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Prof. Stefan F. Keller -Date -13. June 2022 +Date, Time +13. June 2022, 4pm
also available as PDF
-
Synthetic Script & Substitution +
  • Custom Scripts (merchant, employees)
  • +
  • Automation
  • +
  • Result Analysis
  • + + +
  • Showcase employees
  • Conclusion & Future Work
  • @@ -182,7 +186,7 @@

    Content

    section.custom ul { font-size: 0.6em; } -" data-marpit-pagination="3" data-marpit-pagination-total="23" style="--paginate:true;--theme:default;--style:section::after { +" data-marpit-pagination="3" data-marpit-pagination-total="26" style="--paginate:true;--theme:default;--style:section::after { font-size: medium } @@ -212,7 +216,7 @@

    Content

    section.custom ul { font-size: 0.6em; } -" data-marpit-pagination="3" data-marpit-pagination-total="23" style="--paginate:true;--theme:default;--style:section::after { +" data-marpit-pagination="3" data-marpit-pagination-total="26" style="--paginate:true;--theme:default;--style:section::after { font-size: medium } @@ -253,7 +257,7 @@

    Relational DBMS

    section.custom ul { font-size: 0.6em; } -" data-marpit-pagination="3" data-marpit-pagination-total="23" style="" data-size="16:9" data-marpit-advanced-background="pseudo" data-marpit-advanced-background-split="right">
    INSERT INTO Customer (Id, Name, Birthday) VALUES ( 1, 'd9cfApqFe', '1999-11-25');
    -

    Result Analysis

    -

    Generating a chart.html file to visualize

    +

    Generating a chart.html file visualazing the following metric per benchmark:

      -
    • average amount of microseconds (μs) per benchmark (the lower the better)
    • -
    • operations per second (the higher the better)
    • -
    • microseconds per operation (the lower the better)
    • +
    • arithMean (μs)
      +Average execution time microseconds calculated using the aithmetic mean.
    • +
    • geoMean (μs)
      +Average execution time microseconds calculated using the geometric mean.
    • +
    • ops/s
      +Operations per second which equals executions divided by total (μs).
    • +
    • μs/op
      +Microseconds per operation which equals total (μs) divided by executions.
    -

    1 second (s) = 1'000'0000 microseconds (μs)
    -
    1 second (s) = 1'000'0000 microseconds (μs)
    -
    -
    +
    +

    Showcase employees

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    PartBenchmarkTasks
    0initializeDrop all possibly existing data and recreate the root node called "BigBoss"
    1insert_employeeInserts further nodes that are connected to randomly chosen existing nodes. The number of iterations equals 100% of the specified multiplicity.
    2select_before_indexSubsequent query all existing nodes and return the node itself together with all its connected nodes (i.e. its subordinate employees). No index exists at this stage. The number of iterations equals 100% of the specified multiplicity.
    3create_indexCreating a so-called BTREE index on the entity's relationship indicator (i.e. foreign key in relational DBMS, resp. relationship itself in graph-based DBMS).
    4clear_cachAll cached data is discarded.
    5select_after_indexThe identical querying tasks as in Part 2 is repeated.
    6cleanComplete removal of existing data and index information.
    +
    +
    +

    Showcase Results (1/3)

    +

    +
    +
    1 second (s) = 1'000'0000 microseconds (μs)
    +;background-color:white;background-image:none;" data-size="16:9"> +

    Showcase Results (2/3)

    +

    -
    +

    Showcase Results (3/3)

    +

    +
    +
    -

    Conclusion & Future Work

    +

    Conclusion

    +
      +
    • godbbench is a broadly employable tool for automated DB benchmarks
    • +
    • It is difficult to fairly compare fundamentally different DBMS paradigms
    • +
    • Showcase revealed the superiority of MySQL & PostgreSQL over Neo4j
      +in the given scenario
    • +
    +

    Future Work

      -
    • todo
    • +
    • Implementation of further database adaptors
    • +
    • Facility of multi-connection simulation
    • +
    • Creation of more sophisticated custom scripts
    -
    https://doi.org/10.1007/978-3-642-59412-0_16
  • Elmasri, R., & Navathe, S. (2011). Fundamentals of Database Systems (6th ed). Addison-Wesley.
  • Fleming, P. J., & Wallace, J. J. (1986). How not to lie with statistics: The correct way to summarize benchmark results. Communications of the ACM, 29(3), 218–221. https://doi.org/10.1145/5666.5673
  • @@ -1375,11 +1494,11 @@

    References

  • Needham, M., & Hodler, A. E. (2019). Graph Algorithms: Practical Examples in Apache Spark and Neo4j (First edition). O’Reilly Media.
  • Peixoto, T. P. (n.d.). What is graph-tool? Graph-Tool. Retrieved 20 March 2022, from https://graph-tool.skewed.de/
  • Robinson, I., Webber, J., & Eifrem, E. (2015). Graph Databases: New Opportunities for Connected Data.
  • -
  • Scalzo, B. (2018). Database Benchmarking and Stress Testing: An Evidence-Based Approach to Decisions on Architecture and Technology. Springer Science+Business Media, LLC.
  • Stopford, B. (2012, August 17). Thinking in Graphs: Neo4J. http://www.benstopford.com/2012/08/17/thinking-in-graphs-neo4j/
  • +
  • Turner-Trauring, I. (2021, May 12). Docker can slow down your code and distort your benchmarks. Python=>Speed. https://pythonspeed.com/articles/docker-performance-overhead/
  • -
    +![bg 95% drop-shadow](./assets/charts.png) + +---- + -![bg 95% ](./assets/chartbar.png) +# Showcase `employees` + +Part | Benchmark | Tasks +:----|:-----------|:---------------- +0 | `initialize` | Drop all possibly existing data and recreate the root node called "BigBoss" +1 |`insert_employee` | Inserts further nodes that are connected to randomly chosen existing nodes. The number of iterations equals 100% of the specified multiplicity. +2 |`select_before_index` | Subsequent query all existing nodes and return the node itself together with all its connected nodes (i.e. its subordinate employees). No index exists at this stage. The number of iterations equals 100% of the specified multiplicity. +3 |`create_index` | Creating a so-called *BTREE* index on the entity's relationship indicator (i.e. foreign key in relational DBMS, resp. relationship itself in graph-based DBMS). +4 | `clear_cach` | All cached data is discarded. +5 | `select_after_index` | The identical querying tasks as in Part 2 is repeated. +6 | `clean` | Complete removal of existing data and index information. ---- -![bg 95% ](./assets/chartline.png) +# Showcase Results (1/3) + +![](./assets/showcase_insert.png) ---- - +# Showcase Results (2/3) -# Conclusion & Future Work +![](./assets/showcase_selectbefore.png) -- todo +---- + +# Showcase Results (3/3) + +![](./assets/showcase_selectafter.png) + +---- + +# Conclusion + +- `godbbench` is a broadly employable tool for automated DB benchmarks +- It is difficult to fairly compare fundamentally different DBMS paradigms +- Showcase revealed the superiority of MySQL & PostgreSQL over Neo4j +in the given scenario + +# Future Work +- Implementation of further database adaptors +- Facility of multi-connection simulation +- Creation of more sophisticated custom scripts ---- @@ -339,7 +381,6 @@ Generating a `chart.html` file to visualize - Bechberger, D., & Perryman, J. (2020). Graph databases in Action: Examples in Gremlin. Manning. - Bush, J. (2020). Learn SQL Database Programming: Query and manipulate databases from popular relational database servers using SQL. -- Chauhan, C., & Kumar, D. (2017). PostgreSQL High Performance Cookbook: Mastering query optimization, database monitoring, and performance-tuning for PostgreSQL. Packt Publishing. - Codd, E. F. (2002). A Relational Model of Data for Large Shared Data Banks. In M. Broy & E. Denert (Eds.), Software Pioneers (pp. 263–294). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-59412-0_16 - Elmasri, R., & Navathe, S. (2011). Fundamentals of Database Systems (6th ed). Addison-Wesley. - Fleming, P. J., & Wallace, J. J. (1986). How not to lie with statistics: The correct way to summarize benchmark results. Communications of the ACM, 29(3), 218–221. https://doi.org/10.1145/5666.5673 @@ -349,8 +390,9 @@ Generating a `chart.html` file to visualize - Needham, M., & Hodler, A. E. (2019). Graph Algorithms: Practical Examples in Apache Spark and Neo4j (First edition). O’Reilly Media. - Peixoto, T. P. (n.d.). What is graph-tool? Graph-Tool. Retrieved 20 March 2022, from https://graph-tool.skewed.de/ - Robinson, I., Webber, J., & Eifrem, E. (2015). Graph Databases: New Opportunities for Connected Data. -- Scalzo, B. (2018). Database Benchmarking and Stress Testing: An Evidence-Based Approach to Decisions on Architecture and Technology. Springer Science+Business Media, LLC. - Stopford, B. (2012, August 17). Thinking in Graphs: Neo4J. http://www.benstopford.com/2012/08/17/thinking-in-graphs-neo4j/ +- Turner-Trauring, I. (2021, May 12). Docker can slow down your code and distort your benchmarks. 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