Patent Publication Number: US-9418176-B2

Title: Graph-based system and method of information storage and retrieval

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. patent application Ser. No. 14/590,845, filed Jan. 6, 2015, which is a continuation of U.S. patent application Ser. No. 14/146,623, filed Jan. 2, 2014, now U.S. Pat. No. 8,954,441, issued Feb. 10, 2015. 
    
    
     TECHNICAL FIELD 
     This application relates to the technical fields of software and/or hardware technology and, in one example embodiment, to a graph-based system and method of information storage and retrieval. 
     BACKGROUND 
     Storing large numbers of documents in an efficient and quick-to-retrieve manner is a common problem with databases. A number of different solutions have been provided in the database arena, where data is stored in a single database in a single domain. However, recently web sites such as social networks have attempted to gather and access documents from different domains and combine them to satisfy a particular business case. A number of problems have been encountered in such situations, including having to deal with redundant data stores for relationships, duplication of operation and maintenance effort, and significant scalability issues that need to be addressed frequently. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
       Embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like reference numbers indicate similar elements and in which: 
         FIG. 1  is a graph for a document in accordance with an example embodiment. 
         FIG. 2  is a block diagram illustrating a system of implementing Every Document as a graph (EVG) in accordance with an example embodiment. 
         FIG. 3  is a block diagram illustrating various layers of a server application in accordance with an example embodiment. 
         FIG. 4  is a block diagram illustrating an EVG graph in accordance with an example embodiment. 
         FIG. 5  is a block diagram illustrating an EVG graph in accordance with another example embodiment. 
         FIG. 6  is a block diagram illustrating an EVG system in accordance with an example embodiment. 
         FIG. 7  is a block diagram illustrating a task chain in accordance with an example embodiment. 
         FIG. 8  is a sequence diagram illustrating a method  800  in accordance with an example embodiment. 
         FIG. 9  is a flow diagram illustrating a method in accordance with an example embodiment. 
         FIG. 10  is a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. 
     
    
    
     DETAILED DESCRIPTION 
     in an example embodiment, a uniform, generic system for user case-specific relationships is provided. A graph-based model may be provided to allow for simpler and consistent mental models. Users are able to define domain models and perform queries in an efficient and easy-to-understand manner. Furthermore, the system simplifies scaling and operations by leveraging a small number of relatively generic systems and an open multi-tenant architecture for features of appropriate scale. Data sources are abstracted, and the system is able to store and retrieve metadata about the data sources and is able to efficiently use this metadata to gather desired data from the data sources. In this way, a service provider such as a social networking website may accelerate time-to-market of new features and services and reduce cost by enabling reuse and abstraction of existing data objects, which has the effect of reducing duplicate effort. 
     As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Similarly, the term “exemplary” merely means an example of something or an exemplar and not necessarily a preferred or ideal means of accomplishing a goal. For the purposes of this description, the phrase “an on-line social networking application” may be referred to as and used interchangeably with the phrase “an on-line social network” or merely “a social network.” It will also be noted that an on-line social network may be any type of an on-line social network such as, for example, a professional network, an interest-based network, or any on-line networking system that permits users to join as registered members. For the purposes of this description, registered members of an on-line social network may be referred to as simply members. 
     Each member of an on-line social network is represented by a member profile (also referred to as a profile of a member or simply a profile). A member profile may be associated with social links that indicate that member&#39;s connection to other members of the social network. A member profile may also include or be associated with comments or endorsements from other members of the on-line social network, with links to other network resources such as, for example, publications, etc. As mentioned above, an on-line social networking system may be designed to allow registered members to establish and document networks of people they know and trust professionally. Any two members of a social network may indicate their mutual willingness to be “connected” in the context of the social network, in that they can view each other&#39;s profiles, profile recommendations and endorsements for each other and otherwise be in touch via the social network. Reputation scores may be computed based on information obtained from trusted sources, such as patent databases, publications databases, skills, endorsement of skills, or even enterprise contracts. 
     In addition to member profiles, there may be a number of different types of data stored by the social network site. Additionally, data from other data sources, such as audio and video content, email and business documents, calendars, text messages, etc. may also be accessed by the social network site. It would be helpful if all this data can be accessed in an efficient manner and that whatever features the social network site is attempting to set up to access new data types or new data sources can be set up in an efficient manner. 
     In an example embodiment, a concept known as Every Document as a graph (EVG) is introduced. EVG is a shared, multi-tenant service for supporting entity persistence and discovery, managing relationships, and integrating social gestures. It is a layer on top of data store implementations such as Espresso, Voldemort, Oracle, etc. and acts as a proxy to these data stores. 
     In an example embodiment, EVG also acts to assemble complex documents and display them as a simple query, offer strongly-typed representations of data to use case-specific clients, and use metadata to function when new types of edges and entities are introduced, without having to rebuild, redeploy, or disrupt existing clients. 
     In an example embodiment, EVG breaks down rich domain objects that are often represented as hierarchical documents into a graph where individual entities are tied together via directional associations or edges. In EVG, every relationship is represented as an edge and every rich object or document is a graph. 
       FIG. 1  is a graph  100  for a document in accordance with an example embodiment. Here, a member node  102  is linked to a treasuryMedia node  104  via an edge  106 , representing the relationship between the member node  102  and the treasuryMedia node  104 . To get to a member&#39;s media content stored in a treasuryMedia entity, the member2Media edge  106  may be used. 
     The generic framework of EVG makes it easy for the user to assemble a graph from distinct data stores. In an example embodiment, from a database perspective, EVG follows a normalized approach where entities and edges are stored in separate tables, making it easy to recombine these elements to satisfy different use cases. In an example embodiment, EVG is metadata-driven to distinguish stored edges from entities. The metadata also may map entities to physical data stores. EVG can then handle the assembly of these data objects based on an intuitive query language expression. 
     For purposes of this disclosure, a document may be considered to be a rich data object combining elements of different domains. An element may be considered a generic term for a data envelope, and can either be an entity or an edge. An entity or vertex may be considered a material part of a domain model carrying attributes. An association or relationship may be considered to be a direct connection between two entities. An edge may be considered to be a meaning attached to an association. A gesture may be considered a sum of social interactions with entities (e.g., comments, likes, feeds, etc.). A feed may be considered to be an activity stream for a given number of entities. 
       FIG. 2  is a block diagram illustrating a system  200  of implementing EVG in accordance with an example embodiment. A client application  202  may contain an EVG client library  204 , which may perform validation  206  and stencilization  208  activities. A server application  210  may perform assembly  212  of each EVG graph. A metadata store  214  may store and serve mappings, queries, association constraints, registries of virtual associations, and other metadata related to the graphs. An entity store  216  may store and serve entity data. The metadata store  214  may be partitioned by entity. An edge store  218  may store associative links/edges. In an example embodiment, all edges are stored in the same partition/database/table, with distinction between adjacency list and “row-per-edge” storage format. 
     The assembly  212  may construct the graphs by accessing one or more external data stores  220 A,  220 B, and storing the corresponding graph information in the metadata store  214 , entity store  216 , and edge store  218 . A search service  222  may be used to find relationships spanning several degrees of separation, and traverse bidirectional relationships. The search service  222  may also extend an EVG query to support the indexing of metadata. 
     In an example embodiment, at least one of the external data sources  220 A,  220 B is a key-value store system, such as Espresso. Key-value store systems lose the ability to perform traditional JOIN operations common to relational databases. In light of this, the system may be designed with query parameters and features designed to maintain edges in a manner that helps make up for the loss of such traditional JOIN operations. 
       FIG. 3  is a block diagram illustrating various layers of a server application  210  in accordance with an example embodiment. A business layer  300  may allow assembly of data per the client&#39;s specification via EVG graphs, and may manage mapping of entity types to uniform resource names (URN) and uniform resource identifiers (URI). A domain layer  302  may define and publish schemas, formulate queries and invocations, take on the responsibility of reconstituting foreign domain objects, and use visibility constraints to filter obscure pieces of data that are restricted based on domain logic, such as privacy settings, subscription status, etc. In an example embodiment, the domain layer  302  may be implemented using a domain-specific REST.LI service. REST.LI is a Java framework that allows users to create clients and servers using a Representational State Transfer (REST) style. 
     The domain layer  302  may also, via the EVG client library  204 , perform validations driven by schemas and provide strongly typed interfaces proxying data maps (stencils). 
     A presentation layer  304  may then emit flattened, simplified Javascript Object Notation (JSON) for consumption by clients, and take user input to be persisted and send it to the business layer  300  to be stored in an EVG graph. 
     In an example embodiment, data sources are abstracted to provide a single interface for multiple data sources. The EVG graphs stich together heterogeneous data and a query engine is then able to access multiple data stores in parallel. By partitioning data, the EVG graphs also become extremely scalable. Related entities may be clustered and parallel queries may be executed for additional scalability. 
     Data structures used by the EVG graphs in one example embodiment are described herein. One of ordinary skill in the art will recognize that these are merely examples, and that other data structures may be utilized in some embodiments. 
     URNs may be represented as a sequence of variables including scheme, entity type, partition key, and entity key. For example, the URN “urn:li:media:(urn:li:member:123,456)” may indicate a scheme of “urn:li”, an entity type of “media”, a partition key of “member:123” and an entity key of “456”. 
     Entities may be represented as strongly-typed Java objects having sub-entities and lists. They may contain properties such as URN and type. 
     Edges may be represented as strongly-typed Java objects having various properties, such as URNS, from entity URNs, to entity URNs, edge types, and various attributes. 
     Adjacency lists may contain properties such as from entity URN, edge type, and an ordered list of edges. 
     In an example embodiment, associations can be modeled in two ways: sub-entities and entities+edges. Composition (“part of”) relations, such as where the member has a list of positions he has worked at, may be modeled as sub-entities, while non-composition relations, such as which companies the member has worked for, may be modeled as entities+edges. 
     The following is example code illustrating setting up an ECG client in accordance with an example embodiment. 
     
       
         
           
               
             
               
                   
               
             
            
               
                 // Initialize client 
               
               
                 EVGClient client = _generator.getBean(EvgClientFactory.class); 
               
               
                 // Setup data 
               
               
                 Author author = new Author( ); 
               
               
                 author.setName(“Mark Twain”); 
               
               
                 Book book = new Book( ); 
               
               
                 book.setAuthor(author); 
               
               
                 // Store 
               
               
                 Urn urnPat = new Urn(“urn:li:book:(urn:li:member:123,?)″); 
               
               
                 CreateEntityRequest createRequest = 
               
            
           
           
               
               
            
               
                   
                 CreateEntityRequest.builder( ).setUrn(urnPat).setEntity(book).build( 
               
               
                   
                 ); 
               
            
           
           
               
            
               
                 CreateEntityResponse createResponse = client.execute(createRequest); 
               
               
                 Urn urn = createResponse.getUrn( ); 
               
               
                 // Retrieve 
               
               
                 GetEntityRequest getRequest = GetEntityRequest.builder( 
               
               
                 ).setUrn(urn).build( ); 
               
               
                 GetEntityResponse getResponse = client.execute(getRequest); 
               
               
                 Book outBook = getResponse.getEntity(Book.class); 
               
               
                 System.out.println(“Author is “ + outBook.getAuthor.getName( ));!! 
               
               
                   
               
            
           
         
       
     
       FIG. 4  is a block diagram illustrating an EVG graph  400  in accordance with an example embodiment. The EVG graph  400  contains two member nodes  402 A,  402 B. Member node  402 A corresponds to member “123” while member node  402 B corresponds to member “234”. These nodes are each linked to a position node  404 A,  404 B and an education node  406 A,  406 B. Each position node  404 A,  404 B is linked to a company node  408 A,  408 B and a seniority node  410 A,  410 B. Each education node  406 A,  406 B is linked to a school node  412 A,  412 B. The edges  414 ,  416 ,  418 ,  420 ,  422 ,  424 ,  426 ,  428 ,  430 , and  432  are all named so that they can easily identify to a user what sort of information is stored on the node following the edge. This allows the user to easily specify a query using a query language. For example, the user may write the following in the query language: 
                                from {‘urn:member:123’, ‘urn:member:234’} get entity                         {over memberPosition get entity                         {over positionCompany get entity;           over positionSeniority get entity;}                         over memberEducation get entity over educationSchool get entity;}                        
which indicates to the system that the user wishes to get all the company nodes  408 A,  408 B, seniority nodes  410 A,  410 B, and school nodes  412 A,  412 B.
 
       FIG. 5  is a block diagram illustrating an EVG graph  500  in accordance with another example embodiment. Here, rather than a working history use case such as in  FIG. 4 , the EVG graph  500  represents admission decisions in higher education (e.g., college admissions). A memberboard node  502  may identify a member of an admissions board of the university, and member data may be stored in a first data store  504  having a first data store type, such as Espresso. The URN for the memberboard node  502  may point to the first data store  504 , where entity data  506  is stored. Another URN may point to another data store  508 , where edge data  510  is stored. This additional data store  508  is depicted as another Espresso database, and in some embodiments may be the same data store as the first data store  504 . In other embodiments, this additional data store  508  may be a completely different type than the first data store  504 . 
     Here, the edge data  510  indicates two edges  512 A,  512 B, each to a decision card node  514 A,  514 B defined by entity data  506 . Each decision card node  514 A,  514 B then contains a URN pointing to a second data store  516  having a second data store type, such as Oracle. The second data store  516  then contains entity data  518  indicating comment nodes  520 A,  502 B,  520 C,  520 D. Another URN may point to another data store  522 , where edge data  524  is stored. This additional data store  508  is depicted as another Oracle database, and in some embodiments may be the same data store as the second data store  516 . In other embodiments, this additional data store  522  may be a completely different type than the second data store  516 . 
     Here, edge data  524  indicating edges  526 A,  526 B,  526 C,  526 D, which are edges to comment nodes  520 A,  520 B,  520 C,  520 D. 
     If a user wishes to perform a query, such as “get all decision cards from a member board and get all the comments on the decision cards,” the user can create a query language query as follows: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 from {′urn:memberBoard:(urn:li:member:123,42)’} get urn 
               
            
           
           
               
               
            
               
                   
                 { over decisionCard get entity 
               
            
           
           
               
               
            
               
                   
                 over uscpComments get entity; } 
               
               
                   
                   
               
            
           
         
       
     
     In an example embodiment, a Java-based client may be provided for programmatic access to the EVG graphs. The client utilizes a common builder pattern for constructing requests and responses. It may provide a layer of abstraction above the REST layer and may be capable of producing and consuming objects typed to client-specific domain classes. 
     The client may be used to construct basic requests and responses. The following is sample code for creating an entity in accordance with an example embodiment: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 SampleAuthor author = new SampleAuthor( ); 
               
            
           
           
               
               
            
               
                   
                 Urn urnTemplate = new Urn(“urn:li:author:(memberx:123,?)”); 
               
               
                   
                 CreateEntityRequest request = 
               
               
                   
                 CreateEntityRequest.builder( 
               
               
                   
                 ).setUrn(urnTemplate).setEntity(author).build( ); 
               
               
                   
                 CreateEntityResponse response = _client.execute(request); 
               
               
                   
                   
               
            
           
         
       
     
     The following is sample code for retrieving an entity in accordance with an example embodiment: 
     
       
         
           
               
             
               
                   
               
             
            
               
                 GetEntityRequest request = GetEntityRequest.builder( ).setUrn(new 
               
               
                 Urn(“urn:li:memberx:234”)).build( ); 
               
               
                 GetEntityResponse response = _client.execute(request); 
               
               
                 RecordTemplate entity = response.getEntity( ); 
               
               
                   
               
            
           
         
       
     
     The following is sample code for updating an entity in accordance with an example embodiment: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 SampleMedia media = new SampleMedia( ); 
               
               
                   
                 UpdateEntityRequest request = UpdateEntityRequest.builder( 
               
               
                   
                 ).setUrn(new 
               
               
                   
                 Urn(“urn:li:media:(memberx:123,42)”)).setEntity(media).build( ); 
               
               
                   
                 UpdateEntityResponse response = _client.execute(request); 
               
               
                   
                   
               
            
           
         
       
     
     The following is sample code tier deleting an entity in accordance with an example embodiment: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 DeleteEntityRequest request = 
               
               
                   
                 DeleteEntityRequest.builder( ).setUrn(_mediaUrn1).build( ); 
               
               
                   
                 DeleteEntityResponse response = _client.execute(request); 
               
               
                   
                   
               
            
           
         
       
     
     The following is sample code for adding an edge in accordance with an example embodiment: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 CreateEdgeRequest request = 
               
               
                   
                 CreateEdgeRequest.builder( 
               
               
                   
                 ).setFromUrn(_memberUrn1).setEdgeType(_memberM 
               
               
                   
                 ediaEdgeType 
               
               
                   
                 ).setToUrn(_mediaUrn1).build( ); 
               
               
                   
                 CreateEdgeResponse response = _client.execute(request); 
               
               
                   
                   
               
            
           
         
       
     
     The following is sample code for deleting an edge in accordance with an example embodiment: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 DeleteEdgeRequest request = 
               
               
                   
                 DeleteEdgeRequest.builder( 
               
               
                   
                 ).setFromUrn(_memberUrn1).setEdgeType(_memberM 
               
               
                   
                 ediaEdgeType 
               
               
                   
                 ).setToUrn(_mediaUrn1).build( ); 
               
               
                   
                 DeleteEdgeResponse response = _client.execute(request); 
               
               
                   
                   
               
            
           
         
       
     
     The following is sample code for querying in accordance with an example embodiment: 
     
       
         
           
               
             
               
                   
               
             
            
               
                 final String query = “from {‘urn:li:memberx:123’, ‘urn:li:memberx:234’} 
               
               
                 ” + 
               
               
                 “get entity {over memberPosition get entity; over 
               
               
                 memberEducation get entity;}”; 
               
               
                 QueryRequest request = QueryRequest.builder( ).setQuery(_query).build( 
               
               
                 ); 
               
               
                 QueryResponse response = _client.execute(request); 
               
               
                 DomainGraph graph = response.getDomainGraph( ); 
               
               
                   
               
            
           
         
       
     
     In an example embodiment, the system may support metadata and index metadata for entities and edges. Metadata may be used to define each entity and edge type for a particular use case, and index metadata may be used to access entity data through a data source&#39;s secondary index. 
     In an example embodiment, a number of different attributes are available for a user to create metadata for a new entity or edge, including entityType, urnResolver, urnResolverConfig, edge, rowPerEdge, edgeMultiTenant, and reducedEdge. 
     The entityType attribute supports entities and edges and specifies the name of the entity or edge. 
     The urnResolver attribute specifies the data store. 
     The urnResolverConfig attribute is a map with attributes specific to the resolver (data store). The map may include database and table information for the entity, and the URN pattern which will specify the URN to database translation. 
     The edge attribute specifies whether the entity type is an entity or an edge. 
     The rowPerEdge attribute indicates whether each edge is stored in one separate row or several edges can be aggregated into one row. 
     The edgeMultiTenant attribute specifies whether multiple edge types can be stored in the table. 
     The reducedEdge attribute specifies whether the edge can be stored in a reduced format. 
     Referring back to the example in  FIG. 1  having a member entity  102  with an edge  106  to an entity for treasuryMedia  104 , various metadata for each of these elements may be provided. For example, the following is sample metadata for the entity treasuryMedia  104  in accordance with an example embodiment: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 //Metadata if the entity treasuryMedia is stored in Oracle 
               
               
                   
                 { 
               
               
                   
                 “urnResolver”:“oracle”, 
               
               
                   
                 “entityType”:“treasuryMedia”, 
               
               
                   
                 “urnResolverConfig”: 
               
               
                   
                 { 
               
               
                   
                 “com.linkedin.evg.internal.OracleUrnResolverConfig”: 
               
               
                   
                 { 
               
               
                   
                 “table”:“TREASURY_MEDIA”, 
               
               
                   
                 “dbUri”:“jdbc:oracle:thin:evg/evg@//devdb:1521/DB” 
               
               
                   
                 } 
               
               
                   
                 }, 
               
               
                   
                 “edge”:false 
               
               
                   
                 } 
               
               
                   
                 //Metadata if the entity treasuryMedia is stored in Espresso 
               
               
                   
                 { 
               
               
                   
                 “urnResolver”:“espresso”, 
               
               
                   
                 “entityType”:“treasuryMedia”, 
               
               
                   
                 “urnResolverConfig”: 
               
               
                   
                 { 
               
               
                   
                 “com.linkedin.evg.internal.EspressoUrnResolverConfig”: 
               
               
                   
                 { 
               
               
                   
                 “table”:“TreasuryMedia”, 
               
               
                   
                 “database”:“evg”, 
               
               
                   
                 “urnPatternRead”:“urn:li:treasuryMedia:(urn:li:member:$0,$1)”, 
               
               
                   
                 “espressoCluster”: “http://esv4-be51.corp.linkedin.com:12921” 
               
               
                   
                 } 
               
               
                   
                 }, 
               
               
                   
                 “edge”:false 
               
               
                   
                 } 
               
               
                   
                   
               
            
           
         
       
     
     The following is sample metadata for the edge member2Media  106  in accordance with an example embodiment: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 //Metadata if the edge member2Media is stored in Oracle 
               
               
                   
                 { 
               
               
                   
                 “entityType”:“member2Media”, 
               
               
                   
                 “urnResolver”:“oracle”, 
               
               
                   
                 “urnResolverConfig”: 
               
               
                   
                 { 
               
               
                   
                 “com.linkedin.evg.internal.OracleUrnResolverConfig”: 
               
               
                   
                 “ 
               
               
                   
                 “dbUri”:“jdbc:oracle:thin:evg/evg@//devdb:1521/DB” 
               
               
                   
                 “table”: “TreasuryAdjacencyList”, 
               
               
                   
                 “urnPatternRead”: “urn:li:member2Media:(urn:li:member:$0,$1)”, 
               
               
                   
                 “database”: “evg” 
               
               
                   
                 } 
               
               
                   
                 }, 
               
               
                   
                 “edge”:true, 
               
               
                   
                 “rowPerEdge”: false 
               
               
                   
                 } 
               
               
                   
                 //Metadata if the edge member2Media is stored in Espresso 
               
               
                   
                 { 
               
               
                   
                 “entityType”:“member2Media”, 
               
               
                   
                 “urnResolver”:“espresso”, 
               
               
                   
                 “urnResolverConfig”: 
               
               
                   
                 { 
               
               
                   
                 “com.linkedin.evg.internal.EspressoUrnResolverConfig”: 
               
               
                   
                 { 
               
               
                   
                 “espressoCluster”: “http://esv4-be51.corp.linkedin.com:12921”, 
               
               
                   
                 “table”: “TreasuryAdjacencyList”, 
               
               
                   
                 “urnPatternRead”: “urn:li:member2Media:(urn:li:member:$0,$1)”, 
               
               
                   
                 “database”: “evg” 
               
               
                   
                 } 
               
               
                   
                 }, 
               
               
                   
                 “edge”:true, 
               
               
                   
                 “rowPerEdge”: false 
               
               
                   
                 } 
               
               
                   
                   
               
            
           
         
       
     
     In an example embodiment, a number of different attributes are available for a user to create index metadata for a new entity or edge, including indexName, urnResolver, urnResolverConfig, edge, toIndexField, indexFields, and supportedEdges. 
     The indexName attribute specifies the name of the entity or edge. 
     The urnResolver attribute defines the data store. 
     The urnResolverConfig attribute is a map with attributes specific to the resolver (data store). The map includes database and table information for the entity and the URN pattern which specifies the URN to database translation. 
     The edge attribute specifies whether the entity type is an entity or an edge. 
     The toIndexField attribute is used if the entity is an edge and specifies a full valid URN. The system then retrieves and returns the data defined in this URN. 
     The supportedEdges attribute specifies the edges in an EVG graph query supported by the index. 
     In an example embodiment, entities are stored in a table per per-domain object. In an alternative embodiment, a completely opaque binary envelope is used. In the table per per-domain object case, this means that users create a table for their objects. In order to allow the data to be partitioned, all keys, for both entities and edges, begin with a partition key. In an example embodiment, this may be a member identification. Consequently, since the URN needs to carry enough information to fill in the parameters of the request to perform any of the operations on the underlying data store, it also needs to have the identification of the domain specific object along the way. 
     Table 1 depicts example URNs in accordance with an example embodiment: 
     
       
         
           
               
               
               
             
               
                 TABLE 1 
               
               
                   
               
               
                 Entity 
                 URN 
                 Notes 
               
               
                   
               
             
            
               
                 members&#39;s 
                 urn:li:member:1 
                   
               
               
                 profile 
               
               
                 position #123 
                 urn:li:position:(urn:li:member:1,123) 
                 Although position is an integral part of a 
               
               
                   
                   
                 profile, it can also be served up as an entity 
               
               
                   
                   
                 of its own, while acting as a sub-entity of a 
               
               
                   
                   
                 member&#39;s profile 
               
               
                 member 
                 urn:li:profileSection:(urn:li:member: 
                 An object with this address does not exist 
               
               
                 profile&#39;s 
                 1,RECOMMENDATIONS) 
                 nor is ever materialized outside of a 
               
               
                 section 
                   
                 members profile; this effectively refers to 
               
               
                   
                   
                 an area on the screen where corresponding 
               
               
                   
                   
                 data is rendered. 
               
               
                 treasury 
                 urn:li:treasuryMedia:(urn:li:member: 
               
               
                 media #456 
                 1,456) 
               
               
                   
               
            
           
         
       
     
     The results of using an EVG graph is that data from multiple data sources may be abstracted and queries for data from these multiple data sources can be sent to a single destination: the EVG system. The EVG system maintains the edges for the data in these multiple data sources. Each entity itself may be unaware that another entity exists, even if an edge is present between the two entities, because the EVG system maintains the edges separately from the entities. 
     The EVG system is also able to retrieve all pieces of data in parallel, despite the fact that they may be disparate pieces of data in disparate data sources, as opposed to prior art techniques where the system retrieves at least some data in series, necessitating a waiting period until the final piece of data is retrieved, prior to loading. Additionally, the EVG system is also intelligent enough such that if one of the disparate pieces of data being retrieved has an edge to another piece of data (e.g., a sub-entity), it can immediately retrieve that other piece of data. Thus, for example, if there are two entities, labeled media 1  and media 2 , each having an edge to sub-entities, labeled group 1  and group 2 , the system, upon retrieving media 1 , can immediately begin retrieving group 1 , without waiting for media 2  to be completely retrieved. Thus, the EVG system is designed to accept queries that specify edges, rather than goal entities, to retrieve. The EVG system then uses these specified edges to return “whatever” entities reside on the other ends of these edges. 
       FIG. 6  is a block diagram illustrating an EVG system  600  in accordance with an example embodiment. A query (written in a query language) is received at a query parser  602 , which generates an abstract syntax tree (AST) representation of the query. This is then passed to a query engine  604 . The query engine  604  may then start an assembly task  606 , an entity request task  608 , an edge request task  610 , an entity result task  612 , and an edge result task  614 . The entity result task  612  may require that the entity request task  608  complete before launching, and the edge result task  614  may require that the entity result task  612  complete before launching. However, the entity result task  612  and the edge result task  614  may each launch additional tasks dynamically as needed. For example, if one of these tasks  612 ,  614  determine that there is, in fact, an additional group element under the currently retrieved element, it may launch an additional entity request task to retrieve this additional group element. Each request task  608 - 610  may contain a pointer to where it is located in the AST in order to make this possible. 
     A result context  616  gathers URNs generated by the tasks  608 - 610  and retrieves corresponding data from the data sources for these URNs. This helps eliminate duplicate requests. For example, if two different entities are linked to the same media file, the media file, while referenced by two different tasks, will only be retrieved once as the result context  616  is intelligent enough to recognize duplicate URNs and only retrieve one piece of data. 
     The assembly task  606  then forms the response to the query based on the data from the result context  616 . 
     Notably, the request tasks  608 - 610  look up in the resolver  618  to determine how to actually retrieve the corresponding data. The resolver  618  provides this information based on the metadata, allowing the request tasks  608  to schedule actual data retrieval calls via URNs. Communication flows  620  and  622  indicate how the edgeResult task  614  can actually cause a loop or cycle by then initiating calls to entityRequest  608  and/or edgeRequest  610 . 
       FIG. 7  is a block diagram illustrating a task chain  700  in accordance with an example embodiment. The task chain  700  includes an entity get  702 , which then uses an xfetcher task  704  which, when the result comes back, gets turned into xnormialize  706 , which then results entitydone  708 . The xfetcher task  704  and the xnomalize  706  task may be collectively known as a resolver  710 , which may be plug-and-play, meaning that the resolver  710  for one type of data source can be switched out with the resolver  710 . The task chain  700  may be defined by metadata. Additionally, the resolver  710  can be designed as a dual fetcher, performing similar tasks on different data sources simultaneously, which makes it easier for users to migrate data from one data source to another. 
       FIG. 8  is a sequence diagram illustrating a method  800  in accordance with an example embodiment. The method  800  involves a number of different entities, including a user  802 , front-end  804 , middle tier  806 , EVG engine  808 , AST query engine  810 , Assembler  812 , Metadata source  814 , 1st data source  816 , and 2nd data source  818 . At operation  820 , the user (through, for example, a browser) may send an HTTP request to the front-end  804 . At operation  822 , the front-end  804  sends a request to the middle tier  806 . At operation  824 , the middle tier  806  sends a query via REST to the EVG engine  808 . At operation  826 , the EVG engine  808  sends a query to the AST query engine  810 . 
     At operation  828 , the AST query engine  810  sends an AST message for content to the assembler  812 . At operation  830 , the assembler  812  sends a get request to the metadata source  814 , which returns the metadata at operation  832 . At operation  834 , the assembler  812  then creates the tasks. At operation  836 , the assembler  812  sends a get request to the 1st data source  816 , which returns content at operation  838 . At operation  840 , the assembler  812  populates the content in a data structure. At operation  842 , the assembler  812  sends a get request to the 2nd data source  818 , which returns content at operation  844 . At operation  846  the assembler  812  populates the content in a data structure. 
     At operation  848 , the assembler  812  sends the content to the EVG engine  808 , which at operation  850  forms a response from the content. This response is sent to the middle tier  806  at operation  852 . The middle tier  806  then returns a model to the front-end  804  at operation  854 . The front-end then returns an HTML page at  856  based on the model. 
       FIG. 9  is a flow diagram illustrating a method  900  in accordance with an example embodiment. At operation  902 , structure of a resultant Every Document as a Graph (EVG) graph may be outlined using an EVG query. At operation  904 , first metadata for a first data source may be retrieved. At operation  906 , at least one entity key for a first entity is determined, wherein the entity key comes directly from the EVG query or from an entity on a preceding level of the EVG graph. Then, at operation  908 , based on the first metadata and entity key, an edge may be created in the EVG graph beginning at the first entity, wherein the edge contains information retrieved from the first data source. At operation  910 , second metadata for a second data source is retrieved, the second data source being of a different data source type than the first data source such that accessing data from the first data source is performed differently than accessing data from the second data source. Then, based on the second metadata and information contained in the edge retrieved from first data source, a second entity may be created in the EVG graph, wherein the edge connects to the second entity, wherein the second entity contains information retrieved from the second data source. 
       FIG. 10  is a diagrammatic representation of a machine in the example form of a computer system  1000  within which a set of instructions  1024 , for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine operates as a stand-alone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions  1024  (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions  1024  to perform any one or more of the methodologies discussed herein. 
     The example computer system  1000  includes a processor  1002  (e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), a main memory  1004  and a static memory  1006 , which communicate with each other via a bus  1008 . The computer system  1000  may further include a video display unit  1010  (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system  1000  also includes an alphanumeric input device  1012  (e.g., a keyboard), a user interface (UI) navigation device  1014  (e.g., a cursor control device), a storage device  1016 , a signal generation device  1018  (e.g., a speaker and a network interface device  1020 . 
     The storage device  1016  includes a machine-readable medium  1022  on which is stored one or more sets of instructions and data structures (e.g., instructions  1024 ) embodying or utilized by any one or more of the methodologies or functions described herein. The instructions  1024  may also reside, completely or at least partially, within the main memory  1004  and/or within the processor  1002  during execution thereof by the computer system  1000 , with the main memory  1004  and the processor  1002  also constituting machine-readable media  1022 . 
     The instructions  1024  may further be transmitted or received over a network  1026  via the network interface device  1020  utilizing any one of a number of well-known transfer protocols (e.g., Hyper Text Transfer Protocol (HTTP)). 
     While the machine-readable medium  1022  is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions e.g.,  1024 . The term “machine-readable medium” shall also be taken to include any medium that is capable of storing and encoding a set of instructions e.g.,  1024  for execution by the machine and that cause the machine to perform any one or more of the methodologies of embodiments of the present disclosure, or that is capable of storing and encoding data structures utilized by or associated with such a set of instructions e.g.,  1024 . The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical and magnetic media. Such media may, without limitation, also include hard disks, floppy disks, flash memory cards, digital video disks, random access memory (RAMs), read only memory (ROMs), and the like. 
     The embodiments described herein may be implemented in an operating environment comprising software installed on a computer, in hardware, or in a combination of software and hardware. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “disclosure” merely for convenience and without intending to voluntarily limit the scope of this application to any single embodiment if more than one is, in fact, disclosed. 
     Modules, Components and Logic 
     Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied (1) on a non-transitory machine-readable medium  1022  or (2) in a transmission signal) or hardware-implemented modules. A hardware-implemented module is a tangible unit capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more processors may be configured by software (e.g., an application or application portion) as a hardware-implemented module that operates to perform certain operations as described herein. 
     In various embodiments, a hardware-implemented module may be implemented mechanically or electronically. For example, a hardware-implemented module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC)) to perform certain operations. A hardware-implemented module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware-implemented module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. 
     Accordingly, the term “hardware-implemented module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily or transitorily configured (e.g., programmed) to operate in a certain manner and/or to perform certain operations described herein. Considering embodiments in which hardware-implemented modules are temporarily configured (e.g., programmed), each of the hardware-implemented modules need not be configured or instantiated at any one instance in time. For example, where the hardware-implemented modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware-implemented modules at different times. Software may, accordingly, configure a processor, for example, to constitute a particular hardware-implemented module at one instance of time and to constitute a different hardware-implemented module at a different instance of time. 
     Hardware-implemented modules can provide information to, and receive information from, other hardware-implemented modules. Accordingly, the described hardware-implemented modules may be regarded as being communicatively coupled. Where multiple of such hardware-implemented modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses that connect the hardware-implemented modules.) In embodiments in which multiple hardware-implemented modules are configured or instantiated at different times, communications between such hardware-implemented modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware-implemented modules have access. For example, one hardware-implemented module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware-implemented module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware-implemented modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information). 
     The various operations of example methods described herein may be performed, at least partially, by one or more processors  1002  that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors  1002  may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules. 
     Similarly, the methods described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or more processors  1002  or processor-implemented modules. The performance of certain of the operations may be distributed among the one or more processors  1002 , not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors  1002  may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors  1002  may be distributed across a number of locations. 
     The one or more processors  1002  may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors  1002 ), these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., application program interfaces (APIs).) 
     Although embodiments have been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the inventive subject matter. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.