A graph projection is an in-memory graph containing all or part of the data loaded from a graphset. Ultipa graph algorithms run on graph projections for peak efficiency.

Based on the Shards + HDCs architecture of Ultipa Powerhouse (v5), graph data can be projected to either an HDC server or shard servers, resulting in HDC or distributed projections.

Selecting between a HDC or distributed projection involves factors such as physical infrastructure, data volume, and specific business needs. The table below highlights key distinctions between them:

HDC Projections

To project the entire current graphset to hdc-server-1 as hdcGraph:

hdc.graph.create("hdcGraph", {
  nodes: {"*": ["*"]},
  edges: {"*": ["*"]},
  direction: "undirected",
  load_id: true,
  update: "static",
  query: "query",
  default: true
}).to("hdc-server-1")

To project @account and @movie nodes with selected properties and incoming @rate edges in the current graphset to hdc-server-1 as hdcGraph_1, while omitting nodes' _id values:

hdc.graph.create("hdcGraph_1", {
  nodes: {
    "account": ["name", "gender"],
    "movie": ["name", "year"]
  },
  edges: {"*": ["*"]},
  direction: "in",
  load_id: false,
  update: "static",
  query: "query",
  default: false
}).to("hdc-server-1")

For details on managing HDC projections, see HDC Projections.

Distributed Projections

To project the entire current graphset to its shard servers as distGraph:

create().project("distGraph", ["*"], ["*"], {
  node_properties: ["*"], 
  edge_properties: ["*"],
  orientation: "undirected",
  load_id: true
})

To project @account and @movie nodes with selected properties and incoming @rate edges in the current graphset to its shard servers as distGraph_1, while omitting nodes' _id values:

create().project("distGraph_1", ["account", "movie"], ["rate"], {
  node_properties: ["name", "year", "gender"], 
  edge_properties: ["*"],
  orientation: "in",
  load_id: false
})

For details on managing distributed projections, see Distributed Projections.