of a server-side environment for the first session. The client receives and stores the context with each user command. Upon determining that the database session should be rebuilt in the second session, the client sends initial context. A server for the second session receives the initial context and determines whether commands should be replayed in the second session. If commands are replayed, the server validates that server environment and client-visible results for each command in the second session match that from execution in the first session using the context for that command.

Abstract: A method and system for storage checkpointing of an independent computer application. The independent computer application is launched by a coordinator; and the coordinator installs at least one of an exec interceptor and a fork interceptor. The coordinator also installs at least one file operations interceptor for all file operations and registers the independent computer application with the coordinator. The independent computer application is run and the at least one file operations interceptor is called upon encountering a file operation. The file operations interceptor logs a file event in a file operations database and passes the operation to at least one of a file system, an operating system, at least one or more device drivers, and a storage disk via a storage interface. The file operations interceptor also verifies that the file operation has been issued.

Abstract: Database system comprising nodes configured in a tree structure is disclosed. The system includes a shared metadata store on the root node. Child nodes may request metadata from their ancestors. Parents will forward the request upward until the metadata is found or the root node is reached.

Abstract: Transactional and non-transactional data for maintaining session state is described. In a session, a server instance receives, from a client, a request to execute transactional commands and non-transactional commands. The server instance sends at least one first directive executable at the client to store, in a first set of information, one or more first items representing one or more particular transactional commands that are open but not yet committed. The first set of information is maintained separately from a second set of information including one or more second items representing one or more particular non-transactional commands that have been processed. Based on committing one or more particular transactional commands, the server instance sends at least one second directive executable at the client to purge, from the first set of information, the one or more first items without purging, from the second set of information, the one or more second items.

Abstract: One embodiment of the present invention provides a recommendation system. During operation, the system receives context information associated with the user, updates a plurality of user models based on the received context information, and identifies at least one spatial data structure that stores a plurality of items. A respective item is stored within the spatial data structure based on a vector value associated with the item. The system then queries the spatial data structure to obtain a first set of recommendable items that have vector values within a predetermined range, calculates a score for each item within the set of recommendable items based on the plurality of the user models and a characterization vector associated with each item, ranks the items within the set of recommendable items based on calculated scores, and recommends one or more top-ranked items to the user.

Abstract: A data normalization system is described herein that represents multiple data types that are common within database systems in a normalized form that can be processed uniformly to achieve faster processing of data on superscalar CPU architectures. The data normalization system includes changes to internal data representations of a database system as well as functional processing changes that leverage normalized internal data representations for a high density of independently executable CPU instructions. Because most data in a database is small, a majority of data can be represented by the normalized format. Thus, the data normalization system allows for fast superscalar processing in a database system in a variety of common cases, while maintaining compatibility with existing data sets.