diff options
Diffstat (limited to 'storperf')
| -rw-r--r-- | storperf/utilities/data_treatment.py | 39 | ||||
| -rw-r--r-- | storperf/utilities/math.py | 27 | ||||
| -rw-r--r-- | storperf/utilities/steady_state.py | 45 |
3 files changed, 109 insertions, 2 deletions
diff --git a/storperf/utilities/data_treatment.py b/storperf/utilities/data_treatment.py new file mode 100644 index 0000000..2368fd9 --- /dev/null +++ b/storperf/utilities/data_treatment.py @@ -0,0 +1,39 @@ +############################################################################## +# Copyright (c) 2016 CENGN and others. +# +# All rights reserved. This program and the accompanying materials +# are made available under the terms of the Apache License, Version 2.0 +# which accompanies this distribution, and is available at +# http://www.apache.org/licenses/LICENSE-2.0 +############################################################################## + + +def data_treatment(data_series): + """ + This function aims at performing any necessary pre treatment on the + data_series passed to the steady_state function before being passed + under to the different math utilities (slope, range and average) + so the data can match the requirements of each algorithm. + The function returns a dictionary composed of three values that can be + accessed with the following keys : 'slope_data', 'range_data' and + 'average_data'. + The data_series is currently assumed to follow the pattern : + [[x1,y1], [x2,y2], ..., [xm,ym]]. If this pattern were to change, or + the input data pattern of one of the math module, this data_treatment + function should be the only part of the Steady State detection module + that would need to be modified too. + """ + + x_values = [] + y_values = [] + for l in data_series: + x_values.append(l[0]) + y_values.append(l[1]) + + treated_data = { + 'slope_data': data_series, # No treatment necessary so far + 'range_data': y_values, # The y_values only + 'average_data': y_values + } + + return treated_data diff --git a/storperf/utilities/math.py b/storperf/utilities/math.py index 031fc3e..a11ec19 100644 --- a/storperf/utilities/math.py +++ b/storperf/utilities/math.py @@ -25,7 +25,7 @@ def slope(data_series): # In the particular case of an empty data series if len(data_series) == 0: - beta2 = 0 + beta2 = None else: # The general case m = len(data_series) @@ -78,7 +78,7 @@ def range_value(data_series): # In the particular case of an empty data series if len(data_series) == 0: - range_value = 0 + range_value = None else: # The general case max_value = max(data_series) @@ -86,3 +86,26 @@ def range_value(data_series): range_value = max_value - min_value return range_value + + +def average(data_series): + """ + This function seeks to calculate the average value of the data series + given a series following the pattern : [y1, y2, y3, ..., ym]. + If this data pattern were to change, the data_treatment function + should be adjusted to ensure compatibility with the rest of the + Steady State Dectection module. + The function returns a float number corresponding to the average of the yi. + """ + m = len(data_series) + + if m == 0: # In the particular case of an empty data series + average = None + + else: + data_sum = 0 + for value in data_series: + data_sum += value + average = data_sum / float(m) + + return average diff --git a/storperf/utilities/steady_state.py b/storperf/utilities/steady_state.py new file mode 100644 index 0000000..8bfcb93 --- /dev/null +++ b/storperf/utilities/steady_state.py @@ -0,0 +1,45 @@ +############################################################################## +# Copyright (c) 2016 CENGN and others. +# +# All rights reserved. This program and the accompanying materials +# are made available under the terms of the Apache License, Version 2.0 +# which accompanies this distribution, and is available at +# http://www.apache.org/licenses/LICENSE-2.0 +############################################################################## +from storperf.utilities import data_treatment as DataTreatment +from storperf.utilities import math as math + + +def steady_state(data_series): + """ + This function seeks to detect steady state given on a measurement + window given the data series of that measurement window following + the pattern : [[x1,y1], [x2,y2], ..., [xm,ym]]. m represents the number + of points recorded in the measurement window, x which represents the + time, and y which represents the Volume performance variable being + tested e.g. IOPS, latency... + The function returns a boolean describing wether or not steady state + has been reached with the data that is passed to it. + """ + + # Pre conditioning the data to match the algorithms + treated_data = DataTreatment.data_treatment(data_series) + + # Calculating useful values invoking dedicated functions + slope_value = math.slope(treated_data['slope_data']) + range_value = math.range_value(treated_data['range_data']) + average_value = math.average(treated_data['average_data']) + + if (slope_value is not None and range_value is not None and + average_value is not None): + # Verification of the Steady State conditions following the SNIA + # definition + range_condition = range_value < 0.20 * abs(average_value) + slope_condition = slope_value < 0.10 * abs(average_value) + + steady_state = range_condition and slope_condition + + else: + steady_state = False + + return steady_state |