many updates and fixes
diff --git a/wally/console_report.py b/wally/console_report.py
index 3733de1..ac54965 100644
--- a/wally/console_report.py
+++ b/wally/console_report.py
@@ -1,3 +1,6 @@
+import logging
+
+
import numpy
from cephlib.common import float2str
@@ -9,6 +12,11 @@
from .suits.io.fio import FioTest
from .statistic import calc_norm_stat_props, calc_histo_stat_props
from .suits.io.fio_hist import get_lat_vals
+from .data_selectors import get_aggregated
+
+
+logger = logging.getLogger("wally")
+
class ConsoleReportStage(Stage):
@@ -19,22 +27,26 @@
for suite in rstorage.iter_suite(FioTest.name):
table = texttable.Texttable(max_width=200)
- table.header(["Description", "IOPS ~ Dev", "BW, MiBps", 'Skew/Kurt', 'lat med, ms', 'lat 95, ms'])
- table.set_cols_align(('l', 'r', 'r', 'r', 'r', 'r'))
+ tbl = rstorage.get_txt_report(suite)
+ if tbl is None:
+ table.header(["Description", "IOPS ~ Dev", "BW, MiBps", 'Skew/Kurt', 'lat med, ms', 'lat 95, ms'])
+ table.set_cols_align(('l', 'r', 'r', 'r', 'r', 'r'))
- for job in sorted(rstorage.iter_job(suite), key=lambda job: job.params):
- bw_ts, = list(rstorage.iter_ts(suite, job, metric='bw'))
- props = calc_norm_stat_props(bw_ts)
- avg_iops = props.average // job.params.params['bsize']
- iops_dev = props.deviation // job.params.params['bsize']
+ for job in sorted(rstorage.iter_job(suite), key=lambda job: job.params):
+ bw_ts = get_aggregated(rstorage, suite, job, metric='bw')
+ props = calc_norm_stat_props(bw_ts)
+ avg_iops = props.average // job.params.params['bsize']
+ iops_dev = props.deviation // job.params.params['bsize']
- lat_ts, = list(rstorage.iter_ts(suite, job, metric='lat'))
- bins_edges = numpy.array(get_lat_vals(lat_ts.data.shape[1]), dtype='float32') / 1000 # convert us to ms
- lat_props = calc_histo_stat_props(lat_ts, bins_edges)
- table.add_row([job.params.summary,
- "{} ~ {}".format(float2str(avg_iops), float2str(iops_dev)),
- float2str(props.average / 1024), # Ki -> Mi
- "{}/{}".format(float2str(props.skew), float2str(props.kurt)),
- float2str(lat_props.perc_50), float2str(lat_props.perc_95)])
+ lat_ts = get_aggregated(rstorage, suite, job, metric='lat')
+ bins_edges = numpy.array(get_lat_vals(lat_ts.data.shape[1]), dtype='float32') / 1000 # convert us to ms
+ lat_props = calc_histo_stat_props(lat_ts, bins_edges)
+ table.add_row([job.params.summary,
+ "{} ~ {}".format(float2str(avg_iops), float2str(iops_dev)),
+ float2str(props.average / 1024), # Ki -> Mi
+ "{}/{}".format(float2str(props.skew), float2str(props.kurt)),
+ float2str(lat_props.perc_50), float2str(lat_props.perc_95)])
- print(table.draw())
+ tbl = table.draw()
+ rstorage.put_txt_report(suite, tbl)
+ print(tbl)