GRAPHITE — An Extensible Graph Traversal Framework for RDBMS
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This document discusses integrating graph processing capabilities into relational database management systems (RDBMS). It proposes GRAPHITE, a native graph engine with graph operators that can be combined with other relational operators. GRAPHITE stores graphs columnarly and includes graph traversal operators like fragmented-incremental traversal. It also introduces TraveL, a domain-specific language for writing graph traversals, which can be compiled into execution plans. Initial experimental results on breadth-first search traversals and LDBC Query 1 are provided.
GRAPHITE — An Extensible Graph Traversal Framework for RDBMS
- 1. Marcus Paradies (TU Dresden), March 18, 2015, 3rd Graph-TA Workshop
- 2. Graph Processing on Enterprise Data 2 Relational + Application Logic Relational + Graph + Application Logic Data already in RDBMS SQL as the only interface/no graph abstraction Data transfer to application Efficient processing in GDBMS Processing on replicated data Data transfer to application No combination with other data models possible
- 3. Many graph use cases require support for graph, text, spatial, and temporal processing in a single database engine 3 Patient Diagnosis Patient Record Type: getsDiagn Date: March 16, 2015 Type: getsDiagn Date: May 6, 2012 Type: belongsTo Type: belongsToID: 1 Content: „The patient...“ ID: 2 Content: „For patient…“ Type: gets Date: May 8, 2012 Type: belongsTo ID: 3 Content: „The patient...“ PID: 1 Name: „Jake Maier“ PID: 2 Name: „Andreas Cook“ Hospital Keyword Type: hasKeyword Type: hasKeyword Description: „Flu..“ Type: stayedIn From: May 6, 2012 To: May 8, 2012 Type: stayedIn From: May 8, 2012 To: May 10, 2012 HID: 2 Long:49.398752 Lat: 8.672434 HID: 33 Long:49.006890 Lat: 8.403653 Health Care Graph – An Example
- 4. Integration of Graph Processing into an RDBMS How could a deep integration of graph functionality into a RDBMS look like? GRAPHITE is a native graph engine with graph operators that are freely combinable with other plan operators 4
- 5. Architecture of GRAPHITE Graph Storage Graph Index Structures Physical Graph Operators Logical Graph Operators Graph Statistics Graph Optimizer TraveL TraveL Compiler Graph API 5
- 6. Columnar Graph Storage All data types available in the RDBMS can be used as vertex/edge attributes 6
- 7. Graph Traversal Operators 7 Fragmented-Incremental Traversal (FI-Traversal)
- 8. TraveL – A DSL for Graph Traversals 8 Code GenerationExample Query
- 9. Initial Experimental Results 9 Experimental Results for BFS Traversals Experimental Results for LDBC Query 1
- 10. Marcus Paradies, TU Dresden marcus.paradies@gmail.com https://wwwdb.inf.tu-dresden.de/team/external-members/marcus-paradies/