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kyle-haileykyle-hailey
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made throughput log scale
1 parent fb13b80 commit e6502b7

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+69
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‎dtv.r‎

Lines changed: 36 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,36 @@
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m <- NULL
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m <- matrix(c(
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"randread", 1, "8K", 1.319, 5.915, 0.3, 503, 6.5, 168 , 0, 0, 0, 0, 2, 3,22,64, 3, 1, 0, 0, 0, 0, 0, 0,10.560,24.448,27.520,35.584,48.896,325.632
4+
,"randread", 8, "8K", 11.806, 5.289, 0.4, 600, 5.8, 1511 , 0, 0, 0, 0, 6, 4,25,58, 4, 0, 0, 0, 0, 0, 0, 0,10.048,16.192,20.352,29.312,47.360,226.304
5+
,"randread", 16, "8K", 19.357, 6.452, 0.4, 654, 7.3, 2477 , 0, 0, 0, 0, 1, 3,19,62,11, 0, 0, 0, 0, 0, 0, 0,12.736,19.072,22.144,30.848,50.432,436.224
6+
,"randread", 32, "8K", 31.492, 7.923, 0.2, 522, 6.8, 4031 , 0, 0, 0, 0, 0, 1,13,62,19, 2, 0, 0, 0, 0, 0, 0,16.768,25.216,29.056,44.800,70.144,313.344
7+
,"randread", 64, "8K", 37.209, 13.420, 0.4, 665, 31.1, 4762 , 0, 0, 0, 0, 0, 0, 9,58,21, 6, 1, 1, 0, 0, 0, 0,32.000,145.000,231.000,449.000,519.000,627.000
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, "read", 1, "8K", 8.523, 0.913, 0.3, 645, 2.7, 1091 , 0, 0, 0,16,66,13, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0,1.272,5.600,7.712,22.144,25.472,38.144
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, "read", 1, "32K", 17.193, 1.814, 0.5, 555, 3.4, 550 , 0, 0, 0, 0,42,44, 4, 7, 1, 0, 0, 0, 0, 0, 0, 0,6.240,14.016,21.632,28.544,30.848,51.456
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, "read", 1,"128K", 37.552, 3.320, 1.0, 549, 6.3, 300 , 0, 0, 0, 0, 0,48,37, 8, 4, 1, 0, 0, 0, 0, 0, 0,10.560,21.120,25.984,36.096,44.800,296.960
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, "read", 1, "1M", 87.165, 11.470, 4.0, 582, 10.4, 87 , 0, 0, 0, 0, 0, 0, 0,61,23,14, 0, 0, 0, 0, 0, 0,27.000,38.000,43.000,63.000,155.000,461.000
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, "read", 8, "1M", 269.019, 14.860, 4.0, 594, 15.0, 269 , 0, 0, 0, 0, 0, 0, 0,36,47,14, 1, 0, 0, 0, 0, 0,32.000,62.000,72.000,109.000,400.000,553.000
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, "read", 16, "1M", 376.654, 21.210, 5.0, 588, 15.8, 376 , 0, 0, 0, 0, 0, 0, 0, 3,59,33, 2, 0, 0, 0, 0, 0,42.000,91.000,100.000,141.000,174.000,478.000
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, "read", 32, "1M", 417.548, 38.240, 5.0, 636, 32.8, 417 , 0, 0, 0, 0, 0, 0, 0, 0,21,58,13, 4, 0, 0, 0, 0,99.000,151.000,182.000,465.000,523.000,586.000
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, "read", 64, "1M", 399.669, 79.930, 5.0, 1406, 106.0, 399 , 0, 0, 0, 0, 0, 0, 0, 0,10,43,25,15, 3, 1, 0, 0,255.000,594.000,676.000,1057.000,1205.000,1270.000
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, "write", 1, "1K", 0.757, 1.287, 0.5, 536, 1.7, 775 , 0, 0, 0, 0,48,39,10, 0, 0, 0, 0, 0, 0, 0, 0, 0,2.672,4.256,7.456,19.072,20.352,31.104
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, "write", 1, "8K", 6.802, 1.145, 0.5, 400, 1.8, 870 , 0, 0, 0, 0,50,46, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,1.512,3.184,6.176,18.304,20.096,79.360
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, "write", 1,"128K", 41.685, 2.990, 1.0, 373, 7.3, 333 , 0, 0, 0, 0, 0,25,66, 5, 1, 0, 0, 0, 0, 0, 0, 0,7.008,14.656,22.912,120.320,183.296,284.672
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, "write", 4, "1K", 0.947, 2.057, 0.5, 162, 1.4, 970 , 0, 0, 0, 0, 7,47,42, 1, 0, 0, 0, 0, 0, 0, 0, 0,3.280,5.024,7.328,19.584,20.608,33.536
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, "write", 4, "8K", 7.068, 2.206, 0.6, 156, 2.1, 904 , 0, 0, 0, 0, 0,41,56, 1, 0, 0, 0, 0, 0, 0, 0, 0,2.832,4.320,5.408,21.120,39.680,93.696
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, "write", 4,"128K", 49.128, 5.080, 1.0, 494, 11.4, 393 , 0, 0, 0, 0, 0, 0,66,28, 3, 0, 0, 0, 0, 0, 0, 0,10.000,21.000,36.000,204.000,260.000,420.000
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, "write", 16, "1K", 3.245, 2.402, 0.5, 185, 1.9, 3323 , 0, 0, 0, 0, 0,36,58, 3, 0, 0, 0, 0, 0, 0, 0, 0,3.792,7.648,9.408,21.888,35.072,50.944
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, "write", 16, "8K", 20.884, 2.987, 0.7, 311, 4.5, 2673 , 0, 0, 0, 0, 0, 7,87, 4, 0, 0, 0, 0, 0, 0, 0, 0,4.448,9.664,16.064,73.216,115.200,166.912
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, "write", 16,"128K", 84.580, 11.800, 2.0, 887, 28.7, 676 , 0, 0, 0, 0, 0, 0, 0,76,19, 3, 0, 0, 0, 0, 0, 0,20.000,67.000,174.000,498.000,603.000,750.000
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),nrow=31)
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tm <- t(m)
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m <-tm
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colnames <- c("name","users","bs","MB","lat","min","max","std","iops"
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, "us50","us100","us250","us500","ms1","ms2","ms4","ms10","ms20"
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, "ms50","ms100","ms250","ms500","s1","s2","s5"
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,"p95_00", "p99_00", "p99_50", "p99_90", "p99_95", "p99_99"
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)
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colnames(m)=colnames
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m <- data.frame(m)
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testtype <- "directtv"
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‎fiop.r‎

Lines changed: 33 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -254,9 +254,13 @@ graphit <- function(
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# which is bad, ie the throughput actually decreases
255255
# negative values are where the latency actual got faster
256256
# at higher x values
257+
258+
# intialize the vectors to NA values but correct length
257259
scaling <- rep(NA,(length(lat)-1) )
260+
scalecolor <- rep(NA,(length(lat)-1) )
258261
for ( i in 1:(length(lat)-1) ) {
259262
cat("lat_a ",lat[i],"lat_b",lat[i+1],"\n")
263+
cat("scalex_a ",scalingx[i],"scalex_b",scalingx[i+1],"\n")
260264
lat_f = lat[i+1]/lat[i]
261265
sca_f = scalingx[i+1]/scalingx[i]
262266
cat("lat_f[",i,"]=",lat_f,"\n")
@@ -266,7 +270,15 @@ graphit <- function(
266270
# want to graphically exagerate the higher values and dampen the smaller values
267271
scaling[i] <- 2^(scalei*10)/1024 # > 1 means throughput is going down 2^(1*10)
268272
cat("scalei exp",scaling[i],"\n")
269-
if ( lat[i] > lat[i+1] ) { scaling[i] <- scaling[i]*(-1) }
273+
scalecolor[i] <- "#F8CFCF" # regular red (light)
274+
if ( lat[i] > lat[i+1] ) {
275+
scaling[i] <- scaling[i]*(-1)
276+
scalecolor[i] <- "#CBCDFF" # light blue
277+
}
278+
# not quite sure how this happens, but in some cases
279+
# latency goes up by a smaller factor the users or block size
280+
# yet throughput goes down, in this case
281+
if ( MB[i] > MB[i+1] ) { scalecolor[i] <- "#DFA2A2" } # dark red
270282
}
271283

272284
#
@@ -302,12 +314,19 @@ graphit <- function(
302314
#
303315
# MB/s BARS in bottom graph
304316
#
305-
MBbars <- t(t(fhist)*MB)
317+
logMB <- log(MB+1)
318+
# MBbars <- t(t(fhist)*MB)
319+
MBbars <- t(t(fhist)*logMB)
306320
colnames(MBbars) = col_lables
307321
# B L T R
308322
par(mar=c(2, 4, 0, 4))
309-
op <- barplot(MBbars,col=colors,ylab="MB/s",border=NA,space=1, ylim=c(0,100),xlim=c(1,2*length(lat)+1))
310-
text(op, 0,round(MB),adj=c(0.2,-1.4),col="gray20")
323+
op <- barplot(MBbars,col=colors,ylab="MB/s",border=NA,space=1, ylim=c(0,log(1200)),xlim=c(1,2*length(lat)+1),
324+
yaxt = "n" )
325+
text(op, pmin((logMB),log(400)),round(MB),adj=c(0.2,-.2),col="gray20")
326+
327+
ypts <- c( log(2), log(11), log(101), log(1001));
328+
ylbs <- c( "1", "10", "100", "1000");
329+
axis(2,at=ypts, labels=ylbs)
311330

312331
# j=2
313332
# for ( i in scaling ) {
@@ -365,7 +384,7 @@ graphit <- function(
365384
lwd = 1,
366385
bty = "l",
367386
xlim = c(xminwidth,xmaxwidth),
368-
ylim = c(ymin,ymax),
387+
ylim = c(ymin,ymax*1.1),
369388
ylab = "" ,
370389
xlab = "",
371390
log = "",
@@ -377,15 +396,20 @@ graphit <- function(
377396
#
378397
# SCALING BARs
379398
#
380-
for ( scale in scaling ) {
399+
# for ( scale in scaling ) {
400+
# }
401+
for ( i in 1:(length(lat)-1) ) {
402+
scale <- scaling[i]
381403
col = "#F8CFCF" # regular red (light)
382404
if ( scale < 0 ) {
383405
col = "#CBCDFF" # light blue
384-
# scale= scale*-1
406+
scale= scale*-1
385407
}
386408
if ( scale > 1 ) { # dark red
387409
col = "#DFA2A2"
388410
}
411+
col=scalecolor[i]
412+
cat("scalecolor ", col," i=", i ,"\n")
389413
# create a polygon, a rectangle,
390414
# start half size bar in middle of line
391415
x1=j+.5
@@ -399,7 +423,7 @@ graphit <- function(
399423
polygon(c(x1,x2,x2,x1),c(y1,y1,y2,y2), col=col,border=NA)
400424
# put the text value of scale just above ymin, ie just above 0
401425
# the bottom of the bar
402-
text(c(x1+.5,0), (ymin+0.1*ymax),round(scale,2),adj=c(0,0),col="red")
426+
text(c(x1+.5,0), (ymin+0.1*ymax),round(scale,2),adj=c(0,0),col="gray60")
403427
print(i)
404428
j=j+1
405429
}
@@ -426,7 +450,7 @@ graphit <- function(
426450
#
427451
# ms10 SUCCESS overlay on top graph ( latency lines )
428452
#
429-
op <- barplot(ms10, col=c("#E0E0FF", "#F0FFE0", "#FFF6A0"),ylim =c(0,1), xlab="", ylab="",border=NA,space=0,yaxt="n",xaxt="n")
453+
op <- barplot(ms10, col=c("#C6D4F8", "#C9FACF", "#FFF6A0"),ylim =c(0,1), xlab="", ylab="",border=NA,space=0,yaxt="n",xaxt="n")
430454
par(new = TRUE )
431455

432456
# AVERGE get's ploted twice because there has to be something to initialize the graph

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