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Often, the values of these parameters are confusing. For example, let s compare the characteristics of pine, which is a mail client, and sendmail, which is a mail transport agent. pine was executed only five times, but accounted for 1426.41 KCOREMIN, while sendmail was executed 171 times with a KCOREMIN of 176.44. The explanation for this apparent anomaly is that users probably log in once in the morning and leave their pine mail client running all day. The users sent an average of 34.2 messages during this day, many of which contained attachments, thus accounting for the high CPU overhead.
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When examined over a number of days, accounting figures provide a useful means of understanding how processes are making use of the system s resources. When examined in isolation, however, they can sometimes misrepresent the dominant processes that the machine is used for. This is a well-known aspect of statistical sampling: before you can make any valid generalizations about a phenomenon, your observations must be repeated and sampled randomly. Thus, it is useful to compare the day-to-day variation of a system s resource use with the monthly figures that are generated by /usr/lib/acct/ monacct. Compare these daily values with the previous month s values generated by monacct in Table 20-2. As you can see in Table 20-2, the individual day s figures were misleading. In fact, spread over a whole month, the netscape program tended to use more resources than the pine mail client, being invoked 1,538 times, and using 163985.79 KCOREMIN, compared to 165 invocations and 43839.27 KCOREMIN for pine. Clearly, it is very useful to examine monthly averages for a more reliable, strategic overview of system activity, while daily summaries are useful for making tactical decisions about active processes.
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The previous section looked at the output for monacct, which is the monthly accounting program. To enable monacct, you need to create a cron job for the adm account, which is similar to the entry for the runacct command in the previous section:
0 5 1 * * /usr/lib/acct/monacct
In addition to computing per-process statistics, monacct also computes usage information on a per-user basis, which you can use to bill customers according to the number of CPU minutes they used. Examine the user reports in Table 20-3 for the same month that was reviewed in the previous section. Of the nonsystem users, obviously pwatters is going to have a large bill this month, with 65 prime CPU minutes consumed. Billing could also proceed on the basis of KCORE-MINS utilized; pwatters, in this case, used 104572 KCORE-MINS. How an organization bills its users is probably already well established, but even if users are not billed for cash payment, examining how the system is used is very valuable for planning expansion and for identifying rogue processes that reduce the availability of a system for legitimate processes.
Part IV: Managing Devices
COMMAND NAME totals nscp installp sed pine project ll-ar nawk predict sqpe grep pkgparam false_ne pkgremov pkginsta tee ls TOTAL KCOREMIN 529119.94 163985.79 58676.62 45704.45 43839.27 37654.92 24347.44 21678.96 16808.70 15078.86 13042.15 11360.71 10399.85 10073.67 7163.67 3237.38 3133.31 TOTAL CPU MIN 262.83 6.77 33.65 40.87 3.88 22.76 26.49 24.46 13.59 4.15 18.69 9.11 2.12 8.95 4.75 2.03 2.59 HOG FACTOR 0.00 0.00 0.17 0.42 0.00 1.00 0.53 0.61 0.99 0.40 0.71 0.94 1.00 0.39 0.12 0.88 0.78 TOTAL REALMIN 632612.94 59865.58 197.77 98.07 1594.97 22.79 50.37 40.21 13.74 10.30 26.47 9.68 2.13 22.70 38.21 2.30 3.31 MEAN SIZE-K 2013.17 24233.18 1743.57 1118.16 11304.12 1654.41 919.24 886.40 1236.66 3636.67 697.69 1246.38 4899.81 1125.88 1508.46 1592.24 1209.06 MEAN CPU-MIN 0.00 0.00 0.00 0.00 0.02 1.75 6.62 0.00 0.05 0.24 0.00 0.00 0.30 0.10 0.04 0.00 0.00
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