Abstract: Techniques for providing horizontally scaled caching of versioned data are provided. In some aspects, the techniques described herein relate to a method including initializing a first version cache (VC) object based on a version of data stored in a data storage device; replicating the first VC to generate a second VC; receiving a write operation at the first VC; generating a delta for the write operation, the delta representing a change in the version of data; writing the delta to a persistent replication log, the persistent replication log storing an ordered set of deltas including the delta; writing data in the write operation to the data storage device; and applying the ordered set of deltas at the second VC to update data stored by the second VC.

Abstract: Techniques for providing horizontally scaled caching of versioned data are provided. In some aspects, the techniques described herein relate to a method including initializing a first version cache (VC) object based on a version of data stored in a data storage device; replicating the first VC to generate a second VC; receiving a write operation at the first VC; generating a delta for the write operation, the delta representing a change in the version of data; writing the delta to a persistent replication log, the persistent replication log storing an ordered set of deltas including the delta; writing data in the write operation to the data storage device; and applying the ordered set of deltas at the second VC to update data stored by the second VC.

Abstract: Techniques for providing horizontally scaled caching of versioned data are provided. In some aspects, the techniques described herein relate to a method including initializing a first version cache (VC) object based on a version of data stored in a data storage device; replicating the first VC to generate a second VC; receiving a write operation at the first VC; generating a delta for the write operation, the delta representing a change in the version of data; writing the delta to a persistent replication log, the persistent replication log storing an ordered set of deltas including the delta; writing data in the write operation to the data storage device; and applying the ordered set of deltas at the second VC to update data stored by the second VC.

Abstract: Systems and methods for precomputing data and storing cache objects corresponding to the precomputed data are described. A system creates a new cache object when a user interacts with the system. The system precomputes formulas in the newly created cache object by replacing the formulas with corresponding calculated values. The system precomputes the formulas in the background (i.e., the user is not presented with the precomputed values while the user is manipulating the data). The system may persistently store a precomputed version cache object in a dedicated version cache storage for later use. If updates are performed to the structure and/or values of a version represented in a precomputed version cache object, effected parts of the version cache object are invalidated by replacing calculated values with the underlying formulas.

Abstract: A method of transforming requests into queries on a data store is disclosed. The method comprises receiving, by a processor, a request for data stored in a data store, the request being in a request query language based on a domain model, the request including a first part specifying a navigation path of one or more joins and one or more aggregations, the request including a second part specifying details of the one or more joins and aggregations; mapping, by the processor, entities specified in the request to a plurality of tables and a plurality of fields in the data store using metadata associated with the domain model; creating table aliases based on the plurality of tables or the one or more joins; creating field aliases based on the plurality of fields or the one or more aggregations; assembling the table aliases and the field aliases into one or more queries associated with the data store; sending the one or more queries to the data store.

Abstract: A system for assigning a workload to compute resources includes an interface and a processor. The interface is configured to receive a workload. The processor is configured to break the workload into a set of subproblems; and for a subproblem of the set of subproblems: determine whether the subproblem benefits from intersheet parallelism; determine whether the subproblem benefits from intrasheet parallelism; determine whether the subproblem benefits from directed acyclic graph (DAG) partitioning; and assign the subproblem, wherein assigning the subproblem utilizes optimization when appropriate based at least in part on benefits from the intersheet parallelism, the intrasheet parallelism, and the DAG partitioning.

Abstract: In an embodiment, a method comprises storing metadata that maps a domain model to data stored in a plurality of data stores, each data store being associated with a particular query language, the domain model describing the data and relationships between the data. The method comprises receiving a request for data stored in a first data store of, the request being in a request query language based on the domain model. The method comprises generating an abstract syntax tree indicating a field selection, an entity path, and a condition based on the request; generating a structure model comprising one or more aggregation levels for one or more entities; and generating annotations comprising query language aliases for portions of the request and correlating the portions of the request with the metadata. The method comprises generating queries in a first query language associated with the first data store based on the annotations; and sending the queries to the first data store.

Abstract: Disclosed herein are system, method, and computer program product embodiments for performing ad-hoc analytical queries of graph data. An embodiment operates by receiving a graph pattern for a subgraph of interest. The facts of interest are then selected from graph data based on the received graph pattern. Dimensions are then defined based on a dimension seed pattern and a set of level expressions, and measures are defined based on a computation function and an aggregation function. A graph cube is formed based on the selected facts and the defined dimensions and measures. Because the facts, dimensions, and measures of interest are defined at the time of an analytical query, a user does not have to define such facts, dimensions, and measures, or know which analytical queries will be of interest, at the time of data collection.

Abstract: In an embodiment, a method comprises storing metadata that maps a domain model to data stored in a plurality of data stores, each data store being associated with a particular query language, the domain model describing the data and relationships between the data. The method comprises receiving a request for data stored in a first data store of, the request being in a request query language based on the domain model. The method comprises generating an abstract syntax tree indicating a field selection, an entity path, and a condition based on the request; generating a structure model comprising one or more aggregation levels for one or more entities; and generating annotations comprising query language aliases for portions of the request and correlating the portions of the request with the metadata. The method comprises generating queries in a first query language associated with the first data store based on the annotations; and sending the queries to the first data store.

Abstract: In an embodiment, a method comprises generating and storing metadata that maps a domain model to data stored in a data store, wherein the domain model describes the data and relationships between the data; receiving, from a client application, a request for data stored in the data store, wherein the request is in a first query language; translating the request into one or more queries based on the metadata, wherein the one or more queries are in a second query language; sending the one or more queries to the data store; receiving a first result set from the data store, based on the data store executing the one or more queries.

Abstract: A computing system and platform uses various types of data stores to allow efficient querying of, and accelerated access to, extremely large data sets. One such data store is a dimension store that combines key-value and columnar stores, access to which is provided by several selectable mechanisms chosen based the nature of the data of interest. These include bitmap-based access, us of an optimized columnar data format, and access via namespace identifiers. A compressed, optimized page data format is provided for storing and analyzing large fact-based data. The complex dimension store is used to provide complex relationships and interpretation of the fact-based data, enabling high-performance advanced queries, with bitmap indexes passed between the two stores. Dimension data is stored in an encrypted manner throughout the system, and can be exchanged among parties in a secure manner.

Abstract: Systems and methods for precomputing data and storing cache objects corresponding to the precomputed data are described. A system creates a new cache object when a user interacts with the system. The system precomputes formulas in the newly created cache object by replacing the formulas with corresponding calculated values. The system precomputes the formulas in the background (i.e., the user is not presented with the precomputed values while the user is manipulating the data). The system may persistently store a precomputed version cache object in a dedicated version cache storage for later use. If updates are performed to the structure and/or values of a version represented in a precomputed version cache object, effected parts of the version cache object are invalidated by replacing calculated values with the underlying formulas.

Abstract: In an embodiment, a method comprises generating and storing metadata that maps a domain model to data stored in a data store, wherein the domain model describes the data and relationships between the data; receiving, from a client application, a request for data stored in the data store, wherein the request is in a first query language; translating the request into one or more queries based on the metadata, wherein the one or more queries are in a second query language; sending the one or more queries to the data store; receiving a first result set from the data store, based on the data store executing the one or more queries.

Abstract: A system, computer-implemented method, and computer-readable storage medium for generating a block-based index, are provided. A block index is generated where the block index comprises a plurality of blocks and a block corresponds to a section of a graph column that stores a value. A block range vector is also generated for the index where the block range vector includes range information for the block that corresponds to the section of the graph and where the block-based index facilitates traversal of the graph column that searches for the value by constraining the traversal to the section of the graph.

Abstract: Among other disclosed subject matter, a computer program product is tangibly embodied in a computer-readable storage medium and includes instructions that when executed by a processor perform a method for recording information about an item. The method includes assigning a unique identifier to an item in a repository, the item supporting versioning and being subject to a data model having no predefined schema for items. The method includes associating a first attribute with the unique identifier, the first attribute being part of the item and being configured for modification. The method includes associating the first attribute with a version number, wherein the versioning is supported without recording in the repository a time period when the first attribute is valid.

Abstract: A system, computer-implemented method, and a computer-readable storage medium for a data graph traversal are provided. The input parameters for traversing the data graph are received. The data graph having a set of vertices and a set of edges are stored in a column based format in a memory cache of a computer device based on the input parameters is traversed. The traversal generates a set of traversed vertices that are the result of the graph traversal.

Abstract: A system, computer-implemented method, and a computer-readable storage medium for a traversal of a property graph, are provided. The edge table of the property graph is divided into a plurality of fragments. A first fragment is selected for traversal using a set of selected vertices, where the traversal identifies a set of edges. Based on the set of edges, a set of adjacent vertices is determined during the traversal. A set of discovered vertices in the property graph is determined based on the set of selected vertices and the set of adjacent vertices.

Abstract: An execution framework allows developers to write sequential computational logic, constrained for the runtime system to efficiently parallelize execution of custom business logic. The framework can be leveraged to overcome limitations in executing low level procedural code, by empowering the system runtime environment to parallelize this code. Embodiments employ algorithmic skeletons in the realm of optimizing/executing data flow graphs of database management systems. By providing an extensible set of algorithmic skeletons the developer of custom logic can select the skeleton appropriate for new custom logic, and then fill in the corresponding computation logic according to the structural template of the skeleton.

Abstract: A system, computer-implemented method, and a computer-readable medium for determining why a query returns a null set in a database management system. When the database management system receives a query graph, database management system compares the query graph to the data graph. Based on the comparison, database management system identifies a discovered component of the query graph and a missing component of the query graph, wherein the missing query component indicates a reason for the null set.

Abstract: Disclosed herein are system, method, and computer program product embodiments for performing ad-hoc analytical queries of graph data. An embodiment operates by receiving a graph pattern for a subgraph of interest. The facts of interest are then selected from graph data based on the received graph pattern. Dimensions are then defined based on a dimension seed pattern and a set of level expressions, and measures are defined based on a computation function and an aggregation function. A graph cube is formed based on the selected facts and the defined dimensions and measures. Because the facts, dimensions, and measures of interest are defined at the time of an analytical query, a user does not have to define such facts, dimensions, and measures, or know which analytical queries will be of interest, at the time of data collection.