V0.12.1 (#93)

* Prepare next release

* Inspector: workload dict without metrics and reporting

* Docs: JOSS intro

dbmsbenchmarker/inspector.py

@@ -25,6 +25,7 @@
 from colour import Color
 from numpy import nan
 from datetime import datetime, timezone
+import copy
 
 from dbmsbenchmarker import benchmarker, tools, evaluator, monitor
 
@@ -144,6 +145,11 @@ def load_experiment(self, code, anonymize=None, load=True):
         self.benchmarks.computeTimerRun()
         self.benchmarks.computeTimerSession()
         self.e = evaluator.evaluator(self.benchmarks, load=load, force=True)
+        self.workload = copy.deepcopy(self.e.evaluation['general'])
+        # remove metrics
+        del(self.workload['loadingmetrics'])
+        del(self.workload['streamingmetrics'])
+        del(self.workload['reporting'])
     def get_experiment_list_queries(self):
         # list of successful queries
         return self.benchmarks.listQueries()
@@ -260,12 +266,7 @@ def get_experiment_query_properties(self, numQuery=None):
             return self.e.evaluation['query']
     def get_experiment_workload_properties(self):
         # dict of workload properties
-        workload = self.e.evaluation['general']
-        # remove metrics
-        del(workload['loadingmetrics'])
-        del(workload['streamingmetrics'])
-        del(workload['reporting'])
-        return workload
+        return self.workload
     #def get_measures(self, numQuery, timer, warmup=0, cooldown=0):
     def get_timer(self, numQuery, timer, warmup=0, cooldown=0):
         # dataframe of dbms x measures

paper.md

@@ -34,7 +34,8 @@ See the [homepage](https://github.com/Beuth-Erdelt/DBMS-Benchmarker) and the [do
 
 # Statement of Need
 
-There are a variety of (relational) database management systems (DBMS) and a lot of products.
+Benchmarking of database management systems (DBMS) is an active research area.
+There are a variety of DBMS and a lot of products.
 The types thereof can be divided into for example row-wise, column-wise, in-memory, distributed and GPU-enhanced. 
 All of these products have unique characteristics, special use cases, advantages and disadvantages and their justification.
 In order to be able to verify and ensure the performance measurement, we want to be able to create and repeat benchmarking scenarios.

setup.py

@@ -8,7 +8,7 @@
 
 setuptools.setup(
     name="dbmsbenchmarker",
-    version="0.11.22",
+    version="0.12.1",
     author="Patrick Erdelt",
     author_email="perdelt@beuth-hochschule.de",
     description="DBMS-Benchmarker is a Python-based application-level blackbox benchmark tool for Database Management Systems (DBMS). It connects to a given list of DBMS (via JDBC) and runs a given list of parametrized and randomized (SQL) benchmark queries. Evaluations are available via Python interface, in reports and at an interactive multi-dimensional dashboard.",