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PG-FD: Mapping Functional Dependencies to the Future Property Graph Schema Standard

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Advances in Databases and Information Systems (ADBIS 2024)

Abstract

There has been a notable effort, in the past five years, to develop and promote Graph Query Language, GQL, as a standard for querying graph data, akin to the role SQL plays in relational data querying. Although this goal is still a work in progress, the graph database community has been advancing by not only defining the GQL specification but also introducing additional specifications such as Property Graph Key, PG-Key, and later Property Graph Schema, PG-Schema, for specifying graph schema and dependencies. In this regard, a number of proposals have been made in the literature for expressing Functional Dependencies in graph data. Our first contribution is a survey of such proposals, highlighting important ones and their differences. Our second contribution is a solution for translating dependencies defined within such proposals into dependencies that conform to PG-Schema. Our solution is accompanied by a working prototype for translating graph dependencies into PG-Schema compliant dependencies.

This work received support from the National Research Agency under the France 2030 program, with reference to ANR-22-PESN-0007.

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Notes

  1. 1.

    https://neo4j.com, https://www.tigergraph.com and https://aws.amazon.com/neptune.

  2. 2.

    https://www.w3.org/TR/rdf-sparql-query/.

  3. 3.

    https://www.iso.org/standard/76120.html and https://www.gqlstandards.org/home.

  4. 4.

    i.e. FDs that conditionally hold in a part of the relation [31].

  5. 5.

    Authors of [36] said they adapt GFD of [18]. However, they used graph database and a syntax inspired from Cypher language [20] and used node id. Therefore, they rather extend GED than GFD.

  6. 6.

    https://networkx.org/.

  7. 7.

    https://oer.gitlab.io/cs/functional-dependencies/.

  8. 8.

    https://networkx.org/documentation/stable/reference/classes/multidigraph.html.

  9. 9.

    https://github.com/MaudeManouvrier/PG-FD.

References

  1. Abedjan, Z., Golab, L., Naumann, F., et al.: Data Profiling. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-01865-7

  2. Alipourlangouri, M.: Temporal dependencies for graphs. In: ACM SIGMOD Conference (2021). https://doi.org/10.1145/3448016.3450586

  3. Angles, R., Bonifati, A., Dumbrava, S., et al.: PG-keys: keys for property graphs. In: ACM SIGMOD Conference (2021). https://doi.org/10.1145/3448016.3457561

  4. Angles, R., Bonifati, A., Dumbrava, S., et al.: PG-schema: schemas for property graphs. PACMMOD 1(2), 1–25 (2023). https://doi.org/10.1145/3589778

    Article  Google Scholar 

  5. Angles, R., Thakkar, H., Tomaszuk, D.: Mapping RDF databases to property graph databases. IEEE Access 8, 86091–86110 (2020). https://doi.org/10.1109/ACCESS.2020.2993117

    Article  Google Scholar 

  6. Boncz, P.: The (sorry) state of graph database systems (2022). Keynote in EDBT

    Google Scholar 

  7. Bonifati, A., Fletcher, G., Voigt, H., et al.: Querying graphs, vol. 10, no. 3, pp. 1–184 (2018). https://doi.org/10.1007/978-3-031-01864-0

  8. Codd, E.F.: Further normalization of the data base relational model. Data Base Syst. 6, 33–64 (1972)

    Google Scholar 

  9. De Virgilio, R., Maccioni, A., Torlone, R.: Converting relational to graph databases. In: GRADES (2013). https://doi.org/10.1145/2484425.2484426

  10. Deutsch, A., Xu, Y., Wu, M., et al.: Aggregation support for modern graph analytics in TigerGraph. In: ACM SIGMOD Conference (2020). https://doi.org/10.1145/3318464.3386144

  11. Fan, W.: Dependencies for graphs: challenges and opportunities. ACM J. Data Inf. Qual. 11(2), 1–12 (2019). https://doi.org/10.1145/3310230

    Article  Google Scholar 

  12. Fan, W., Fan, Z., Tian, C., et al.: Keys for graphs. VLDB Endow. 8(12), 1590–1601 (2015). https://doi.org/10.14778/2824032.2824056

  13. Fan, W., Geerts, F., Jia, X., et al.: Conditional functional dependencies for capturing data inconsistencies. ACM TODS 33(2), 1–48 (2008). https://doi.org/10.1145/1366102.1366103

    Article  Google Scholar 

  14. Fan, W., Jin, R., Liu, M., et al.: Capturing associations in graphs. VLDB Endow. 13(12) (2020). https://doi.org/10.14778/3407790.3407795

  15. Fan, W., Lu, P.: Dependencies for graphs. In: ACM SIGMOD-SIGACT-SIGAI Symposium (2017). https://doi.org/10.1145/3034786.3056114

  16. Fan, W., Lu, P.: Dependencies for graphs. ACM TODS 44(2), 1–40 (2019). https://doi.org/10.1145/3287285

    Article  MathSciNet  Google Scholar 

  17. Fan, W., Wang, X., Wu, Y., et al.: Association rules with graph patterns. VLDB Endow. 8(12), 1502–1513 (2015). https://doi.org/10.14778/2824032.2824048

  18. Fan, W., Wu, Y., Xu, J.: Functional dependencies for graphs. In: ACM SIGMOD Conference (2016). https://doi.org/10.1145/2882903.2915232

  19. Francis, N., Gheerbrant, A., Guagliardo, P., et al.: A researcher’s digest of GQL. In: ICDT Conference, vol. 255 (2023). https://doi.org/10.4230/LIPIcs.ICDT.2023.1

  20. Francis, N., Green, A., Guagliardo, P., et al.: Cypher: an evolving query language for property graphs. In: ACM SIGMOD Conference (2018). https://doi.org/10.1145/3183713.3190657

  21. Kwashie, S., Liu, L., Liu, J., et al.: Certus: an effective entity resolution approach with graph differential dependencies (GDDs). VLDB Endow. 12(6), 653–666 (2019). https://doi.org/10.14778/3311880.3311883

  22. Liu, D., Kwashie, S., Zhang, Y., et al.: An efficient approach for discovering graph entity dependencies (GEDs). Inf. Syst. 125 (2024). https://doi.org/10.1016/j.is.2024.102421

  23. Pokornỳ, J., Valenta, M., Kovačič, J.: Integrity constraints in graph databases. Procedia Comput. Sci. 109, 975–981 (2017). https://doi.org/10.1016/j.procs.2017.05.456

    Article  Google Scholar 

  24. van Rest, O., Hong, S., Kim, J., et al.: PGQL: a property graph query language. In: GRADES (2016). https://doi.org/10.1145/2960414.2960421

  25. Rodriguez, M.A.: The gremlin graph traversal machine and language (invited talk). In: DBPL (2015). https://doi.org/10.1145/2815072.2815073

  26. Sequeda, J.F., Arenas, M., Miranker, D.P.: On directly mapping relational databases to RDF and OWL. In: WWW Conference (2012). https://doi.org/10.1145/2187836.2187924

  27. Shimomura, L.C., Fletcher, G., Yakovets, N.: GGDs: graph generating dependencies. In: ACM CIKM (2020). https://doi.org/10.1145/3340531.3412149

  28. Skavantzos, P., Leck, U., Zhao, K., et al.: Uniqueness constraints for object stores. ACM J. Data Inf. Qual. (2023). https://doi.org/10.1145/3581758

  29. Skavantzos, P., Link, S.: Normalizing property graphs. VLDB Endow. 16(11), 3031–3043 (2023). https://doi.org/10.14778/3611479.3611506

  30. Skavantzos, P., Zhao, K., Link, S.: Uniqueness constraints on property graphs. In: La Rosa, M., Sadiq, S., Teniente, E. (eds.) CAiSE 2021. LNCS, vol. 12751, pp. 280–295. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-79382-1_17

    Chapter  Google Scholar 

  31. Song, S., Chen, L.: Integrity Constraints on Rich Data Types. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-27177-9

    Book  Google Scholar 

  32. Song, S., Gao, F., Huang, R., et al.: Data dependencies extended for variety and veracity: a family tree. IEEE TKDE 34(10), 4717–4736 (2020). https://doi.org/10.1109/TKDE.2020.3046443

    Article  Google Scholar 

  33. Thapa, R.B., Giese, M.: Mapping relational database constraints to SHACL. In: Sattler, U., et al. (eds.) ISWC 2022. LNCS, vol. 13489, pp. 214–230. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-19433-7_13

    Chapter  Google Scholar 

  34. Tian, Y.: The world of graph databases from an industry perspective. ACM SIGMOD Rec. 51(4), 60–67 (2023). https://doi.org/10.1145/3582302.3582320

    Article  Google Scholar 

  35. Zada, M.S.H., Yuan, B., Anjum, A., et al.: Large-scale data integration using graph probabilistic dependencies (GPDs). In: IEEE/ACM BDCAT Conference (2020). https://doi.org/10.1109/BDCAT50828.2020.00028

  36. Zheng, X., Dasgupta, S., Gupta, A.: P2KG: declarative construction and quality evaluation of knowledge graph from polystores. In: Abelló, A., et al. (eds.) ADBIS 2023. CCIS, vol. 1850, pp. 427–439. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-42941-5_37

    Chapter  Google Scholar 

  37. Zhou, G., Kwashie, S., Zhang, Y., et al.: FASTAGEDS: fast approximate graph entity dependency discovery. In: Zhang, F., Wang, H., Barhamgi, M., Chen, L., Zhou, R. (eds.) WISE 2023. LNCS, vol. 14306, pp. 451–465. Springer, Singapore (2023). https://doi.org/10.1007/978-981-99-7254-8_35

    Chapter  Google Scholar 

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Acknowledgment

We would like to thank Ibtissem Khedim, for facilitating the initiation of this project during her master’s research internship, and the referees of the article for their insightful feedback.

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Correspondence to Maude Manouvrier .

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Manouvrier, M., Belhajjame, K. (2024). PG-FD: Mapping Functional Dependencies to the Future Property Graph Schema Standard. In: Tekli, J., Gamper, J., Chbeir, R., Manolopoulos, Y. (eds) Advances in Databases and Information Systems. ADBIS 2024. Lecture Notes in Computer Science, vol 14918. Springer, Cham. https://doi.org/10.1007/978-3-031-70626-4_4

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