Overview
This documentation contains
an example of how to perform a TPC-H-like Benchmark from a command line
a list of the key features
an example of the basic usage in Python
an illustration of the concepts
an illustration of the evaluations
a description of the options and configurations
some use-cases and test scenarios
examples of how to use the interactive inspector
examples of how to use the interactive dashboard
In Python we basically use the benchmarker as follows:
from dbmsbenchmarker import *
# tell the benchmarker where to find the config files
configfolder = "./config"
# tell the benchmarker where to put results
resultfolder = "/results"
# get a benchmarker object
dbms = benchmarker.benchmarker(result_path=resultfolder)
dbms.getConfig(configfolder)
# tell the benchmarker which fixed evaluations we want to have (line plot and box plot per query)
dbms.reporter.append(benchmarker.reporter.ploter(dbms))
dbms.reporter.append(benchmarker.reporter.boxploter(dbms))
# start benchmarking
dbms.runBenchmarks()
# print collected errors
dbms.printErrors()
# get unique code of this experiment
code = dbms.code
# generate inspection object
evaluate = inspector.inspector(resultfolder)
# load this experiment into inspector
evaluate.load_experiment(code)
# get latency of run (measures and statistics) of first query
df_measure, df_statistics = evaluate.get_measures_and_statistics(1, type='latency', name='run')
There also is a command line interface for running benchmarks and generation of reports.