def report_graph(
graph, report_type, node=None, edge=None, fid=None, lid=None, key=None
):
"""Create report operation for nx graph.
This operation is used to simulate networkx graph reporting methods with variaty
report type and corresponding config parameters.
Args:
graph (`nx.Graph`): A nx graph.
report_type: report type, can be
type_pb2.(NODE_NUM,
EDGE_NUM,
HAS_NODE,
HAS_EDGE,
NODE_DATA,
EDGE_DATA,
NEIGHBORS_BY_NODE,
SUCCS_BY_NODE,
PREDS_BY_NODE,
NEIGHBORS_BY_LOC,
SUCCS_BY_LOC,
PREDS_BY_LOC,
DEG_BY_NODE,
IN_DEG_BY_NODE,
OUT_DEG_BY_NODE,
DEG_BY_LOC,
IN_DEG_BY_LOC,
OUT_DEG_BY_LOC,
NODES_BY_LOC)
node (str): node id, used as node id with 'NODE' report types. (optional)
edge (str): an edge with 'EDGE' report types. (optional)
fid (int): fragment id, with 'LOC' report types. (optional)
lid (int): local id of node in grape_engine, with 'LOC; report types. (optional)
key (str): edge key for MultiGraph or MultiDiGraph, with 'EDGE' report types. (optional)
Returns:
An op to do reporting job.
"""
config = {
types_pb2.GRAPH_NAME: utils.s_to_attr(graph.key),
types_pb2.REPORT_TYPE: utils.report_type_to_attr(report_type),
}
if node is not None:
config[types_pb2.NODE] = utils.s_to_attr(node)
if edge is not None:
config[types_pb2.EDGE] = utils.s_to_attr(edge)
if fid is not None:
config[types_pb2.FID] = utils.i_to_attr(fid)
if lid is not None:
config[types_pb2.LID] = utils.i_to_attr(lid)
config[types_pb2.EDGE_KEY] = utils.s_to_attr(str(key) if key is not None else "")
op = Operation(
graph.session_id,
types_pb2.REPORT_GRAPH,
config=config,
output_types=types_pb2.RESULTS,
)
return op
def add_edges(graph, **kwargs):
"""Create an `ADD_EDGES` op, add op to default dag.
Args:
graph (:class:`Graph`): a :class:`Graph` instance.
**kwargs: additional properties respect to different `graph_type`.
Returns:
An op to add edges to a graph in c++ side with necessary configurations.
"""
config = {
types_pb2.GRAPH_NAME: utils.s_to_attr(graph.key),
types_pb2.GRAPH_TYPE: utils.graph_type_to_attr(graph.graph_type),
}
if graph.graph_type == types_pb2.ARROW_PROPERTY:
attrs = kwargs.pop("attrs", None)
if attrs:
for k, v in attrs.items():
if isinstance(v, attr_value_pb2.AttrValue):
config[k] = v
else:
raise ValueError(f"Not support add edges on graph type {graph.graph_type}")
op = Operation(
graph.session_id,
types_pb2.ADD_EDGES,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def output(context, fd, selector, vertex_range, **kwargs):
"""Output result to `fd`, this will be handled by registered vineyard C++ adaptor.
Args:
results (:class:`Context`): Results return by `run_app` operation, store the query results.
fd (str): Such as `file:///tmp/result_path`
selector (str): Select the type of data to retrieve.
vertex_range (str): Specify a range to retrieve.
Returns:
An op to output results to `fd`.
"""
config = {}
config[types_pb2.FD] = utils.s_to_attr(fd)
config[types_pb2.SELECTOR] = utils.s_to_attr(selector)
config[types_pb2.STORAGE_OPTIONS] = utils.s_to_attr(json.dumps(kwargs))
if vertex_range is not None:
config[types_pb2.VERTEX_RANGE] = utils.s_to_attr(vertex_range)
op = Operation(
context.session_id,
types_pb2.OUTPUT,
config=config,
inputs=[context.op],
output_types=types_pb2.NULL_OUTPUT,
)
return op
def to_undirected(graph):
"""Create to_undirected operation for graph.
Args:
graph (:class:`nx.Graph`)
Returns:
Operation
"""
check_argument(
graph.graph_type
in (graph_def_pb2.DYNAMIC_PROPERTY, graph_def_pb2.ARROW_PROPERTY)
)
config = {}
# The key maybe filled later in coordinator
if hasattr(graph, "key"):
config[types_pb2.GRAPH_NAME] = utils.s_to_attr(graph.key)
op = Operation(
graph.session_id,
types_pb2.TO_UNDIRECTED,
config=config,
inputs=[graph.op],
output_types=types_pb2.GRAPH,
)
return op
def project_dynamic_property_graph(graph, v_prop, e_prop, v_prop_type, e_prop_type):
"""Create project graph operation for nx graph.
Args:
graph (:class:`nx.Graph`): A nx graph.
v_prop (str): The node attribute key to project.
e_prop (str): The edge attribute key to project.
v_prop_type (str): Type of the node attribute.
e_prop_type (str): Type of the edge attribute.
Returns:
Operation to project a dynamic property graph. Results in a simple graph.
"""
check_argument(graph.graph_type == types_pb2.DYNAMIC_PROPERTY)
config = {
types_pb2.GRAPH_NAME: utils.s_to_attr(graph.key),
types_pb2.GRAPH_TYPE: utils.graph_type_to_attr(types_pb2.DYNAMIC_PROJECTED),
types_pb2.V_PROP_KEY: utils.s_to_attr(v_prop),
types_pb2.E_PROP_KEY: utils.s_to_attr(e_prop),
types_pb2.V_DATA_TYPE: utils.s_to_attr(utils.data_type_to_cpp(v_prop_type)),
types_pb2.E_DATA_TYPE: utils.s_to_attr(utils.data_type_to_cpp(e_prop_type)),
}
op = Operation(
graph.session_id,
types_pb2.PROJECT_GRAPH,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def create_learning_instance(graph, nodes=None, edges=None, gen_labels=None):
"""Create an engine for graph learning.
Args:
graph (:class:`graphscope.framework.graph.GraphDAGNode`):
Source property graph.
nodes (list): The node types that will be used for gnn training.
edges (list): The edge types that will be used for gnn training.
gen_labels (list): Extra node and edge labels on original graph for gnn training.
Returns:
An op to create a learning engine based on a graph.
"""
config = {}
# pickle None is expected
config[types_pb2.NODES] = utils.bytes_to_attr(pickle.dumps(nodes))
config[types_pb2.EDGES] = utils.bytes_to_attr(pickle.dumps(edges))
config[types_pb2.GLE_GEN_LABELS] = utils.bytes_to_attr(
pickle.dumps(gen_labels))
op = Operation(
graph.session_id,
types_pb2.CREATE_LEARNING_INSTANCE,
config=config,
inputs=[graph.op],
output_types=types_pb2.LEARNING_GRAPH,
)
return op
def gremlin_to_subgraph(
interactive_query, gremlin_script, request_options=None, oid_type="int64"
):
"""Create a subgraph from gremlin output.
Args:
interactive_query (:class:`graphscope.interactive.query.InteractiveQueryDAGNode`):
The GIE instance holds the graph that gremlin query on.
gremlin_script (str):
gremlin script to be executed.
request_options (dict, optional): gremlin request options. format:
{
"engine": "gae"
}
oid_type (str, optional):
Type of vertex original id. Defaults to "int64".
Returns:
An op to create the subgraph from gremlin script
"""
config = {}
config[types_pb2.GIE_GREMLIN_QUERY_MESSAGE] = utils.s_to_attr(gremlin_script)
config[types_pb2.OID_TYPE] = utils.s_to_attr(oid_type)
if request_options:
config[types_pb2.GIE_GREMLIN_REQUEST_OPTIONS] = utils.s_to_attr(
json.dumps(request_options)
)
op = Operation(
interactive_query.session_id,
types_pb2.SUBGRAPH,
config=config,
inputs=[interactive_query.op],
output_types=types_pb2.GRAPH,
)
return op
def modify_edges(graph, modify_type, edges, attr={}, weight=None):
"""Create modify edges operation for nx graph.
Args:
graph (:class:`nx.Graph`): A nx graph.
modify_type (`type_pb2.(NX_ADD_EDGES | NX_DEL_EDGES | NX_UPDATE_EDGES)`): The modify type
edges (list): List of edges to be inserted into or delete from graph based on `modify_type`
Returns:
An op to modify edges on the graph.
"""
check_argument(graph.graph_type == graph_def_pb2.DYNAMIC_PROPERTY)
config = {}
config[types_pb2.GRAPH_NAME] = utils.s_to_attr(graph.key)
config[types_pb2.MODIFY_TYPE] = utils.modify_type_to_attr(modify_type)
config[types_pb2.PROPERTIES] = utils.s_to_attr(json.dumps(attr))
if weight:
config[types_pb2.EDGE_KEY] = utils.s_to_attr(weight)
op = Operation(
graph.session_id,
types_pb2.MODIFY_EDGES,
config=config,
large_attr=utils.bytes_to_large_attr(edges),
output_types=types_pb2.GRAPH,
)
return op
def project_arrow_property_graph_to_simple(
graph,
v_prop,
e_prop,
):
"""Project arrow property graph to a simple graph.
Args:
graph (:class:`graphscope.Graph`): Source graph, which type should be ARROW_PROPERTY
v_prop (str): The node attribute key to project.
e_prop (str): The edge attribute key to project.
Returns:
Operation to project a property graph, results in a simple ARROW_PROJECTED graph.
"""
check_argument(graph.graph_type == graph_def_pb2.ARROW_PROPERTY)
config = {
types_pb2.V_PROP_KEY: utils.s_to_attr(v_prop),
types_pb2.E_PROP_KEY: utils.s_to_attr(e_prop),
}
op = Operation(
graph.session_id,
types_pb2.PROJECT_TO_SIMPLE,
config=config,
inputs=[graph.op],
output_types=types_pb2.GRAPH,
)
return op
def run_app(graph, app, *args, **kwargs):
"""Run `app` on the `graph`.
Args:
graph (:class:`Graph`): A loaded graph.
app (:class:`App`): A loaded app that will be queried.
key (str): Key of query results, can be used to retrieve results.
*args: Additional query params that will be used in evaluation.
**kwargs: Key-value formated query params that mostly used in Cython apps.
Returns:
An op to run app on the specified graph, with optional query parameters.
"""
config = {
types_pb2.GRAPH_NAME: utils.s_to_attr(graph.key),
types_pb2.APP_NAME: utils.s_to_attr(app.key),
}
output_prefix = kwargs.pop("output_prefix", ".")
config[types_pb2.OUTPUT_PREFIX] = utils.s_to_attr(output_prefix)
# optional query arguments.
params = utils.pack_query_params(*args, **kwargs)
query_args = query_args_pb2.QueryArgs()
query_args.args.extend(params)
op = Operation(
graph._session_id,
types_pb2.RUN_APP,
config=config,
output_types=types_pb2.RESULTS,
query_args=query_args,
)
return op
def arrow_to_dynamic(graph):
"""Transform a :class:`Graph` object to :class:`nx.Graph`.
Args:
graph (:class:`Graph`): Source graph, which type should be ARROW_PROPERTY.
Returns:
An op of transform arrow graph to dynamic graph with necessary configurations.
"""
check_argument(graph.graph_type == graph_def_pb2.ARROW_PROPERTY)
config = {
types_pb2.GRAPH_NAME:
utils.s_to_attr(graph.key),
types_pb2.GRAPH_TYPE:
utils.graph_type_to_attr(graph_def_pb2.ARROW_PROPERTY),
types_pb2.DST_GRAPH_TYPE:
utils.graph_type_to_attr(graph_def_pb2.DYNAMIC_PROPERTY),
types_pb2.OID_TYPE:
utils.s_to_attr(utils.data_type_to_cpp(graph.schema.oid_type)),
types_pb2.VID_TYPE:
utils.s_to_attr(utils.data_type_to_cpp(graph.schema.vid_type)),
types_pb2.DEFAULT_LABEL_ID:
utils.i_to_attr(graph._default_label_id),
}
op = Operation(
graph.session_id,
types_pb2.TRANSFORM_GRAPH,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def to_vineyard_tensor(context, selector=None, vertex_range=None, axis=None):
"""Retrieve results as vineyard tensor.
Parameters:
results (:class:`Context`): Results return by `run_app` operation, store the query results.
selector (str): Select the type of data to retrieve.
vertex_range (str): Specify a range to retrieve.
Returns:
An op to convert query results into a vineyard tensor.
"""
config = {}
if selector is not None:
config[types_pb2.SELECTOR] = utils.s_to_attr(selector)
if vertex_range is not None:
config[types_pb2.VERTEX_RANGE] = utils.s_to_attr(vertex_range)
if axis is not None:
config[types_pb2.AXIS] = utils.i_to_attr(axis)
op = Operation(
context.session_id,
types_pb2.TO_VINEYARD_TENSOR,
config=config,
inputs=[context.op],
output_types=types_pb2.VINEYARD_TENSOR,
)
return op
def context_to_numpy(context, selector=None, vertex_range=None, axis=0):
"""Retrieve results as a numpy ndarray.
Args:
results (:class:`Context`): Results return by `run_app` operation, store the query results.
selector (str): Select the type of data to retrieve.
vertex_range (str): Specify a range to retrieve.
Returns:
An op to retrieve query results and convert to numpy ndarray.
"""
config = {}
if selector is not None:
config[types_pb2.SELECTOR] = utils.s_to_attr(selector)
if vertex_range is not None:
config[types_pb2.VERTEX_RANGE] = utils.s_to_attr(vertex_range)
if axis is not None:
config[types_pb2.AXIS] = utils.i_to_attr(axis)
op = Operation(
context.session_id,
types_pb2.CONTEXT_TO_NUMPY,
config=config,
inputs=[context.op],
output_types=types_pb2.TENSOR,
)
return op
def create_interactive_query(graph, engine_params):
"""Create a interactive engine that query on the :code:`graph`
Args:
graph (:class:`graphscope.framework.graph.GraphDAGNode`):
Source property graph.
engine_params (dict, optional):
Configuration to startup the interactive engine. See detail in:
`interactive_engine/deploy/docker/dockerfile/executor.vineyard.properties`
Returns:
An op to create a interactive engine based on a graph.
"""
config = {}
if engine_params is not None:
config[types_pb2.GIE_GREMLIN_ENGINE_PARAMS] = utils.s_to_attr(
json.dumps(engine_params))
op = Operation(
graph.session_id,
types_pb2.CREATE_INTERACTIVE_QUERY,
config=config,
inputs=[graph.op],
output_types=types_pb2.INTERACTIVE_QUERY,
)
return op
def run_app(app, *args, **kwargs):
"""Run `bound app` on the `graph`.
Args:
app (:class:`AppDAGNode`): A :class:`AppDAGNode` instance which represent a bound app.
key (str): Key of query results, can be used to retrieve results.
*args: Additional query params that will be used in evaluation.
**kwargs: Key-value formated query params that mostly used in Cython apps.
Returns:
An op to run app on the specified graph, with optional query parameters.
"""
inputs = [app.op]
config = {}
output_prefix = kwargs.pop("output_prefix", ".")
config[types_pb2.OUTPUT_PREFIX] = utils.s_to_attr(output_prefix)
# optional query arguments.
params = utils.pack_query_params(*args, **kwargs)
query_args = query_args_pb2.QueryArgs()
query_args.args.extend(params)
op = Operation(
app.session_id,
types_pb2.RUN_APP,
inputs=inputs,
config=config,
output_types=types_pb2.RESULTS,
query_args=query_args,
)
return op
def graph_to_dataframe(graph, selector=None, vertex_range=None):
"""Retrieve graph raw data as a pandas DataFrame.
Args:
graph (:class:`Graph`): Source graph.
selector (str): Select the type of data to retrieve.
vertex_range (str): Specify a range to retrieve.
Returns:
An op to convert a graph's data to pandas DataFrame.
"""
config = {
types_pb2.GRAPH_NAME: utils.s_to_attr(graph.key),
}
if selector is not None:
config[types_pb2.SELECTOR] = utils.s_to_attr(selector)
if vertex_range is not None:
config[types_pb2.VERTEX_RANGE] = utils.s_to_attr(vertex_range)
op = Operation(
graph._session_id,
types_pb2.GRAPH_TO_DATAFRAME,
config=config,
output_types=types_pb2.DATAFRAME,
)
return op
def create_graph(session_id, graph_type, **kwargs):
"""Create an `CREATE_GRAPH` op, add op to default dag.
Args:
session_id (str): Refer to session that the graph will be create on.
graph_type (:enum:`GraphType`): GraphType defined in proto.types.proto.
**kwargs: additional properties respect to different `graph_type`.
Returns:
An op to create a graph in c++ side with necessary configurations.
"""
config = {
types_pb2.GRAPH_TYPE: utils.graph_type_to_attr(graph_type),
}
if graph_type == types_pb2.ARROW_PROPERTY:
attrs = kwargs.pop("attrs", None)
if attrs:
for k, v in attrs.items():
if isinstance(v, attr_value_pb2.AttrValue):
config[k] = v
elif graph_type == types_pb2.DYNAMIC_PROPERTY:
config[types_pb2.E_FILE] = utils.s_to_attr(kwargs["efile"])
config[types_pb2.V_FILE] = utils.s_to_attr(kwargs["vfile"])
config[types_pb2.DIRECTED] = utils.b_to_attr(kwargs["directed"])
else:
raise RuntimeError("Not supported graph type {}".format(graph_type))
op = Operation(session_id,
types_pb2.CREATE_GRAPH,
config=config,
output_types=types_pb2.GRAPH)
return op
def add_column(graph, results, selector):
"""Add a column to `graph`, produce a new graph.
Args:
graph (:class:`Graph`): Source ArrowProperty graph.
results (:class:`Context`): Results that generated by previous app querying.
selector (str): Used to select a subrange of data of results, add them
as one column of graph.
Returns:
A new graph with new columns added.
"""
config = {
types_pb2.GRAPH_NAME: utils.s_to_attr(graph.key),
types_pb2.GRAPH_TYPE: utils.graph_type_to_attr(graph.graph_type),
types_pb2.CTX_NAME: utils.s_to_attr(results.key),
types_pb2.SELECTOR: utils.s_to_attr(selector),
}
op = Operation(
graph._session_id,
types_pb2.ADD_COLUMN,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def context_to_dataframe(results, selector=None, vertex_range=None):
"""Retrieve results as a pandas DataFrame.
Args:
results (:class:`Context`): Results return by `run_app` operation, store the query results.
selector (str): Select the type of data to retrieve.
vertex_range (str): Specify a range to retrieve.
Returns:
An op to retrieve query results and convert to pandas DataFrame.
"""
config = {
types_pb2.CTX_NAME: utils.s_to_attr(results.key),
}
if selector is not None:
config[types_pb2.SELECTOR] = utils.s_to_attr(selector)
if vertex_range is not None:
config[types_pb2.VERTEX_RANGE] = utils.s_to_attr(vertex_range)
op = Operation(
results._session_id,
types_pb2.CONTEXT_TO_DATAFRAME,
config=config,
output_types=types_pb2.DATAFRAME,
)
return op
def create_subgraph(graph, nodes=None, edges=None):
"""Create subgraph operation for nx graph.
Args:
graph (:class:`nx.Graph`): A nx graph.
nodes (list): the nodes to induce a subgraph.
edges (list): the edges to induce a edge-induced subgraph.
Returns:
Operation
"""
check_argument(graph.graph_type == graph_def_pb2.DYNAMIC_PROPERTY)
config = {
types_pb2.GRAPH_NAME: utils.s_to_attr(graph.key),
}
if nodes is not None:
config[types_pb2.NODES] = utils.bytes_to_attr(nodes)
if edges is not None:
config[types_pb2.EDGES] = utils.bytes_to_attr(edges)
op = Operation(
graph.session_id,
types_pb2.INDUCE_SUBGRAPH,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def copy_graph(graph, copy_type="identical"):
"""Create copy operation for nx graph.
Args:
graph (:class:`nx.Graph`): A nx graph.
copy_type (str): 'identical': copy graph to destination graph without any change.
'reverse': copy graph to destination graph with reversing the graph edges
Returns:
Operation
"""
check_argument(graph.graph_type in (graph_def_pb2.ARROW_PROPERTY,
graph_def_pb2.DYNAMIC_PROPERTY))
check_argument(copy_type in ("identical", "reverse"))
config = {
types_pb2.GRAPH_NAME: utils.s_to_attr(graph.key),
types_pb2.COPY_TYPE: utils.s_to_attr(copy_type),
}
op = Operation(
graph.session_id,
types_pb2.COPY_GRAPH,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def gremlin_query(interactive_query, query, request_options=None):
"""Execute a gremlin query.
Args:
interactive_query (:class:`graphscope.interactive.query.InteractiveQueryDAGNode`):
The GIE instance holds the graph that gremlin query on.
query (str):
Scripts that written in gremlin quering language.
request_options (dict, optional): gremlin request options. format:
{
"engine": "gae"
}
Returns:
An op to execute a gremlin query on the GIE instance.
"""
config = {}
config[types_pb2.GIE_GREMLIN_QUERY_MESSAGE] = utils.s_to_attr(query)
if request_options:
config[types_pb2.GIE_GREMLIN_REQUEST_OPTIONS] = utils.s_to_attr(
json.dumps(request_options))
op = Operation(
interactive_query.session_id,
types_pb2.GREMLIN_QUERY,
config=config,
inputs=[interactive_query.op],
output_types=types_pb2.GREMLIN_RESULTS,
)
return op
def create_unload_op(session_id, op_type, inputs):
"""Uility method to create a unload `Operation` based on op type and op."""
op = Operation(
session_id,
op_type,
inputs=inputs,
output_types=types_pb2.NULL_OUTPUT,
)
return op
def project_arrow_property_graph(
graph,
v_label_id,
v_prop_id,
e_label_id,
e_prop_id,
v_data_type,
e_data_type,
oid_type=None,
vid_type=None,
):
"""Project arrow property graph to a simple graph.
Args:
graph (:class:`Graph`): Source graph, which type should be ARROW_PROPERTY
dst_graph_key (str): The key of projected graph.
v_label_id (int): Label id of vertex used to project.
v_prop_id (int): Property id of vertex used to project.
e_label_id (int): Label id of edge used to project.
e_prop_id (int): Property id of edge used to project.
Returns:
An op to project `graph`, results in a simple ARROW_PROJECTED graph.
"""
check_argument(graph.graph_type == types_pb2.ARROW_PROPERTY)
config = {
types_pb2.GRAPH_NAME:
utils.s_to_attr(graph.key),
types_pb2.GRAPH_TYPE:
utils.graph_type_to_attr(types_pb2.ARROW_PROJECTED),
types_pb2.V_LABEL_ID:
utils.i_to_attr(v_label_id),
types_pb2.V_PROP_ID:
utils.i_to_attr(v_prop_id),
types_pb2.E_LABEL_ID:
utils.i_to_attr(e_label_id),
types_pb2.E_PROP_ID:
utils.i_to_attr(e_prop_id),
types_pb2.OID_TYPE:
utils.s_to_attr(oid_type),
types_pb2.VID_TYPE:
utils.s_to_attr(vid_type),
types_pb2.V_DATA_TYPE:
utils.s_to_attr(utils.data_type_to_cpp(v_data_type)),
types_pb2.E_DATA_TYPE:
utils.s_to_attr(utils.data_type_to_cpp(e_data_type)),
}
op = Operation(
graph._session_id,
types_pb2.PROJECT_GRAPH,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def get_context_data(results, node):
config = {
types_pb2.CONTEXT_KEY: utils.s_to_attr(results.key),
types_pb2.NODE: utils.s_to_attr(node),
}
op = Operation(
results._session_id,
types_pb2.GET_CONTEXT_DATA,
config=config,
output_types=types_pb2.RESULTS,
)
return op
def create_app(app_assets):
"""Wrapper for create an `CREATE_APP` Operation with configuration.
This op will do nothing but provide required information for `BOUND_APP`
"""
config = {types_pb2.APP_ALGO: utils.s_to_attr(app_assets.algo)}
if app_assets.gar is not None:
config[types_pb2.GAR] = utils.bytes_to_attr(app_assets.gar)
op = Operation(
None, types_pb2.CREATE_APP, config=config, output_types=types_pb2.APP
)
return op
def flatten_arrow_property_graph(graph,
v_prop,
e_prop,
v_prop_type,
e_prop_type,
oid_type=None,
vid_type=None):
"""Flatten arrow property graph.
Args:
graph (:class:`nx.Graph`): A nx graph hosts an arrow property graph.
v_prop (str): The vertex property id.
e_prop (str): The edge property id.
v_prop_type (str): Type of the node attribute.
e_prop_type (str): Type of the edge attribute.
oid_type (str): Type of oid.
vid_type (str): Type of vid.
Returns:
Operation to flatten an arrow property graph. Results in a arrow flattened graph.
"""
config = {
types_pb2.GRAPH_NAME:
utils.s_to_attr(graph.key),
types_pb2.GRAPH_TYPE:
utils.graph_type_to_attr(graph_def_pb2.ARROW_FLATTENED),
types_pb2.DST_GRAPH_TYPE:
utils.graph_type_to_attr(graph.graph_type),
types_pb2.V_DATA_TYPE:
utils.s_to_attr(utils.data_type_to_cpp(v_prop_type)),
types_pb2.E_DATA_TYPE:
utils.s_to_attr(utils.data_type_to_cpp(e_prop_type)),
}
if graph.graph_type == graph_def_pb2.ARROW_PROPERTY:
config[types_pb2.V_PROP_KEY] = utils.s_to_attr(str(v_prop))
config[types_pb2.E_PROP_KEY] = utils.s_to_attr(str(e_prop))
config[types_pb2.OID_TYPE] = utils.s_to_attr(
utils.data_type_to_cpp(oid_type))
config[types_pb2.VID_TYPE] = utils.s_to_attr(
utils.data_type_to_cpp(vid_type))
else:
config[types_pb2.V_PROP_KEY] = utils.s_to_attr(v_prop)
config[types_pb2.E_PROP_KEY] = utils.s_to_attr(e_prop)
op = Operation(
graph.session_id,
types_pb2.PROJECT_TO_SIMPLE,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def unload_app(app):
"""Unload a loaded app.
Args:
app (:class:`App`): The app to unload.
Returns:
An op to unload the `app`.
"""
config = {types_pb2.APP_NAME: utils.s_to_attr(app.key)}
op = Operation(
app._session_id, types_pb2.UNLOAD_APP, config=config, output_types=types_pb2.APP
)
return op
def add_labels_to_graph(graph, loader_op):
"""Add new labels to existed graph.
Args:
graph (:class:`Graph`): A graph instance.
May not be fully loaded. i.e. it's in a building
procedure.
loader_op (:class:`graphscope.framework.operation.Operation`):
Operation of loader.
Raises:
NotImplementedError: When encountered not supported graph type.
Returns:
The operation.
Notes:
Since we don't want to trigger the loading, we must not use
any api that can trigger the loading process implicitly.
"""
from graphscope.framework.graph import GraphDAGNode
assert isinstance(graph, GraphDAGNode)
inputs = [graph.op, loader_op]
# vid_type is fixed
config = {
types_pb2.GRAPH_TYPE: utils.graph_type_to_attr(graph._graph_type),
types_pb2.DIRECTED: utils.b_to_attr(graph._directed),
types_pb2.OID_TYPE: utils.s_to_attr(graph._oid_type),
types_pb2.GENERATE_EID: utils.b_to_attr(graph._generate_eid),
types_pb2.VID_TYPE: utils.s_to_attr("uint64_t"),
types_pb2.IS_FROM_VINEYARD_ID: utils.b_to_attr(False),
}
# inferred from the context of the dag.
config.update({types_pb2.GRAPH_NAME: utils.place_holder_to_attr()})
if graph._graph_type != graph_def_pb2.ARROW_PROPERTY:
raise NotImplementedError(
f"Add vertices or edges is not supported yet on graph type {graph._graph_type}"
)
op = Operation(
graph._session.session_id,
types_pb2.ADD_LABELS,
inputs=inputs,
config=config,
output_types=types_pb2.GRAPH,
)
return op
def close_learning_instance(learning_instance):
"""Close the learning instance.
Args:
learning_instance (:class:`graphscope.learning.graph.GraphDAGNode`):
The learning instance.
Returns:
An op to close the instance.
"""
config = {}
op = Operation(
learning_instance.session_id,
types_pb2.CLOSE_LEARNING_INSTANCE,
config=config,
inputs=[learning_instance.op],
output_types=types_pb2.NULL_OUTPUT,
)
return op
