Commit 5d60482d authored by Azat Khuziyakhmetov's avatar Azat Khuziyakhmetov
Browse files

edited the documentation for recommendation system

parent a4ec59c0
......@@ -62,7 +62,9 @@ The optimal CPU usages depends on the amount of cores requested. When the number
![node_cpu_usage_max](img/node_cpu_usage_max.svg)
*The `LOW` values are highlighted*
*The corresponding values are highlighted*
`LOW` is red. `NORM` is green and `HIGH` is orange.
## node_cpu_usage_min
......@@ -95,7 +97,9 @@ Similar to the attribute `node_cpu_usage_max` but indicates the minimum of `cpu_
![node_cpu_usage_max](img/node_cpu_usage_max.svg)
*The `LOW` values are highlighted*
*The corresponding values are highlighted*
`LOW` is red. `NORM` is green and `HIGH` is orange.
## cpu_usage_total_max
......@@ -170,3 +174,17 @@ It is `True` if the node has a high load during the interval `D`.
If during the interval `D` (300 seconds) consequent measurements of `load1` on the node exceeds the amount of cores the node has, then the value is `True`.
`False` otherwise.
## mem_swap_used
It is `True` if there is a node where swap memory was used.
**Values**:
`True` - if swap was used on one of the nodes
`False` - otherwise
**Calculation**:
For every node check if `mem_swap_max` value is non zero. If it is non zero for any node, then set the attribute to `True`, otherwise `False`.
This diff is collapsed.
......@@ -41,14 +41,20 @@ class NodeData:
seq_cpu_usage = None
seq_load_avg = None
seq_load_max = None
seq_ib_rcv_max = None
seq_ib_xmit_max = None
proc = None
alloc_cu = None
ib_rcv_max = None
ib_xmit_max = None
def __init__(self):
self.proc = ProcData()
self.seq_load_avg = SeqVals()
self.seq_load_max = SeqVals()
self.seq_cpu_usage = SeqVals()
self.seq_ib_rcv_max = SeqVals()
self.seq_ib_xmit_max = SeqVals()
class SeqVals:
delta = None
......
......@@ -2,7 +2,7 @@ import matplotlib.pyplot as plt
import numpy as np
XLIM = 64
YLIM = 100
YLIM = 120
x_const = 8
tx = np.arange(1.0, XLIM)
......@@ -15,16 +15,22 @@ plt.grid(True, which="both", linestyle='--')
# lines
y_is_50 = tx*0 + 50
y_is_80 = tx*0 + 80
y_is_100 = tx*0 + 100
y_lim = tx*0 + YLIM
x_is_const = [x_const, x_const], [0, YLIM]
# plot the lines
plt.plot(tx, y_is_50, label="U=50%")
plt.plot(tx, y_is_80, label="U=80%")
plt.plot(tx, y_is_100, label="U=100%")
plt.plot(*x_is_const, label="R=8")
# highlight the area
plt.fill_between(tx, y_is_50, where=tx <= x_const, color='red', alpha=0.3)
plt.fill_between(tx, y_is_80, where=tx >= x_const, color='red', alpha=0.3)
plt.fill_between(tx, y_is_100, y_lim, color='orange', alpha=0.3)
plt.fill_between(tx, y_is_50, y_is_100, where=tx <= x_const, color='green', alpha=0.3)
plt.fill_between(tx, y_is_80, y_is_100, where=tx >= x_const, color='green', alpha=0.3)
plt.legend(loc='lower right')
......
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