Implement batch query funtions for PGGraphStorage of PostgreSQl AGE graph storage
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@@ -1458,6 +1458,197 @@ class PGGraphStorage(BaseGraphStorage):
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logger.error(f"Error during edge deletion: {str(e)}")
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raise
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async def get_nodes_batch(self, node_ids: list[str]) -> dict[str, dict]:
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"""
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Retrieve multiple nodes in one query using UNWIND.
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Args:
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node_ids: List of node entity IDs to fetch.
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Returns:
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A dictionary mapping each node_id to its node data (or None if not found).
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"""
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if not node_ids:
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return {}
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# Format node IDs for the query
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formatted_ids = ", ".join(['"' + node_id.replace('"', '') + '"' for node_id in node_ids])
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query = """SELECT * FROM cypher('%s', $$
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UNWIND [%s] AS node_id
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MATCH (n:base {entity_id: node_id})
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RETURN node_id, n
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$$) AS (node_id text, n agtype)""" % (
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self.graph_name,
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formatted_ids
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)
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results = await self._query(query)
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# Build result dictionary
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nodes_dict = {}
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for result in results:
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if result["node_id"] and result["n"]:
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node_dict = result["n"]["properties"]
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# Remove the 'base' label if present in a 'labels' property
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if "labels" in node_dict:
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node_dict["labels"] = [label for label in node_dict["labels"] if label != "base"]
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nodes_dict[result["node_id"]] = node_dict
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return nodes_dict
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async def node_degrees_batch(self, node_ids: list[str]) -> dict[str, int]:
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"""
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Retrieve the degree for multiple nodes in a single query using UNWIND.
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Args:
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node_ids: List of node labels (entity_id values) to look up.
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Returns:
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A dictionary mapping each node_id to its degree (number of relationships).
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If a node is not found, its degree will be set to 0.
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"""
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if not node_ids:
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return {}
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# Format node IDs for the query
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formatted_ids = ", ".join(['"' + node_id.replace('"', '') + '"' for node_id in node_ids])
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query = """SELECT * FROM cypher('%s', $$
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UNWIND [%s] AS node_id
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MATCH (n:base {entity_id: node_id})
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OPTIONAL MATCH (n)-[r]-()
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RETURN node_id, count(r) AS degree
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$$) AS (node_id text, degree bigint)""" % (
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self.graph_name,
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formatted_ids
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)
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results = await self._query(query)
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# Build result dictionary
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degrees_dict = {}
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for result in results:
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if result["node_id"] is not None:
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degrees_dict[result["node_id"]] = int(result["degree"])
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# Ensure all requested node_ids are in the result dictionary
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for node_id in node_ids:
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if node_id not in degrees_dict:
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degrees_dict[node_id] = 0
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return degrees_dict
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async def edge_degrees_batch(self, edges: list[tuple[str, str]]) -> dict[tuple[str, str], int]:
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"""
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Calculate the combined degree for each edge (sum of the source and target node degrees)
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in batch using the already implemented node_degrees_batch.
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Args:
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edges: List of (source_node_id, target_node_id) tuples
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Returns:
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Dictionary mapping edge tuples to their combined degrees
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"""
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if not edges:
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return {}
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# Use node_degrees_batch to get all node degrees efficiently
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all_nodes = set()
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for src, tgt in edges:
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all_nodes.add(src)
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all_nodes.add(tgt)
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node_degrees = await self.node_degrees_batch(list(all_nodes))
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# Calculate edge degrees
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edge_degrees_dict = {}
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for src, tgt in edges:
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src_degree = node_degrees.get(src, 0)
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tgt_degree = node_degrees.get(tgt, 0)
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edge_degrees_dict[(src, tgt)] = src_degree + tgt_degree
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return edge_degrees_dict
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async def get_edges_batch(self, pairs: list[dict[str, str]]) -> dict[tuple[str, str], dict]:
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"""
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Retrieve edge properties for multiple (src, tgt) pairs in one query.
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Args:
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pairs: List of dictionaries, e.g. [{"src": "node1", "tgt": "node2"}, ...]
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Returns:
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A dictionary mapping (src, tgt) tuples to their edge properties.
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"""
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if not pairs:
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return {}
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# 从字典列表中提取源节点和目标节点ID
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src_nodes = []
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tgt_nodes = []
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for pair in pairs:
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src_nodes.append(pair["src"].replace('"', ''))
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tgt_nodes.append(pair["tgt"].replace('"', ''))
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# 构建查询,使用数组索引来匹配源节点和目标节点
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src_array = ", ".join([f'"{src}"' for src in src_nodes])
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tgt_array = ", ".join([f'"{tgt}"' for tgt in tgt_nodes])
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query = f"""SELECT * FROM cypher('{self.graph_name}', $$
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WITH [{src_array}] AS sources, [{tgt_array}] AS targets
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UNWIND range(0, size(sources)-1) AS i
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MATCH (a:base {{entity_id: sources[i]}})-[r:DIRECTED]-(b:base {{entity_id: targets[i]}})
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RETURN sources[i] AS source, targets[i] AS target, properties(r) AS edge_properties
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$$) AS (source text, target text, edge_properties agtype)"""
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results = await self._query(query)
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# 构建结果字典
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edges_dict = {}
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for result in results:
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if result["source"] and result["target"] and result["edge_properties"]:
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edges_dict[(result["source"], result["target"])] = result["edge_properties"]
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return edges_dict
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async def get_nodes_edges_batch(self, node_ids: list[str]) -> dict[str, list[tuple[str, str]]]:
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"""
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Get all edges for multiple nodes in a single batch operation.
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Args:
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node_ids: List of node IDs to get edges for
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Returns:
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Dictionary mapping node IDs to lists of (source, target) edge tuples
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"""
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if not node_ids:
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return {}
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# Format node IDs for the query
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formatted_ids = ", ".join(['"' + node_id.replace('"', '') + '"' for node_id in node_ids])
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query = """SELECT * FROM cypher('%s', $$
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UNWIND [%s] AS node_id
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MATCH (n:base {entity_id: node_id})
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OPTIONAL MATCH (n)-[]-(connected:base)
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RETURN node_id, connected.entity_id AS connected_id
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$$) AS (node_id text, connected_id text)""" % (
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self.graph_name,
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formatted_ids
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)
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results = await self._query(query)
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# Build result dictionary
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nodes_edges_dict = {node_id: [] for node_id in node_ids}
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for result in results:
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if result["node_id"] and result["connected_id"]:
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nodes_edges_dict[result["node_id"]].append(
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(result["node_id"], result["connected_id"])
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)
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return nodes_edges_dict
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async def get_all_labels(self) -> list[str]:
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"""
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Get all labels (node IDs) in the graph.
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