def test_error_on_parameters_not_correct(arrow_project_graph): # Incorrect type of parameters with pytest.raises(ValueError, match="could not convert string to float"): pagerank(arrow_project_graph, "delta=0.85", 10) with pytest.raises(ValueError, match=r"invalid literal for int\(\) with base 10"): pagerank(arrow_project_graph, 0.85, "max_round=10") with pytest.raises( TypeError, match="takes from 1 to 3 positional arguments but 6 were given"): pagerank(arrow_project_graph, 0.85, 10, 100, 1000, 10000)
def test_add_column_string_oid(p2p_property_graph_string, p2p_project_directed_graph_string): g1 = p2p_property_graph_string g2 = p2p_project_directed_graph_string property_names = [ p.name for p in g1.schema.get_vertex_properties("person") ] assert "pagerank" not in property_names ctx = graphscope.pagerank(g2) g3 = g1.add_column(ctx, selector={"pagerank": "r"}) property_names = [ p.name for p in g3.schema.get_vertex_properties("person") ] assert "pagerank" in property_names
def test_demo_distribute(gs_session_distributed, data_dir, modern_graph_data_dir): graph = load_ldbc(gs_session_distributed, data_dir) # Interactive engine interactive = gs_session_distributed.gremlin(graph) sub_graph = interactive.subgraph( # noqa: F841 'g.V().hasLabel("person").outE("knows")') person_count = (interactive.execute( 'g.V().hasLabel("person").outE("knows").bothV().dedup().count()').all( ).result()[0]) knows_count = (interactive.execute( 'g.V().hasLabel("person").outE("knows").count()').all().result()[0]) interactive2 = gs_session_distributed.gremlin(sub_graph) sub_person_count = interactive2.execute("g.V().count()").all().result()[0] sub_knows_count = interactive2.execute("g.E().count()").all().result()[0] assert person_count == sub_person_count assert knows_count == sub_knows_count # Analytical engine # project the projected graph to simple graph. simple_g = sub_graph.project_to_simple(v_label="person", e_label="knows") pr_result = graphscope.pagerank(simple_g, delta=0.8) tc_result = graphscope.triangles(simple_g) # add the PageRank and triangle-counting results as new columns to the property graph # FIXME: Add column to sub_graph sub_graph.add_column(pr_result, {"Ranking": "r"}) sub_graph.add_column(tc_result, {"TC": "r"}) # test subgraph on modern graph mgraph = load_modern_graph(gs_session_distributed, modern_graph_data_dir) # Interactive engine minteractive = gs_session_distributed.gremlin(mgraph) msub_graph = minteractive.subgraph( # noqa: F841 'g.V().hasLabel("person").outE("knows")') person_count = (minteractive.execute( 'g.V().hasLabel("person").outE("knows").bothV().dedup().count()').all( ).result()[0]) msub_interactive = gs_session_distributed.gremlin(msub_graph) sub_person_count = msub_interactive.execute( "g.V().count()").all().result()[0] assert person_count == sub_person_count
def test_demo(gs_session, data_dir): graph = load_ldbc(gs_session, data_dir) # Interactive engine interactive = gs_session.gremlin(graph) sub_graph = interactive.subgraph( # noqa: F841 'g.V().hasLabel("person").outE("knows")') # Analytical engine # project the projected graph to simple graph. simple_g = sub_graph.project_to_simple(v_label="person", e_label="knows") pr_result = graphscope.pagerank(simple_g, delta=0.8) tc_result = graphscope.triangles(simple_g) # add the PageRank and triangle-counting results as new columns to the property graph # FIXME: Add column to sub_graph sub_graph.add_column(pr_result, {"Ranking": "r"}) sub_graph.add_column(tc_result, {"TC": "r"})
def test_demo(data_dir): gs_image, gie_manager_image = get_gs_image_on_ci_env() sess = graphscope.session( num_workers=1, k8s_gs_image=gs_image, k8s_gie_graph_manager_image=gie_manager_image, k8s_coordinator_cpu=0.5, k8s_coordinator_mem="2500Mi", k8s_vineyard_cpu=0.1, k8s_vineyard_mem="512Mi", k8s_engine_cpu=0.1, k8s_engine_mem="1500Mi", k8s_etcd_cpu=2, k8s_vineyard_shared_mem="2Gi", k8s_volumes=get_k8s_volumes(), ) graph = load_ldbc(sess, data_dir) # Interactive engine interactive = sess.gremlin(graph) sub_graph = interactive.subgraph( # noqa: F841 'g.V().hasLabel("person").outE("knows")' ) # Analytical engine # project the projected graph to simple graph. simple_g = sub_graph.project_to_simple(v_label="person", e_label="knows") pr_result = graphscope.pagerank(simple_g, delta=0.8) tc_result = graphscope.triangles(simple_g) # add the PageRank and triangle-counting results as new columns to the property graph # FIXME: Add column to sub_graph sub_graph.add_column(pr_result, {"Ranking": "r"}) sub_graph.add_column(tc_result, {"TC": "r"}) # GNN engine sess.close()
def test_run_app_on_directed_graph( p2p_project_directed_graph, sssp_result, pagerank_result, hits_result, bfs_result, clustering_result, dc_result, ev_result, katz_result, ): # sssp ctx1 = sssp(p2p_project_directed_graph, src=6) r1 = (ctx1.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) r1[r1 == 1.7976931348623157e308] = float( "inf") # replace limit::max with inf assert np.allclose(r1, sssp_result["directed"]) ctx2 = sssp(p2p_project_directed_graph, 6) r2 = (ctx2.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) r2[r2 == 1.7976931348623157e308] = float( "inf") # replace limit::max with inf assert np.allclose(r2, sssp_result["directed"]) assert np.allclose( ctx2.to_dataframe({ "node": "v.id", "r": "r" }, vertex_range={ "begin": 1, "end": 4 }).sort_values(by=["node"]).to_numpy(), [[1.0, 260.0], [2.0, 229.0], [3.0, 310.0]], ) assert np.allclose( sorted(ctx1.to_numpy("r", vertex_range={ "begin": 1, "end": 4 })), sorted([260.0, 229.0, 310.0]), ) r3 = sssp(p2p_project_directed_graph, 100000000) assert r3 is not None # pagerank ctx_pr = pagerank(p2p_project_directed_graph, delta=0.85, max_round=10) ret_pr = (ctx_pr.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(ret_pr, pagerank_result["directed"]) # hits ctx_hits = hits(p2p_project_directed_graph, tolerance=0.001) ret_hub = (ctx_hits.to_dataframe({ "node": "v.id", "hub": "r.hub" }).sort_values(by=["node"]).to_numpy(dtype=float)) ret_auth = (ctx_hits.to_dataframe({ "node": "v.id", "auth": "r.auth" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(ret_hub, hits_result["hub"]) assert np.allclose(ret_auth, hits_result["auth"]) # bfs ctx4 = bfs(p2p_project_directed_graph, src=6) r4 = (ctx4.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=int)) assert np.all(r4 == bfs_result["directed"]) ctx5 = bfs(p2p_project_directed_graph, 6) r5 = (ctx5.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=int)) assert np.all(r5 == bfs_result["directed"]) assert np.all( ctx5.to_dataframe( { "node": "v.id", "r": "r" }, vertex_range={ "begin": 1, "end": 4 }).sort_values(by=["node"]).to_numpy() == [[1, 5], [2, 5], [3, 6]]) assert np.all( sorted(ctx5.to_numpy("r", vertex_range={ "begin": 1, "end": 4 })) == [5, 5, 6]) # simple_path assert is_simple_path(p2p_project_directed_graph, [1, 10]) with pytest.raises(InvalidArgumentError, match="Louvain not support directed graph."): louvain(p2p_project_directed_graph) # clustering ctx_clustering = clustering(p2p_project_directed_graph) ret_clustering = (ctx_clustering.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(ret_clustering, clustering_result["directed"]) # degree_centrality ctx_dc = degree_centrality(p2p_project_directed_graph) ret_dc = (ctx_dc.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(ret_dc, dc_result["directed"]) # eigenvector_centrality ctx_ev = eigenvector_centrality(p2p_project_directed_graph) ret_ev = (ctx_ev.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(ret_ev, ev_result["directed"]) # katz_centrality ctx_katz = katz_centrality(p2p_project_directed_graph)
def test_app_on_undirected_graph( p2p_project_undirected_graph, sssp_result, pagerank_result, bfs_result, wcc_result, lpa_result, triangles_result, kshell_result, ): # sssp ctx1 = sssp(p2p_project_undirected_graph, src=6) r1 = (ctx1.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) r1[r1 == 1.7976931348623157e308] = float( "inf") # replace limit<double>::max with inf assert np.allclose(r1, sssp_result["undirected"]) assert np.allclose( ctx1.to_dataframe({ "node": "v.id", "r": "r" }, vertex_range={ "begin": 1, "end": 4 }).sort_values(by=["node"]).to_numpy(), [[1.0, 31.0], [2.0, 39.0], [3.0, 78.0]], ) assert np.allclose( sorted(ctx1.to_numpy("r", vertex_range={ "begin": 1, "end": 4 })), [31.0, 39.0, 78.0], ) # pagerank (only work on undirected graph) ctx2 = pagerank(p2p_project_undirected_graph, delta=0.85, max_round=10) r2 = (ctx2.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(r2, pagerank_result["undirected"]) ctx3 = pagerank(p2p_project_undirected_graph, 0.85, 10) r3 = (ctx3.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(r3, pagerank_result["undirected"]) # r4 = pagerank(arrow_project_graph, 10, 0.85) # check max_round=10 # assert r4 is not None ctx5 = pagerank(p2p_project_undirected_graph, "0.85", "10") r5 = (ctx5.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(r5, pagerank_result["undirected"]) ctx6 = pagerank(p2p_project_undirected_graph) r6 = (ctx6.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(r6, pagerank_result["undirected"]) assert np.allclose( ctx6.to_dataframe({ "node": "v.id", "r": "r" }, vertex_range={ "begin": 1, "end": 4 }).sort_values(by=["node"]).to_numpy(), [ [1.0, 6.153724343761569e-05], [2.0, 9.280361872165397e-05], [3.0, 1.643246086005906e-05], ], ) assert np.allclose( sorted(ctx6.to_numpy("r", vertex_range={ "begin": 1, "end": 4 })), sorted([ 6.153724343761569e-05, 9.280361872165397e-05, 1.643246086005906e-05 ]), ) # bfs ctx7 = bfs(p2p_project_undirected_graph, src=6) r7 = (ctx7.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=int)) assert np.all(r7 == bfs_result["undirected"]) assert np.all( ctx7.to_dataframe( { "node": "v.id", "r": "r" }, vertex_range={ "begin": 1, "end": 4 }).sort_values(by=["node"]).to_numpy() == [[1, 1], [2, 2], [3, 2]]) assert np.all( sorted(ctx7.to_numpy("r", vertex_range={ "begin": 1, "end": 4 })) == [1, 2, 2]) # wcc ctx8 = wcc(p2p_project_undirected_graph) r8 = (ctx8.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=int)) assert np.all(r8 == wcc_result) assert np.all( ctx8.to_dataframe( { "node": "v.id", "r": "r" }, vertex_range={ "begin": 1, "end": 4 }).sort_values(by=["node"]).to_numpy() == [[1, 1], [2, 1], [3, 1]]) assert np.all( ctx8.to_numpy("r", vertex_range={ "begin": 1, "end": 4 }) == [1, 1, 1]) # lpa ctx9 = lpa(p2p_project_undirected_graph, max_round=10) r9 = (ctx9.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=int)) assert np.all(r9 == lpa_result) assert np.all( ctx9.to_dataframe( { "node": "v.id", "r": "r" }, vertex_range={ "begin": 1, "end": 4 }).sort_values(by=["node"]).to_numpy() == [[1, 1], [2, 2], [3, 2]]) assert np.all( sorted(ctx9.to_numpy("r", vertex_range={ "begin": 1, "end": 4 })) == [1, 2, 2]) # kshell ctx10 = k_shell(p2p_project_undirected_graph, k=3) r10 = (ctx10.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=int)) assert np.all(r10 == kshell_result) assert np.all( ctx10.to_dataframe( { "node": "v.id", "r": "r" }, vertex_range={ "begin": 1, "end": 4 }).sort_values(by=["node"]).to_numpy() == [[1, 0], [2, 0], [3, 0]]) assert np.all( ctx10.to_numpy("r", vertex_range={ "begin": 1, "end": 4 }) == [0, 0, 0]) # triangles ctx_triangles = triangles(p2p_project_undirected_graph) ret_triangles = (ctx_triangles.to_dataframe({ "node": "v.id", "r": "r" }).sort_values(by=["node"]).to_numpy(dtype=float)) assert np.allclose(ret_triangles, triangles_result["undirected"]) # louvain ctx10 = louvain(p2p_project_undirected_graph, min_progress=50, progress_tries=2) # simple_path assert is_simple_path(p2p_project_undirected_graph, [1, 10])
def test_demo_distribute(data_dir, modern_graph_data_dir): gs_image, gie_manager_image = get_gs_image_on_ci_env() sess = graphscope.session( num_workers=1, k8s_gs_image=gs_image, k8s_gie_graph_manager_image=gie_manager_image, k8s_coordinator_cpu=0.5, k8s_coordinator_mem="2500Mi", k8s_vineyard_cpu=0.1, k8s_vineyard_mem="512Mi", k8s_engine_cpu=0.1, k8s_engine_mem="1500Mi", k8s_vineyard_shared_mem="2Gi", k8s_volumes=get_k8s_volumes(), ) graph = load_ldbc(sess, data_dir) # Interactive engine interactive = sess.gremlin(graph) sub_graph = interactive.subgraph( # noqa: F841 'g.V().hasLabel("person").outE("knows")') person_count = (interactive.execute( 'g.V().hasLabel("person").outE("knows").bothV().dedup().count()').all( ).result()[0]) knows_count = (interactive.execute( 'g.V().hasLabel("person").outE("knows").count()').all().result()[0]) interactive2 = sess.gremlin(sub_graph) sub_person_count = interactive2.execute("g.V().count()").all().result()[0] sub_knows_count = interactive2.execute("g.E().count()").all().result()[0] assert person_count == sub_person_count assert knows_count == sub_knows_count # Analytical engine # project the projected graph to simple graph. simple_g = sub_graph.project_to_simple(v_label="person", e_label="knows") pr_result = graphscope.pagerank(simple_g, delta=0.8) tc_result = graphscope.triangles(simple_g) # add the PageRank and triangle-counting results as new columns to the property graph # FIXME: Add column to sub_graph sub_graph.add_column(pr_result, {"Ranking": "r"}) sub_graph.add_column(tc_result, {"TC": "r"}) # test subgraph on modern graph mgraph = load_modern_graph(sess, modern_graph_data_dir) # Interactive engine minteractive = sess.gremlin(mgraph) msub_graph = minteractive.subgraph( # noqa: F841 'g.V().hasLabel("person").outE("knows")') person_count = (minteractive.execute( 'g.V().hasLabel("person").outE("knows").bothV().dedup().count()').all( ).result()[0]) msub_interactive = sess.gremlin(msub_graph) sub_person_count = msub_interactive.execute( "g.V().count()").all().result()[0] assert person_count == sub_person_count # GNN engine sess.close()