Abstract: Techniques herein decouple available results, from graph analysis execution, to adapt to various deployment configurations. In an embodiment, a graph engine is deployed that has multiple mutually-exclusive configuration modes that include being embedded within a software application, centrally serving software applications, or distributed amongst a cluster of computers. Based on a current configuration mode of the graph engine, a software application receives or generates an analysis request to process a graph. The software application provides the analysis request to the graph engine in exchange for access to a computational future, of the graph engine, that is based on the analysis request and the graph. Based on a proxy of said computational future, the software application accesses a result of the analysis request. In an embodiment, a remote proxy exchanges representational state transfer (REST) messages.

Abstract: Techniques and a system are provided for managing resources used by user-provided programs. The system includes an application programming interface (API) that allows user-provided programs to access memory resources managed by functions provided by the API. The system stores memory-usage records made during memory allocations. Memory-usage records may be used to identify memory resources, analyze memory usage, and provide other features.

Abstract: Techniques and a system are provided for managing resources used by user-provided programs. The system includes an application programming interface (API) that allows user-provided programs to access memory resources managed by functions provided by the API. The system stores memory-usage records made during memory allocations. Memory-usage records may be used to identify memory resources, analyze memory usage, and provide other features.

Abstract: Techniques and a system are provided for managing resources used by user-provided programs. The system includes an application programming interface (API) that allows user-provided programs to access memory resources managed by functions provided by the API. The system stores memory-usage records made during memory allocations. Memory-usage records may be used to identify memory resources, analyze memory usage, and provide other features.

Abstract: Techniques for efficiently loading graph data into memory are provided. A plurality of node ID lists are retrieved from storage. Each node ID list is ordered based on one or more order criteria, such as node ID, and is read into memory. A new list of node IDs is created in memory and is initially empty. From among the plurality of node ID lists, a particular node ID is selected based on the one or more order criteria, removed from the node ID list where the particular node ID originates, and added to the new list. This process of selecting, removing, and adding continues until no more than one node ID list exists, other than the new list. In this way, the retrieval of the plurality of node ID lists from storage may be performed in parallel while the selecting and adding are performed sequentially.

Abstract: Techniques herein decouple available results, from graph analysis execution, to adapt to various deployment configurations. In an embodiment, a graph engine is deployed that has multiple mutually-exclusive configuration modes that include being embedded within a software application, centrally serving software applications, or distributed amongst a cluster of computers. Based on a current configuration mode of the graph engine, a software application receives or generates an analysis request to process a graph. The software application provides the analysis request to the graph engine in exchange for access to a computational future, of the graph engine, that is based on the analysis request and the graph. Based on a proxy of said computational future, the software application accesses a result of the analysis request. In an embodiment, a remote proxy exchanges representational state transfer (REST) messages.

Abstract: Techniques and a system are provided for managing resources used by user-provided programs. The system includes an application programming interface (API) that allows user-provided programs to access memory resources managed by functions provided by the API. The system stores memory-usage records made during memory allocations. Memory-usage records may be used to identify memory resources, analyze memory usage, and provide other features.

Abstract: Systems and methods for interactive front-end graph analysis are provided herein. According to one embodiment, a front-end application receives, from a compiler, first meta-information for a particular graph analysis procedure, where the first meta-information identifies a set of input parameters for passing graph information to the particular graph analysis procedure. The front-end application registers, using the first meta-information, the particular graph analysis procedure as an available command. The front-end application also receives second meta-information that identifies, for each respective graph object of a set of one or more graph objects, a respective set of graph characteristics. In response to receiving a request to apply the particular graph analysis procedure to the set of one or more graph objects, the front-end application enforces a set of one or more constraints based on the first meta-information and the second meta-information.

Abstract: Systems and methods for interactive front-end graph analysis are provided herein. According to one embodiment, a front-end application receives, from a compiler, first meta-information for a particular graph analysis procedure, where the first meta-information identifies a set of input parameters for passing graph information to the particular graph analysis procedure. The front-end application registers, using the first meta-information, the particular graph analysis procedure as an available command. The front-end application also receives second meta-information that identifies, for each respective graph object of a set of one or more graph objects, a respective set of graph characteristics. In response to receiving a request to apply the particular graph analysis procedure to the set of one or more graph objects, the front-end application enforces a set of one or more constraints based on the first meta-information and the second meta-information.

Abstract: Techniques for efficiently loading graph data into memory are provided. A plurality of node ID lists are retrieved from storage. Each node ID list is ordered based on one or more order criteria, such as node ID, and is read into memory. A new list of node IDs is created in memory and is initially empty. From among the plurality of node ID lists, a particular node ID is selected based on the one or more order criteria, removed from the node ID list where the particular node ID originates, and added to the new list. This process of selecting, removing, and adding continues until no more than one node ID list exists, other than the new list. In this way, the retrieval of the plurality of node ID lists from storage may be performed in parallel while the selecting and adding are performed sequentially.