Inspector
See the rendered example for more details.
Debug Tool
There is a debug tool, that helps to analyze result folders: python evaluate.py -h
usage: evaluate.py [-h] [-r RESULT_FOLDER] [-e EXPERIMENT] [-q QUERY] [-c CONNECTION] [-n NUM_RUN] [-d] [-rt] {resultsets,errors,warnings,query}
A debug tool for DBMSBenchmarker. It helps to analyze a result folder. It depends on the evaluation cube, so that cube must have been created before.
positional arguments:
{resultsets,errors,warnings,query}
show debug infos about which part of the outcome
optional arguments:
-h, --help show this help message and exit
-r RESULT_FOLDER, --result-folder RESULT_FOLDER
folder for storing benchmark result files, default is given by timestamp
-e EXPERIMENT, --experiment EXPERIMENT
code of experiment
-q QUERY, --query QUERY
number of query to inspect
-c CONNECTION, --connection CONNECTION
name of DBMS to inspect
-n NUM_RUN, --num-run NUM_RUN
number of run to inspect
-d, --diff show differences in result sets
-rt, --remove-titles remove titles when comparing result sets
It depends on the evaluation cube. In case, it can be generated by dbmsbenchmarker -e yes -r 1647993954 read
for example for experiment 1647993954
.
Show Queries
We can take a look at the actual queries that have been sent: python evaluate.py -e 1647993954 -q 1 -n 0 query
This shows the query string for query number 2, first run.
Show Result Sets
We can take a look at the actual queries that have been sent: python evaluate.py -e 1647993954 -q 2 resultsets
This shows the query string for query number 2.
Show Errors
We can take a look at the actual queries that have been sent: python evaluate.py -e 1647993954 errors
Show Warnings
We can take a look at the actual queries that have been sent: python evaluate.py -e 1647993954 warnings