Added benchmark datasets yaml files for use with Dataset

python/cugraph/cugraph/datasets/__init__.py

@@ -38,3 +38,8 @@
 small_tree = Dataset(meta_path / "small_tree.yaml")
 toy_graph = Dataset(meta_path / "toy_graph.yaml")
 toy_graph_undirected = Dataset(meta_path / "toy_graph_undirected.yaml")
+# soc_livejournal = Dataset(meta_path / "soc-livejournal1.yaml") # 250MB
+# cit_patents = Dataset(meta_path / "cit-patents.yaml") # 965MB
+# europe_osm = Dataset(meta_path / "europe_osm.yaml") # 1.8GB
+# hollywood = Dataset(meta_path / "hollywood.yaml") # 1.5GB
+# twitter = Dataset(meta_path / "soc-twitter-2010.yaml") # 8.8GB

python/cugraph/cugraph/datasets/metadata/cit-patents.yaml

@@ -0,0 +1,22 @@
+name: cit-Patents
+file_type: .csv
+description: A citation graph that includes all citations made by patents granted between 1975 and 1999, totaling 16,522,438 citations.
+author: NBER
+refs:
+ J. Leskovec, J. Kleinberg and C. Faloutsos. Graphs over Time Densification Laws, Shrinking Diameters and Possible Explanations. 
+ ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2005.
+delim: " "
+header: None
+col_names:
+ - src
+ - dst
+col_types:
+ - int32
+ - int32
+has_loop: true
+is_directed: true
+is_multigraph: false
+is_symmetric: false
+number_of_edges: 16518948
+number_of_nodes: 3774768
+url: https://data.rapids.ai/cugraph/datasets/cit-Patents.csv

python/cugraph/cugraph/datasets/metadata/europe_osm.yaml

@@ -0,0 +1,21 @@
+name: europe_osm
+file_type: .csv
+description: A graph of OpenStreetMap data for Europe.
+author: M. Kobitzsh / Geofabrik GmbH
+refs:
+ Rossi, Ryan. Ahmed, Nesreen. The Network Data Respoistory with Interactive Graph Analytics and Visualization.
+delim: " "
+header: None
+col_names:
+ - src
+ - dst
+col_types:
+ - int32
+ - int32
+has_loop: false
+is_directed: false
+is_multigraph: false
+is_symmetric: true
+number_of_edges: 54054660
+number_of_nodes: 50912018
+url: https://data.rapids.ai/cugraph/datasets/europe_osm.csv

python/cugraph/cugraph/datasets/metadata/hollywood.yaml

@@ -0,0 +1,25 @@
+name: hollywood
+file_type: .csv
+description:
+ A graph of movie actors where vertices are actors, and two actors are joined by an edge whenever they appeared in a movie together.
+author: Laboratory for Web Algorithmics (LAW)
+refs:
+ "The WebGraph Framework I: Compression Techniques," Paolo Boldi 
+ and Sebastiano Vigna, Proc. of the Thirteenth International 
+ World Wide Web Conference (WWW 2004), 2004, Manhattan, USA, 
+ pp. 595--601, ACM Press.
+delim: " "
+header: None
+col_names:
+ - src
+ - dst
+col_types:
+ - int32
+ - int32
+has_loop: false
+is_directed: false
+is_multigraph: false
+is_symmetric: true
+number_of_edges: 113891327
+number_of_nodes: 1139905
+url: https://data.rapids.ai/cugraph/datasets/hollywood.csv

python/cugraph/cugraph/datasets/metadata/soc-livejournal1.yaml

@@ -0,0 +1,22 @@
+name: soc-LiveJournal1
+file_type: .csv
+description: A graph of the LiveJournal social network.
+author: L. Backstrom, D. Huttenlocher, J. Kleinberg, X. Lan
+refs:
+ L. Backstrom, D. Huttenlocher, J. Kleinberg, X. Lan. Group Formation in 
+ Large Social Networks Membership, Growth, and Evolution. KDD, 2006.
+delim: " "
+header: None
+col_names:
+ - src
+ - dst
+col_types:
+ - int32
+ - int32
+has_loop: false
+is_directed: true
+is_multigraph: false
+is_symmetric: false
+number_of_edges: 68993773
+number_of_nodes: 4847571
+url: https://data.rapids.ai/cugraph/datasets/soc-LiveJournal1.csv

python/cugraph/cugraph/datasets/metadata/soc-twitter-2010.yaml

@@ -0,0 +1,22 @@
+name: soc-twitter-2010
+file_type: .csv
+description: A network of follower relationships from a snapshot of Twitter in 2010, where an edge from i to j indicates that j is a follower of i.
+author: H. Kwak, C. Lee, H. Park, S. Moon
+refs:
+ J. Yang, J. Leskovec. Temporal Variation in Online Media. ACM Intl. 
+ Conf. on Web Search and Data Mining (WSDM '11), 2011. 
+delim: " "
+header: None
+col_names:
+ - src
+ - dst
+col_types:
+ - int32
+ - int32
+has_loop: true
+is_directed: false
+is_multigraph: false
+is_symmetric: false
+number_of_edges: 530051354
+number_of_nodes: 21297772
+url: https://data.rapids.ai/cugraph/datasets/soc-twitter-2010.csv

python/cugraph/cugraph/tests/utils/test_dataset.py

@@ -94,6 +94,7 @@ def setup_deprecation_warning_tests():
 # Helpers
 
 # check if there is a row where src == dst
+# Should this be renamed to 'has_self_loop'?
 def has_loop(df):
  df.rename(columns={df.columns[0]: "src", df.columns[1]: "dst"}, inplace=True)
  res = df.where(df["src"] == df["dst"])