anchor.diff:  == Benchmark Configuration
   
   
  -[[benchmarker.addDependency]]
  -=== Add Dependency On `optaplanner-benchmark`
  +[[addADependencyOnBenchmarkJar]]
  +=== Add a Dependency on `optaplanner-benchmark`
   
   The benchmarker is in a separate artifact called ``optaplanner-benchmark``.
   
  -If you use Maven, add a dependency in your [path]_pom.xml_ file:
  +If you use Maven, add a dependency in your `pom.xml` file:
   
   [source,xml,options="nowrap"]
   ----
  
positive.code:   <inheritedSolverBenchmark>
      <problemBenchmarks>
        ...
        <inputSolutionFile>data/nqueens/unsolved/32queens.xml</inputSolutionFile>
        <inputSolutionFile>data/nqueens/unsolved/64queens.xml</inputSolutionFile>
      </problemBenchmarks>
      <solver>
        ...<!-- Common solver configuration -->
  
negative.code: 
  
  [[readingAnInputSolutionFromADatabase]]
  ==== Reading An Input Solution From A Database (Or Other Storage)
  
  There are two options if your dataset is in a relational database or another type of repository:
  
  * Extract the datasets from the database and serialize them to a local file (for example as XML with `XStreamSolutionFileIO` if XML isn't too verbose).
  Then use those files an `<inputSolutionFile>` elements.
  ** The benchmarks is now more reliable because they run offline.
  ** Each dataset is only loaded just in time.
  * Load all the datasets in advance and pass them to the `buildPlannerBenchmark()` method:
  +
  [source,java,options="nowrap"]
  ----
          PlannerBenchmark plannerBenchmark = benchmarkFactory.buildPlannerBenchmark(dataset1, dataset2, dataset3);
  ----
  
  
  [[warmingUpTheHotSpotCompiler]]
  