erpc_analysis::db_trait

Trait AnalysisDatabase

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pub trait AnalysisDatabase: Send + Sync {
Show 17 methods // Required methods fn create_graph_projection<'life0, 'life1, 'async_trait>( &'life0 self, params: &'life1 GraphProjectionParams, ) -> Pin<Box<dyn Future<Output = Result<(), AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn delete_graph_projection<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<(), AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn check_graph_projection_exists<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<bool, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn calculate_node_degrees<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<Vec<NodeMetrics>, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn calculate_graph_metrics<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<GraphMetrics, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn calculate_weakly_connected_components<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<ComponentAnalysisResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn calculate_strongly_connected_components<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<ComponentAnalysisResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn calculate_louvain_communities<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, projection_name: &'life1 str, params: &'life2 LouvainConfig, ) -> Pin<Box<dyn Future<Output = Result<ComponentAnalysisResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait; fn calculate_label_propagation_communities<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, projection_name: &'life1 str, params: &'life2 LabelPropagationConfig, ) -> Pin<Box<dyn Future<Output = Result<ComponentAnalysisResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait; fn calculate_modularity<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, projection_name: &'life1 str, community_property: &'life2 str, ) -> Pin<Box<dyn Future<Output = Result<f64, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait; fn classify_components_by_geography<'life0, 'life1, 'async_trait>( &'life0 self, components: &'life1 [ConnectedComponent], ) -> Pin<Box<dyn Future<Output = Result<PartitionClassificationResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn classify_components_by_asn<'life0, 'life1, 'async_trait>( &'life0 self, components: &'life1 [ConnectedComponent], ) -> Pin<Box<dyn Future<Output = Result<PartitionClassificationResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn classify_components_by_family<'life0, 'life1, 'async_trait>( &'life0 self, components: &'life1 [ConnectedComponent], ) -> Pin<Box<dyn Future<Output = Result<PartitionClassificationResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn calculate_betweenness_centrality<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, sampling_size: Option<usize>, sampling_seed: Option<u64>, ) -> Pin<Box<dyn Future<Output = Result<CentralityAnalysisResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn calculate_closeness_centrality<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, use_wasserman_faust: Option<bool>, ) -> Pin<Box<dyn Future<Output = Result<CentralityAnalysisResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn calculate_combined_centrality<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, betweenness_sampling_size: Option<usize>, betweenness_sampling_seed: Option<u64>, use_wasserman_faust: Option<bool>, ) -> Pin<Box<dyn Future<Output = Result<CentralityAnalysisResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait; fn analyze_paths_between_communities<'life0, 'life1, 'life2, 'life3, 'async_trait>( &'life0 self, projection_name: &'life1 str, source_nodes: &'life2 [String], target_nodes: &'life3 [String], ) -> Pin<Box<dyn Future<Output = Result<PathAnalysisResult, AnalysisError>> + Send + 'async_trait>> where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait, 'life3: 'async_trait;
}
Expand description

Trait defining the interface for database operations required by the eRPC analysis engine.

Required Methods§

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fn create_graph_projection<'life0, 'life1, 'async_trait>( &'life0 self, params: &'life1 GraphProjectionParams, ) -> Pin<Box<dyn Future<Output = Result<(), AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Creates or recreates a GDS graph projection. If a projection with the same name exists, it should ideally be dropped and recreated.

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fn delete_graph_projection<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<(), AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Deletes an existing GDS graph projection if it exists. Should succeed even if the projection does not exist (making it idempotent).

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fn check_graph_projection_exists<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<bool, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Checks if a GDS graph projection with the given name exists.

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fn calculate_node_degrees<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<Vec<NodeMetrics>, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Calculates node-level degree metrics for all nodes in a given GDS projection. Returns a vector of NodeMetrics containing in-degree, out-degree, and total degree for each node in the graph.

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fn calculate_graph_metrics<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<GraphMetrics, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Calculates comprehensive graph metrics for a given GDS projection including basic counts, degree distribution, and degree statistics.

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fn calculate_weakly_connected_components<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<ComponentAnalysisResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Calculates weakly connected components using Neo4j GDS WCC algorithm. Returns analysis results containing components, sizes, and statistics.

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fn calculate_strongly_connected_components<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<ComponentAnalysisResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Calculates strongly connected components using Neo4j GDS SCC algorithm. Returns analysis results containing components, sizes, and statistics.

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fn calculate_louvain_communities<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, projection_name: &'life1 str, params: &'life2 LouvainConfig, ) -> Pin<Box<dyn Future<Output = Result<ComponentAnalysisResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Calculates communities using Neo4j GDS Louvain algorithm. Returns analysis results containing communities, sizes, and statistics.

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fn calculate_label_propagation_communities<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, projection_name: &'life1 str, params: &'life2 LabelPropagationConfig, ) -> Pin<Box<dyn Future<Output = Result<ComponentAnalysisResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Calculates communities using Neo4j GDS Label Propagation algorithm. Returns analysis results containing communities, sizes, and statistics.

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fn calculate_modularity<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, projection_name: &'life1 str, community_property: &'life2 str, ) -> Pin<Box<dyn Future<Output = Result<f64, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Calculates modularity score for a given community assignment. Higher modularity indicates better community structure.

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fn classify_components_by_geography<'life0, 'life1, 'async_trait>( &'life0 self, components: &'life1 [ConnectedComponent], ) -> Pin<Box<dyn Future<Output = Result<PartitionClassificationResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Classifies connected components by geographic location (country). Groups relays by country and analyzes their distribution across components.

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fn classify_components_by_asn<'life0, 'life1, 'async_trait>( &'life0 self, components: &'life1 [ConnectedComponent], ) -> Pin<Box<dyn Future<Output = Result<PartitionClassificationResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Classifies connected components by ASN. Groups relays by ASN and analyzes their distribution across components.

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fn classify_components_by_family<'life0, 'life1, 'async_trait>( &'life0 self, components: &'life1 [ConnectedComponent], ) -> Pin<Box<dyn Future<Output = Result<PartitionClassificationResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Classifies connected components by relay family relationships. Groups relays by family membership and analyzes their distribution across components.

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fn calculate_betweenness_centrality<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, sampling_size: Option<usize>, sampling_seed: Option<u64>, ) -> Pin<Box<dyn Future<Output = Result<CentralityAnalysisResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Calculates betweenness centrality for nodes in a GDS projection. Uses Neo4j GDS betweenness centrality algorithm to identify nodes that act as bridges between other nodes.

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fn calculate_closeness_centrality<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, use_wasserman_faust: Option<bool>, ) -> Pin<Box<dyn Future<Output = Result<CentralityAnalysisResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Calculates closeness centrality for nodes in a GDS projection. Uses Neo4j GDS closeness centrality algorithm to identify nodes that are close to all other nodes in the network.

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fn calculate_combined_centrality<'life0, 'life1, 'async_trait>( &'life0 self, projection_name: &'life1 str, betweenness_sampling_size: Option<usize>, betweenness_sampling_seed: Option<u64>, use_wasserman_faust: Option<bool>, ) -> Pin<Box<dyn Future<Output = Result<CentralityAnalysisResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Calculates both betweenness and closeness centrality

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fn analyze_paths_between_communities<'life0, 'life1, 'life2, 'life3, 'async_trait>( &'life0 self, projection_name: &'life1 str, source_nodes: &'life2 [String], target_nodes: &'life3 [String], ) -> Pin<Box<dyn Future<Output = Result<PathAnalysisResult, AnalysisError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait, 'life3: 'async_trait,

Analyzes shortest paths between nodes from different communities. Uses Neo4j GDS shortest path algorithms to understand inter-community connectivity.

Implementors§