Abstract: Herein are techniques that concurrently populate entries in a compressed sparse row (CSR) encoding, of a type of edge of a heterogenous graph. In an embodiment, a computer obtains a mapping of a relational schema to a graph data model. The relational schema defines vertex tables that correspond to vertex types in the graph data model, and edge tables that correspond to edge types in the graph data model. Each edge type is associated with a source vertex type and a target vertex type. For each vertex type, a sequence of persistent identifiers of vertices is obtained. Based on the mapping and for a CSR representation of each edge type, a source array is populated that, for a same vertex ordering as the sequence of persistent identifiers for the source vertex type, is based on counts of edges of the edge type that originate from vertices of the source vertex type.

Abstract: In an embodiment, a computer obtains a mapping of a relational schema of a database to a graph data model. The relational schema identifies vertex table(s) that correspond to vertex type(s) in the graph data model and edge table(s) that correspond to edge type(s) in the graph data model. Each edge type is associated with a source vertex type and a target vertex type. Based on that mapping, a forward compressed sparse row (CSR) representation is populated for forward traversal of edges of a same edge type. Each edge originates at a source vertex and terminates at a target vertex. Based on the forward CSR representation, a reverse CSR representation of the edge type is populated for reverse traversal of the edges of the edge type. Acceleration occurs in two ways. Values calculated for the forward CSR are reused for the reverse CSR. Elastic and inelastic scaling may occur.

Abstract: Herein are techniques that concurrently populate entries in a compressed sparse row (CSR) encoding, of a type of edge of a heterogenous graph. In an embodiment, a computer obtains a mapping of a relational schema to a graph data model. The relational schema defines vertex tables that correspond to vertex types in the graph data model, and edge tables that correspond to edge types in the graph data model. Each edge type is associated with a source vertex type and a target vertex type. For each vertex type, a sequence of persistent identifiers of vertices is obtained. Based on the mapping and for a CSR representation of each edge type, a source array is populated that, for a same vertex ordering as the sequence of persistent identifiers for the source vertex type, is based on counts of edges of the edge type that originate from vertices of the source vertex type.

Abstract: In an embodiment, a computer obtains a mapping of a relational schema of a database to a graph data model. The relational schema identifies vertex table(s) that correspond to vertex type(s) in the graph data model and edge table(s) that correspond to edge type(s) in the graph data model. Each edge type is associated with a source vertex type and a target vertex type. Based on that mapping, a forward compressed sparse row (CSR) representation is populated for forward traversal of edges of a same edge type. Each edge originates at a source vertex and terminates at a target vertex. Based on the forward CSR representation, a reverse CSR representation of the edge type is populated for reverse traversal of the edges of the edge type. Acceleration occurs in two ways. Values calculated for the forward CSR are reused for the reverse CSR. Elastic and inelastic scaling may occur.

Abstract: Herein are techniques that concurrently populate entries in a compressed sparse row (CSR) encoding, of a type of edge of a heterogenous graph. In an embodiment, a computer obtains a mapping of a relational schema to a graph data model. The relational schema defines vertex tables that correspond to vertex types in the graph data model, and edge tables that correspond to edge types in the graph data model. Each edge type is associated with a source vertex type and a target vertex type. For each vertex type, a sequence of persistent identifiers of vertices is obtained. Based on the mapping and for a CSR representation of each edge type, a source array is populated that, for a same vertex ordering as the sequence of persistent identifiers for the source vertex type, is based on counts of edges of the edge type that originate from vertices of the source vertex type.

Abstract: Herein are techniques that concurrently populate entries in a compressed sparse row (CSR) encoding, of a type of edge of a heterogenous graph. In an embodiment, a computer obtains a mapping of a relational schema to a graph data model. The relational schema defines vertex tables that correspond to vertex types in the graph data model, and edge tables that correspond to edge types in the graph data model. Each edge type is associated with a source vertex type and a target vertex type. For each vertex type, a sequence of persistent identifiers of vertices is obtained. Based on the mapping and for a CSR representation of each edge type, a source array is populated that, for a same vertex ordering as the sequence of persistent identifiers for the source vertex type, is based on counts of edges of the edge type that originate from vertices of the source vertex type.

Abstract: A method for managing class metadata in a garbage collected system, including (i) allocating a metaspace to a class loader of a mutator using a memory heap, where the metaspace is configured to store the class metadata generated by the class loader, (ii) storing, in the metaspace, class metadata items associated with classes defined by the class loader, where the class metadata items and the class loader are coterminous, and where all of the class metadata items are identified by a garbage collector as live if any of the class metadata items is reachable by the mutator, (iii) updating a linkset graph during resolution of symbolic links to sumarize cross-metaspace references, and (iv) reclaiming, by the garbage collector based on a pre-determined algorithm using the metaspace, memory locations unreachable by the mutator, where all memory locations allocated to the class metadata items are reclaimed together as a group.

Abstract: A method for managing class metadata in a garbage collected system, including (i) allocating a metaspace to a class loader of a mutator using a memory heap, where the metaspace is configured to store the class metadata generated by the class loader, (ii) storing, in the metaspace, class metadata items associated with classes defined by the class loader, where the class metadata items and the class loader are coterminous, and where all of the class metadata items are identified by a garbage collector as live if any of the class metadata items is reachable by the mutator, (iii) updating a linkset graph during resolution of symbolic links to sumarize cross-metaspace references, and (iv) reclaiming, by the garbage collector based on a pre-determined algorithm using the metaspace, memory locations unreachable by the mutator, where all memory locations allocated to the class metadata items are reclaimed together as a group.

Abstract: A method for garbage collection, involving identifying a first object referenced by a second object, determining whether the address of the first object is lower than a pointer position, in response to determining that the address of the first object is lower than the pointer position, adding an identifier for the first object to a mark stack, determining whether a number of identifiers in the mark stack has reached a flush threshold, in response to determining that the number of identifiers in the mark stack has reached the flush threshold, setting a set of marks included in a mark bitmap to grey, setting a region field of a rescan map to indicate that a region of the mark bitmap includes any of the set of marks, and performing a rescan of the region based on the region field.

Abstract: A method for performing garbage collection promotion, comprising determining that an age of a large young object is greater than a predetermined tenuring threshold, wherein the predetermined tenuring threshold specifies an age beyond which objects are promoted, setting a plurality of types of a plurality of large memory regions from young to old to promote the large young object to a large old object, wherein the plurality of large memory regions host the large young object, scavenging references of the large old object, wherein the large old object is a large promoted object, scanning a large young object list to identify a plurality of unvisited large young objects, wherein a plurality of visited bits of the plurality of unvisited large young objects are unset, and releasing a plurality of unvisited large memory regions, wherein the unvisited large memory regions host the plurality of unvisited large young objects.

Abstract: A method for garbage collection, involving identifying a first object referenced by a second object, determining whether the address of the first object is lower than a pointer position, in response to determining that the address of the first object is lower than the pointer position, adding an identifier for the first object to a mark stack, determining whether a number of identifiers in the mark stack has reached a flush threshold, in response to determining that the number of identifiers in the mark stack has reached the flush threshold, setting a set of marks included in a mark bitmap to grey, setting a region field of a rescan map to indicate that a region of the mark bitmap includes any of the set of marks, and performing a rescan of the region based on the region field.

Abstract: A method for performing garbage collection promotion, comprising determining that an age of a large young object is greater than a predetermined tenuring threshold, wherein the predetermined tenuring threshold specifies an age beyond which objects are promoted, setting a plurality of types of a plurality of large memory regions from young to old to promote the large young object to a large old object, wherein the plurality of large memory regions host the large young object, scavenging references of the large old object, wherein the large old object is a large promoted object, scanning a large young object list to identify a plurality of unvisited large young objects, wherein a plurality of visited bits of the plurality of unvisited large young objects are unset, and releasing a plurality of unvisited large memory regions, wherein the unvisited large memory regions host the plurality of unvisited large young objects.