Abstract: Disclosed are systems, methods, and non-transitory computer-readable storage media for providing an embedded web view of a folder in a content management system on a web page. For example, a user can request from a content management system code for embedding a web view of a content item or group of content items (e.g., folder) into a web page. After the code is embedded into the webpage, the web page can present a web view of the content item or group of content items that is dynamically updated when the content item or group of content items is updated. Thus, the user is relieved of the burden of updating the web page with new links to reflect changes in content items stored in the online content management system.

Abstract: A materialization configuration request is received via a programmatic interface from a client of a journal-based multi-data-store database. The request indicates a partitioning rule to be used to select, for respective writes indicated in committed transaction entries of a journal, the materialization node at which the writes are to be stored. A control plane component of the database verifies that a set of materialization nodes corresponding to the partitioning rule has been established, and initiates the propagation of writes from the journal to the materialization nodes by respective write appliers.

Abstract: Techniques and tools are described for producing time-series data using faceted search based on document creation time. For example, index information can be created from events (e.g., by adding meta-data and indexing the events as documents). In addition, index information can be created that maps document creation time to time ranges. Search queries can then be executed (e.g., comprising ad-hoc filters to filter on the meta-data), and search results can be faceted on the time ranges to produce time-series data. The time-series data can be graphed to display trends of activity (e.g., trends of events based on user activity).

Abstract: Disclosed below are representative embodiments of methods, apparatus, and systems for managing, monitoring, controlling, and/or classifying assets in an information technology (“IT”) environment. Certain embodiments leverage bath services oriented architecture concepts and event mechanisms to create a platform with which additional controls can easily integrate.

Abstract: A global transaction system receives a transaction request for a plurality of database services of microservices. The global transaction system receives a plurality of local commit decisions of local commit requests from local transaction managers of the database services of the microservices. The local commit request corresponds to the transaction request for each database. The global transaction system generates a physical commit request to each of the local transaction managers based on the local commit decisions and a global commit decision. Each local transaction manager submits the physical commit request to each database server of the database services corresponding to the transaction request.

Abstract: A method and apparatus for replicating a data container of a source storage server at the logical level in an unordered stream of individual data units are described. In certain embodiments, the replication operations can be performed without regard to the differences in geometry of physical persistent storage of the source and destination storage servers and without regard to the differences in data container format of the source and destination storage servers. An initial replication operation of the source data container is performed by transferring the data objects within the source data container to a replica data container in the destination storage server as an unordered stream of individual data units while preserving data object identifiers of the source data objects. Afterwards, incremental replication operations can be performed to capture modifications to the source data container over time after the initial replication operation.

Abstract: Embodiments relate to improving efficiency of data analytics performed on sets of entity data in which different entity properties having very different update frequencies. Time-based analytical queries track the entity states at each moment within a given time window. Analytical queries are executed over a massive number of entity states while using a reasonable memory footprint. The technique partitions the entity properties into partial historical snapshots of data and combines the partial snapshots on demand only as needed to execute analytical queries over business entities. A complete entity state having values for all entity properties is not required to execute most queries. Only partial snapshots including values referenced by the query need to be combined to satisfy the query. Using partial snapshots minimizes data replication, and the snapshots can be efficiently combined into entity states sufficient for query execution.

Abstract: Systems and methods are disclosed to perform data replication based on an update stream from a source data store and over a communication channel that does not guarantee a correct ordering of stream events at the destination data store. In embodiments, an event sender receives the update stream and marks each event with a clock value according to the correct order. The marked events are then sent via the communication channel. In embodiments, an event replicator fetches the events from the communication channel and applies them to the destination data store. Older or duplicate events may be detected using the clock values and appropriately ignored. A tombstone object is maintained separately from the destination object to track deleted data items in order to avoid in-place tombstoning. Conditional updates and delete barriers are used to ensure that the objects are updated correctly by concurrently executing replicator nodes.

Abstract: A method, system, and apparatus for managing a persistent query result set are disclosed. A resource manager is disclosed that receives a query from a client over a computer network. A computer database server is disclosed that executes the query and generates a result set based on and in response to the received query. An execution platform is disclosed that divides the result set into a plurality of chunks, wherein each chunk comprises a portion of the generated result set. The resource manager adds metadata to each of the plurality of chunks. A first chunk of the plurality of chunks comprises metadata pointing to the plurality of chunks. The resource manager delivers at least the first chunk of the plurality of chunks to the client in response to the query. The execution platform offloads the remaining plurality of chunks to cloud storage in parallel.

Abstract: A technique for managing a metadata transaction log consolidates multiple mapping pointer changes that affect a single metadata block in a single transaction entry. The technique creates a data structure that identifies the mapping pointers in the metadata block that are changing, and stores the data structure in the transaction entry along with records that describe the individual mapping pointer changes.

Abstract: A computer architecture for graph processing employs a high-bandwidth memory closely coupled to independent processing elements for searching through a graph using a first set of processing elements operating simultaneously to determine neighbors to a current frontier and second processing elements operating simultaneously to determine a next frontier, this process being repeated to search through graph nodes.

Abstract: An executable utility is injected into cloud-based virtual machines (VMs) that are subject to backups by a data storage management system tasked with protecting the cloud-based VMs and their associated data. The utility is injected into a target VM which is “live” and operating. The utility analyzes the VM's live volume to discover data extents therein, and for each extent computes a respective checksum and determines whether the extent is a “hole.” Afterwards, checksums help identify changed data in successive snapshots of the live volume, so that only changed data will be read and backed up in incremental backups. Time is saved in performing the backup operation first by pre-warming the backup's source volume in parallel with the utility analyzing the live volume, and second by skipping read operations for extents unchanged since a preceding backup. The resulting incremental backup operation is sped up as compared to prior art approaches.

Abstract: In one embodiment, a computer-implemented method executable by a computer to process metadata of a data source is provided. The method includes: processing, by a processor of the computer, the metadata to determine a graph of nodes and edges; converting, by the processor of the computer, the graph from a cyclic graph to an acyclic graph; converting, by the processor of the computer, the acyclic graph to a listing; performing, by the processor of the computer, a topological sort on the listing; and generating a report that includes the sorted listing.

Abstract: An example of an apparatus including a network interface to receive first metadata and second metadata. The first metadata is associated with a first data source and the second metadata is associated with a second data source. The apparatus includes a processor to determine a first series of variance values associated with first metadata and second metadata, and to determine a second series of variance values associated with first metadata and second metadata. Furthermore, the apparatus includes a memory storage unit to store the first series of variance values and the second series of variance values. The apparatus includes an analysis engine to analyze the first series of variance values and the second series of variance values to confirm compatibility between the first data source and the second data source. The second series of variance values is to be analyzed after the first series of variance values is passed.

Abstract: A method for processing snapshots and a distributed block storage system, the method including: acquiring the number of read operations and the number of read/write operations for a data block in a distributed block storage system; on the basis of the number of read operations and the number of read/write operations, determining a target snapshot manner, wherein the target snapshot manner includes copying while writing or re-orienting while writing; on the basis of the target snapshot manner, performing a snapshot operation on the data block in the distributed block storage system.

Abstract: Techniques for leveraging frequent patterns identified in a captured workload are provided. In one approach, multiple frequent patterns detected in a captured workload may be ordered by frequency to determine, for example, which patterns should be targeted for optimization. In another approach, a model of a captured workload is created, where the model comprises nodes that represent templates (which in turn correspond to requests) and edges that represent transitions between templates. The model is used to create an artificial workload, such as a workload that is twice as large as the originally-captured workload. The model may also be edited before creating the artificial workload. In another approach, workload models are compared to identify errors, regressions, or security issues. In another approach, an artificial workload is created for an application that is not yet deployed and then executed to determine whether the artificial workload or the originally-captured workload executed faster.

Abstract: Methods, systems and computer program products implementing hierarchical classification techniques are disclosed. A hierarchical classification system receives training data including labeled transaction records. The system determines tag sequences from the training data. The system clusters the tag sequences into clusters. The system determines a cluster-level classifier that is trained to predict a cluster for an input transaction record. The system determines a respective cluster-specific classifier for each cluster. The system trains the cluster-specific classifier to predict a label of entity of interest for an input transaction record, given a particular cluster. Upon receiving a test transaction record, the system first applies the cluster-level classifier to determine a particular cluster for the test transaction record, and then determines a label of entity of interest of the test transaction record by applying a cluster-specific classifier of that particular cluster.

Abstract: A method, system and computer program product are disclosed for searching for data. In one embodiment, the invention provides a method comprising identifying a query and a search scope including a set of specified entities; and for each of these entities, estimating a number of documents that would be identified in a search through the entity to answer the query. On the basis of this estimating, a subset of the entities is formed. The query and this subset of entities are sent to a search engine to search the subset of entities to answer the query. In one embodiment, the estimating includes collecting statistical information from queries to build up a historical cache using heuristics or machine learning techniques, wherein the query includes a key word and a scope, and the historical cache contains a maximum number of returned results for an entity given the queries executed.

Abstract: A system and method for analyzing coverage, bias and model explanations in large dimensional modeling data includes discretizing three or more variables of a dataset to generate a discretized phase space represented as a grid of a plurality of cells, the dataset comprising a plurality of records, each record of the plurality of records having a value and a unique identifier (ID). A grid transformation is applied to each record in the dataset to assign each record to a cell of the plurality of cells of the grid according to the grid transformation. A grid index is generated to reference each cell using a discretized feature vector. A grid storage for storing the records assigned to each cell of the grid is then created. The grid storage using the ID of each record as a reference to each record and the discretized feature vector as a key to each cell.

Abstract: A system includes reception of a first instruction at a first system to effect a first change to a hierarchy data model, storage of a first record including first values specifying the first change in a local memory of the first system, reception of a second instruction to effect a second change to the hierarchy data model, storage of a second record including second values specifying the second change in the local memory of the first computer system, reception of an instruction to save the changed hierarchy data model, and, in response to the instruction, transmit the first record and the second record to a second system. The first record and the second record are received and merged to generate a third record including third values specifying a third change to the hierarchy data model, and a query language statement is generated to effect the third change to the hierarchy data model based on the third record.