log-ninja

A set of scripts I find useful when analysing log files. You might like to put them in your ~/bin folder.

Jump to: batch, distribution, field, fields, float, int, logs, median, percentiles, standarddeviation, total, uniqcount, urlencode / urldecode, variance.

## batch

batch will read a steam of input from STDIN and concatenate it (space separated) into a string, flushing it to STDOUT once per second. That means it can batch numerical output from a command in to a line per second with multiple values on it.

So this:

$ for (( i = 0; i <= 10 ; i++ )); do echo $i; sleep 0.2; done
0
1
2
3
4
5
6
7
8
9
10

becomes this:

$ for (( i = 0; i <= 10 ; i++ )); do echo $i; sleep 0.2; done | ./batch
0 1 2
4 5 6 7
9 10

Watch an example.

distribution

If you have the Perl library Time/HiRes.pm installed then you should look at using philovivero's Perl implementation, which is prettier and supports string values too (found looking at an old Stack Overflow post of mine).

See this blog post for more information about this script.

Briefly, use it like this:

Show distribution of earthquake magnitudes over the last 7 days:

$ curl http://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/all_month.csv --silent \
| \sed '1d' \
| cut -d, -f5 \
| ./distribution width=70 lines=30

Found 1154 records distributed in 58 distinct values between 0 and 6.1

     Value    Quant   %ile Histogram
     -----    -----   ---- ---------
      0.00        9   0.78 _____
      0.21       59   5.89 ________________________________
      0.42       78  12.65 __________________________________________
      0.63       66  18.37 ____________________________________
      0.84      119  28.68 _________________________________________________________________
      1.05      130  39.95 ______________________________________________________________________
      1.26      112  49.65 _____________________________________________________________
      1.47      104  58.67 ________________________________________________________
      1.68       87  66.20 _______________________________________________
      1.89      129  77.38 ______________________________________________________________________
      2.10       52  81.89 ____________________________
      2.31       28  84.32 ________________
      2.52       28  86.74 ________________
      2.73       14  87.95 ________
      2.94       13  89.08 _______
      3.16       17  90.55 __________
      3.37        6  91.07 ____
      3.58        8  91.77 _____
      3.79        1  91.85 _
      4.00        4  92.20 ___
      4.21        8  92.89 _____
      4.42       11  93.85 ______
      4.63       21  95.67 ____________
      4.84       25  97.83 ______________
      5.05       10  98.70 ______
      5.26        8  99.39 _____
      5.47        2  99.57 __
      5.68        1  99.65 _
      5.89        2  99.83 __
      6.10        2 100.00 __

```sh

Or how tall people are (in inches):

```sh
$ curl --silent http://socr.ucla.edu/docs/resources/SOCR_Data/SOCR_Data_Dinov_020108_HeightsWeights.html | \
grep -A 2 "<tr" | grep "<td x:num" | sed -e "s/^.*>\([0-9.]*\)<.*$/\1/" | ./distribution lines=30 width=70

Found 25000 records distributed in 20917 distinct values between 60.2784 and 75.1528

     Value    Quant   %ile Histogram
     -----    -----   ---- ---------
     60.28        2   0.01 _
     60.79        4   0.02 _
     61.30        3   0.04 _
     61.82       10   0.08 _
     62.33       59   0.31 __
     62.84       91   0.68 ___
     63.36      211   1.52 ______
     63.87      359   2.96 __________
     64.38      597   5.34 ________________
     64.89      874   8.84 _______________________
     65.41     1211  13.68 ________________________________
     65.92     1731  20.61 ______________________________________________
     66.43     2129  29.12 ________________________________________________________
     66.95     2444  38.90 _________________________________________________________________
     67.46     2637  49.45 ______________________________________________________________________
     67.97     2667  60.12 ______________________________________________________________________
     68.48     2508  70.15 __________________________________________________________________
     69.00     2134  78.68 _________________________________________________________
     69.51     1745  85.66 ______________________________________________
     70.02     1276  90.77 __________________________________
     70.54      960  94.61 __________________________
     71.05      621  97.09 _________________
     71.56      348  98.48 __________
     72.08      192  99.25 ______
     72.59       94  99.63 ___
     73.10       56  99.85 __
     73.61       19  99.93 _
     74.13       14  99.98 _
     74.64        3 100.00 _
     75.15        1 100.00 _

Or show the distribution of word length in your UNIX dictionary: (you can use this shorter words list if you don't have words)

$ cat /usr/share/dict/words | awk '{print length($1)}' | ./distribution width=70

Found 489040 records distributed in 35 distinct values between 1 and 45

     Value    Quant   %ile Histogram
     -----    -----   ---- ---------
      1.00       26   0.01 _
      2.00      290   0.06 _
      3.00     2017   0.48 ___
      4.00     7508   2.01 ________
      5.00    18148   5.72 ___________________
      6.00    35087  12.90 _____________________________________
      7.00    50877  23.30 _____________________________________________________
      8.00    64210  36.43 ___________________________________________________________________
      9.00    67754  50.29 ______________________________________________________________________
     10.00    64374  63.45 ___________________________________________________________________
     11.00    53736  74.44 ________________________________________________________
     12.00    41934  83.01 ____________________________________________
     13.00    30291  89.21 ________________________________
     14.00    20873  93.47 ______________________
     15.00    13512  96.24 ______________
     16.00     8427  97.96 _________
     17.00     4760  98.93 _____
     18.00     2624  99.47 ___
     19.00     1378  99.75 __
     20.00      630  99.88 _
     21.00      309  99.94 _
     22.00      134  99.97 _
     23.00       63  99.98 _
     24.00       35  99.99 _
     25.00       17  99.99 _
     26.00        2 100.00 _
     27.00        5 100.00 _
     28.00        3 100.00 _
     29.00        6 100.00 _
     30.00        2 100.00 _
     31.00        2 100.00 _
     32.00        1 100.00 _
     33.00        1 100.00 _
     34.00        2 100.00 _
     35.00        0 100.00
     36.00        0 100.00
     37.00        0 100.00
     38.00        0 100.00
     39.00        0 100.00
     40.00        0 100.00
     41.00        0 100.00
     42.00        0 100.00
     43.00        0 100.00
     44.00        0 100.00
     45.00        2 100.00 _

It's pneumonoultramicroscopicsilicovolcanoconiosis by the way, in case you were wondering. I thought you were.

You could cut out the outlier by selecting a window of values (i.e. min and max) like this:

$ cat /usr/share/dict/words | awk '{print length($1)}' | ./distribution width=80 min=1 max=35

There was a known bug with percentiles when a min or a max value was specified, but a rewrite has solved this.

You might also be interested in Spark - Holman's script which generates sparklines (more traditional bar charts minus the labels etc) on your command line from on a list of numbers.

field

Takes lines on STDIN and returns the specified field (delimited by whitespace).

$ echo "The quick brown fox jumps over the lazy dog" | ./field 4
fox

fields

Helps you work out what field you want to show.

$ echo "The quick brown fox jumps over the lazy dog" | ./fields
1 : The | 2 : quick | 3 : brown | 4 : fox | 5 : jumps | 6 : over | 7 : the | 8 : lazy | 9 : dog |

Showing final line again for readability
1 : The
2 : quick
3 : brown
4 : fox
5 : jumps
6 : over
7 : the
8 : lazy
9 : dog

float

Converts a field into a float by extracting the first float it can find in the string, ignoring and removing anything else.

$ echo -e "167.2ms\n115.89ms\n143.85ms" | ./float
167.2
115.89
143.85

int

Converts a field into an integer by extracting the first integer it can find in the string, ignoring and removing anything else.

$ echo -e "167.2ms\n115.89ms\n143.85ms" | ./int
167
115
143

## median

Calculates the median value (i.e. 50th percentile) in a stream of numbers, because the mean really sucks. Looking at the median avoids any outlying values skewing the outcome, and allows you to make a statement about half the values such as half of the web requests took less time than 95ms. For example:

$ echo -e "1\n2\n3\n4\n" | median
  3
$ echo -e "1\n2\n3\n4\n5\n100" | median
  3.5

percentiles

This command takes a stream of numbers and provides a summary of their distribution: the min/max, median and the 25th, 75th, 95th, 99th percentiles.

$ echo -e "1\n2\n3\n4\n" | percentiles 
  Min: 1, 25th , Median: 1, 75th: 2, 95th: 3, 99th: 3, Max: 4

standarddeviation

Calculates the population standard deviation for a stream of numbers.

$ echo -e "1\n2\n3\n4\n" | standarddeviation 
1.41421

total

Adds up a column of numbers from STDIN and outputs the total at the end.

$ : echo -e "1\n4\n7\n24\n64" | ./total
100

uniqcount

Roughly equivalent to piping some lines of text through sort and uniq -c, except less characters.

$ echo -e "apple\norange\norange\nbanana\napple\napple\nquince\nbanana" | ./uniqcount
2 orange
3 apple
2 banana
1 quince

urlencode / urldecode

Wrapper scripts for perls urlencoding functionality.

$ echo "first=this+is+a+field&second=was+it+clear+(already)?" | ./urlencode
first%3Dthis%2Bis%2Ba%2Bfield%26second%3Dwas%2Bit%2Bclear%2B(already)%3F
$ echo "first=this+is+a+field&second=was+it+clear+%28already%29%3F" | ./urldecode
first=this+is+a+field&second=was+it+clear+(already)?

variance

Calculates the population variance for a stream of numbers.

$ echo -e "1\n2\n3\n4\n" | variance 
  2

mrmanc/log-ninja

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