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Name
Size
Permission
Action
7z
40
B
-rwxr-xr-x
7za
41
B
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GET
14.71
KB
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HEAD
14.71
KB
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Magick-config
1.23
KB
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MagickCore-config
1.24
KB
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MagickWand-config
1.25
KB
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Mail
383.67
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POST
14.71
KB
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1.23
KB
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[
40.52
KB
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a2p
105.32
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aclocal
35.87
KB
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aclocal-1.13
35.87
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addr2line
28.42
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agentxtrap
19.16
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alias
29
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108.35
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13.12
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11.72
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12.35
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36.85
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9.09
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animate
7.04
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6.76
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apropos
45.49
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apu-1-config
5.97
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ar
61.22
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arch
32.3
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aria_chk
4.56
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aria_dump_log
4.36
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aria_ftdump
4.37
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aria_pack
4.4
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aria_read_log
4.52
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arj
199.56
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12.55
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7.03
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377.36
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28.21
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163.35
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51.73
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atq
51.73
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atrm
51.73
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audit2allow
14.21
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14.21
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15.48
KB
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aulastlog
11.35
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11.18
KB
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14.42
KB
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8.33
KB
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autom4te
31.43
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246.44
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246.44
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20.57
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16.72
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33.08
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31.93
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418.54
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36.48
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28.35
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941.93
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6.8
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6.8
KB
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137
B
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81.47
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bdftopcf
44.19
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bdftruncate
11.2
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26
B
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393.34
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22.74
KB
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68.99
KB
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31.89
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403.2
KB
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bzcat
31.89
KB
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2.08
KB
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bzdiff
2.08
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1.64
KB
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31.89
KB
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15.24
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bzless
1.23
KB
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bzmore
1.23
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754.59
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27.92
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c2ph
35.75
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c89
224
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c99
215
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1.6
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68.7
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69.99
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cal
36.8
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64.26
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52.81
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3.26
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36.75
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750.59
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3.95
MB
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5.83
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26
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6.13
KB
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179.75
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15.38
KB
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15.27
KB
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chage
72.16
KB
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chardetect
307
B
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11.27
KB
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13.12
KB
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chcon
61.46
KB
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checkmodule
400.48
KB
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412.46
KB
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chfn
23.41
KB
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chgrp
61.32
KB
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chmem
40.43
KB
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chmod
57.21
KB
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chown
61.36
KB
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chronyc
85.03
KB
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chrt
32.17
KB
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chsh
23.32
KB
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chvt
11.14
KB
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cifsiostat
48.5
KB
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cksum
32.38
KB
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clambc
139.76
KB
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clamconf
139.43
KB
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clamdscan
155.77
KB
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clamdtop
155.74
KB
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163.64
KB
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clamsubmit
147.73
KB
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clear
7.02
KB
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53.22
KB
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3.9
MB
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cmake3
6.21
MB
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cmp
44.14
KB
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110.59
KB
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col
23.88
KB
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11.29
KB
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colrm
23.77
KB
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column
27.99
KB
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comm
36.55
KB
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command
31
B
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11.09
KB
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1.45
KB
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7.04
KB
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7.04
KB
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6.95
KB
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7.04
KB
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154.52
KB
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cp
151.55
KB
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4.16
MB
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6.31
MB
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cpio
142.55
KB
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754.58
KB
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23.78
KB
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cpupower
66.34
KB
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crc32
794
B
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53.27
KB
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createlang
57.09
KB
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createuser
57.63
KB
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crlutil
127
KB
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crontab
56.23
KB
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csplit
48.82
KB
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19.55
KB
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4.96
MB
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ctest3
7.14
MB
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152.99
KB
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4.08
KB
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40.61
KB
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cvtsudoers
241.7
KB
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cxpm
28.05
KB
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date
60.74
KB
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db_archive
11.23
KB
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db_checkpoint
11.3
KB
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db_deadlock
11.31
KB
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db_dump
15.33
KB
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db_dump185
64.45
KB
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db_hotbackup
15.34
KB
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db_load
27.51
KB
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db_log_verify
15.34
KB
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db_printlog
32.26
KB
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db_recover
11.33
KB
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db_replicate
15.34
KB
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db_stat
15.26
KB
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db_tuner
19.33
KB
-rwxr-xr-x
db_upgrade
11.23
KB
-rwxr-xr-x
db_verify
11.25
KB
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dbilogstrip
1.43
KB
-rwxr-xr-x
dbinfo
3.29
KB
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dbiprof
6.15
KB
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dbiproxy
5.35
KB
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dbus-binding-tool
94.49
KB
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dbus-cleanup-sockets
11
KB
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dbus-daemon
218
KB
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dbus-monitor
23.13
KB
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dbus-run-session
14.97
KB
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dbus-send
27.07
KB
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dbus-test-tool
23.13
KB
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dbus-update-activation-environ...
15.02
KB
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dbus-uuidgen
10.98
KB
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dc
44.33
KB
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dd
73.14
KB
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deallocvt
11.16
KB
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debuginfo-install
7.88
KB
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delv
39.98
KB
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derb
19.95
KB
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df
102.55
KB
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dgawk
502.12
KB
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diff
195.46
KB
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diff3
60.65
KB
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dig
146.96
KB
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dir
114.85
KB
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dircolors
40.44
KB
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dirname
28.31
KB
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display
7.04
KB
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dm_date
5.47
KB
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dm_zdump
4.95
KB
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dmesg
48.52
KB
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dnsdomainname
15.41
KB
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domainname
15.41
KB
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doveadm
596.59
KB
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doveconf
161.41
KB
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dracut
55.83
KB
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dropdb
53.08
KB
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droplang
57.08
KB
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53.05
KB
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dsync
596.59
KB
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dtrace
16.66
KB
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du
110.34
KB
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77.51
KB
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15.18
KB
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3.03
MB
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easy_install-3.6
234
B
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32.31
KB
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737.83
KB
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71.57
KB
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290
B
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48.81
KB
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elfedit
32.18
KB
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enchant
15.29
KB
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enchant-lsmod
11.13
KB
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env
28.33
KB
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envsubst
36.01
KB
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eqn
144.41
KB
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ex
906.45
KB
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32.48
KB
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expr
36.53
KB
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factor
93.29
KB
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fallocate
27.84
KB
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false
28.25
KB
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fc
26
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fc-cache
132
B
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15.45
KB
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fc-cat
15.4
KB
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fc-conflist
11.2
KB
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fc-list
11.26
KB
-rwxr-xr-x
fc-match
11.32
KB
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fc-pattern
11.26
KB
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fc-query
11.23
KB
-rwxr-xr-x
fc-scan
11.27
KB
-rwxr-xr-x
fc-validate
11.27
KB
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fcat
23.82
KB
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fg
26
B
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fgconsole
11.16
KB
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fgrep
290
B
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filan
89.13
KB
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file
19.3
KB
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194.63
KB
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4.27
KB
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23.06
KB
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58.38
KB
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fipscheck
15.37
KB
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fipshmac
11.3
KB
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113.48
KB
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101.18
KB
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flex
318.07
KB
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flex++
318.07
KB
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flock
23.88
KB
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fmt
36.48
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-rwxr-xr-x
fold
36.46
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fonttosfnt
35.99
KB
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formail
43.68
KB
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free
19.33
KB
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freetype-config
4.39
KB
-rwxr-xr-x
freeze
23.82
KB
-rwxr-xr-x
freshclam
39.23
KB
-rwxr-xr-x
fribidi
16.09
KB
-rwxr-xr-x
funzip
31.38
KB
-rwxr-xr-x
g++
754.59
KB
-rwxr-xr-x
galera_new_cluster
917
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galera_recovery
3.28
KB
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gapplication
19.48
KB
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1.2
KB
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garbd
2.2
MB
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gawk
418.54
KB
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gcc
750.59
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gcc-ar
26.45
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gcc-nm
26.45
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gcc-ranlib
26.45
KB
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gcov
307.45
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-rwxr-xr-x
gdbus
40.17
KB
-rwxr-xr-x
gdbus-codegen
2
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gdk-pixbuf-query-loaders-64
15.38
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-rwxr-xr-x
gdk-pixbuf-thumbnailer
15.59
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genbrk
15.75
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-rwxr-xr-x
gencat
22.11
KB
-rwxr-xr-x
gencfu
11.64
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gencnval
19.71
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gendict
24.01
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genkey
43.13
KB
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genl-ctrl-list
11.27
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genrb
95.2
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geoiplookup
15.28
KB
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geoiplookup6
11.16
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geoipupdate
31.28
KB
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geqn
144.41
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getconf
22.02
KB
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getent
26.39
KB
-rwxr-xr-x
getfacl
24.29
KB
-rwxr-xr-x
getkeycodes
11.16
KB
-rwxr-xr-x
getopt
15.38
KB
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getopts
31
B
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gettext
35.94
KB
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gettext.sh
4.52
KB
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gio
73.41
KB
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gio-querymodules-64
11.31
KB
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git
1.46
MB
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git-receive-pack
1.46
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git-shell
717.98
KB
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git-upload-archive
1.46
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git-upload-pack
791.45
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glib-compile-resources
40.25
KB
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glib-compile-schemas
44.38
KB
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glib-genmarshal
39.97
KB
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glib-gettextize
5.25
KB
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glib-mkenums
27.15
KB
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gmake
178.47
KB
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gneqn
271
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gnroff
3.31
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goaccess
610.99
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-rwxr-xr-x
gobject-query
11.13
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-rwxr-xr-x
gost-hash
71.57
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-rwxr-xr-x
gpasswd
76.57
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-rwsr-xr-x
gpg
732.4
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-rwxr-xr-x
gpg-agent
289.74
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-rwxr-xr-x
gpg-connect-agent
152.69
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-rwxr-xr-x
gpg-error
23.18
KB
-rwxr-xr-x
gpg-error-config
1.83
KB
-rwxr-xr-x
gpg-zip
3.23
KB
-rwxr-xr-x
gpg2
732.4
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-rwxr-xr-x
gpgconf
140.31
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-rwxr-xr-x
gpgparsemail
23.7
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-rwxr-xr-x
gpgsplit
48.88
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-rwxr-xr-x
gpgv
345.38
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-rwxr-xr-x
gpgv2
345.38
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-rwxr-xr-x
gpic
180.41
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-rwxr-xr-x
gprof
98.41
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-rwxr-xr-x
gr2fonttest
23.66
KB
-rwxr-xr-x
grep
155.3
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-rwxr-xr-x
gresource
19.55
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groff
81.63
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grops
140.85
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-rwxr-xr-x
grotty
98.59
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-rwxr-xr-x
groups
32.41
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-rwxr-xr-x
grub2-editenv
396.07
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grub2-file
830.36
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grub2-fstest
1.03
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grub2-glue-efi
258.85
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grub2-kbdcomp
1.63
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grub2-menulst2cfg
241.82
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grub2-mkfont
287.6
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grub2-mkimage
379.25
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grub2-mklayout
264.91
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grub2-mknetdir
429.8
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grub2-mkpasswd-pbkdf2
271.29
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grub2-mkrelpath
258.48
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grub2-mkrescue
1017.84
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grub2-mkstandalone
534.32
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grub2-render-label
835.16
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grub2-script-check
295.43
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grub2-syslinux2cfg
763.7
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gsettings
23.8
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gsoelim
32.59
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gss-client
23.17
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gtar
338.02
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gtbl
115.96
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gtester
23.64
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gtester-report
18.39
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gtroff
512.96
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-rwxr-xr-x
gunzip
2.2
KB
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gzexe
5.79
KB
-rwxr-xr-x
gzip
98.43
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-rwxr-xr-x
h2ph
27.65
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h2xs
59.15
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has160-hash
71.57
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hdsploader
11.18
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head
40.51
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hexdump
32.02
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hmac256
15.67
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host
127.02
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hostid
28.32
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-rwxr-xr-x
hostname
15.41
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-rwxr-xr-x
hostnamectl
318.07
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-rwxr-xr-x
hunspell
53.11
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-rwxr-xr-x
i386
15.27
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-rwxr-xr-x
iceauth
31.73
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-rwxr-xr-x
iconv
58.14
KB
-rwxr-xr-x
icu-config
172
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icu-config-64
21.49
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-rwxr-xr-x
icuinfo
15.6
KB
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id
36.52
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identify
7.06
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-rwxr-xr-x
idiag-socket-details
11.34
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idn
32.45
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ifnames
4.03
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-rwxr-xr-x
igawk
3.11
KB
-rwxr-xr-x
imapsync
338.75
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import
7.04
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info
265.19
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infocmp
56.07
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infokey
21.47
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infotocap
64.26
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innochecksum
3.64
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install
139.59
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instmodsh
4.15
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ionice
23.86
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iostat
60.77
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-rwxr-xr-x
ipcalc
15.05
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ipcmk
24
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ipcrm
27.85
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ipcs
48.37
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-rwxr-xr-x
iptables-xml
91.52
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isosize
23.83
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ispell
988
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jemalloc.sh
125
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jobs
28
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join
48.75
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journalctl
537.88
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-rwxr-xr-x
kbd_mode
11.16
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kbdinfo
11.19
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-rwxr-xr-x
kbdrate
11.22
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kdumpctl
33.18
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-rwxr-xr-x
kernel-install
4.7
KB
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keyrand
11.25
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keyutil
60.84
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kill
32.82
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kmod
143.24
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krb5-config
6.96
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l4p-tmpl
1.89
KB
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last
19.11
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lastb
19.11
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lastlog
19.15
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lchfn
15.52
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lchsh
15.49
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ld
982.61
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ld.bfd
982.61
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ld.gold
5.11
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ldd
5.18
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less
154.53
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lessecho
11.11
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lesskey
16.66
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lesspipe.sh
2.24
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lex
318.07
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lexgrog
85.09
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libgcrypt-config
3.78
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libmcrypt-config
1.38
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libnetcfg
15.36
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libpng-config
2.38
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libpng15-config
2.38
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link
28.3
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links
4.37
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links2
4.37
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linux-boot-prober
5.85
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linux32
15.27
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linux64
15.27
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ln
57.22
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loadkeys
110.48
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loadunimap
23.88
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locale
37.11
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localectl
326.16
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localedef
318.31
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locate
39.57
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lockfile
19.36
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logger
28.62
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login
36.38
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loginctl
489.62
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logname
28.31
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look
11.27
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ls
114.85
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lsattr
11.25
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lsblk
79.17
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lscpu
60.75
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lsinitrd
6.26
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lsipc
60.95
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lslocks
41.01
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lslogins
52.88
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lsmem
40.78
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lsns
36.43
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lsscsi
56.48
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lua
15.47
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luac
119.03
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lwp-download
8.43
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lwp-dump
2.73
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lwp-mirror
2.42
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lwp-request
14.71
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lynis
50.57
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lz4
105.84
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lz4c
105.84
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lz4cat
105.84
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lzop
69.32
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m4
151.17
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machinectl
533.95
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magnet-link
71.57
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mail
383.67
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mailq
322.16
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mailq.postfix
322.16
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mailstat
5.72
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mailx
383.67
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make
178.47
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makeconv
40.51
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makedb
18.11
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man
100.44
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mandb
122.25
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manpath
32.55
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mapscrn
19.78
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mariadb
4.33
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mariadb-access
109.33
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mariadb-admin
3.85
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mariadb-binlog
4.11
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mariadb-check
3.85
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mariadb-convert-table-format
4.12
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mariadb-dump
3.94
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mariadb-dumpslow
8.05
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mariadb-embedded
21.82
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mariadb-find-rows
3.21
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mariadb-fix-extensions
1.22
KB
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mariadb-hotcopy
34.14
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mariadb-import
3.84
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mariadb-install-db
21.57
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mariadb-plugin
3.54
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mariadb-secure-installation
13.37
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mariadb-service-convert
2.45
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mariadb-setpermission
17.13
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mariadb-show
3.84
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mariadb-slap
3.86
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mariadb-tzinfo-to-sql
3.54
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mariadb-upgrade
3.63
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mariadb-waitpid
3.53
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mariadb_config
11.57
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mariadbd-multi
26.69
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mariadbd-safe
30.39
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mariadbd-safe-helper
3.5
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mcookie
15.44
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md5sum
40.53
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mdig
44.2
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melt
23.82
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memaslap
65.37
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memcached
108.77
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memcached-tool
4.18
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memcapable
57.71
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memcat
19.99
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memcp
20.19
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memdump
15.81
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memerror
15.46
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memexist
15.72
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memflush
15.73
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memparse
11.06
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memping
15.84
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memrm
15.78
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memslap
24.55
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memstat
20.17
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memtouch
15.8
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mesg
10.98
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mimedump
2.29
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mimeencode
849
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mimeexplode
3.28
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mimepostcard
2.68
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mimesend
3.06
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mixartloader
15.38
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mkdir
77.9
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mkfifo
61.59
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mkfontdir
65
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mkfontscale
32.48
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mkinitrd
2.94
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mknod
65.61
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mktemp
40.66
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modutil
165.78
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mogrify
7.04
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montage
7.04
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more
40.15
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mount
43.23
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mountpoint
15.32
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mpstat
52.53
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msgattrib
23.36
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msgcat
23.34
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msgcmp
23.59
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msgcomm
19.31
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msgconv
19.3
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msgen
19.3
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msgexec
15.33
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msgfilter
27.56
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msgfmt
77.05
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msggrep
35.97
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msghack
12.45
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msginit
44.38
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msgmerge
52.6
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msgunfmt
31.7
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msguniq
19.31
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msql2mysql
1.41
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mv
127.3
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my_print_defaults
3.53
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myisam_ftdump
3.89
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myisamchk
4.01
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myisamlog
3.87
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myisampack
3.91
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mysql
4.33
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mysql_config
4.58
KB
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mysql_convert_table_format
4.12
KB
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mysql_embedded
21.82
MB
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mysql_find_rows
3.21
KB
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mysql_fix_extensions
1.22
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mysql_install_db
21.57
KB
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mysql_plugin
3.54
MB
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mysql_secure_installation
13.37
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mysql_setpermission
17.13
KB
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mysql_tzinfo_to_sql
3.54
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mysql_upgrade
3.63
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mysql_waitpid
3.53
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-rwxr-xr-x
mysqlaccess
109.33
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mysqladmin
3.85
MB
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mysqlbinlog
4.11
MB
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mysqlcheck
3.85
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mysqld_multi
26.69
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mysqld_safe
30.39
KB
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mysqld_safe_helper
3.5
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mysqldump
3.94
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mysqldumpslow
8.05
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mysqlhotcopy
34.14
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mysqlimport
3.84
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mysqlshow
3.84
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mysqlslap
3.86
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nail
383.67
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named-rrchecker
15.32
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namei
27.95
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nano
201.08
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ncurses5-config
5.68
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ncursesw5-config
5.68
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ndptool
23.63
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needs-restarting
8.17
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neqn
271
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net-server
3.34
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net-snmp-config
1.3
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net-snmp-config-x86_64
29.46
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net-snmp-create-v3-user
2.98
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netstat
151.38
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nettle-hash
11.33
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nettle-lfib-stream
7.05
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newaliases
322.16
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newaliases.postfix
322.16
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newgidmap
38.09
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newgrp
40.95
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newuidmap
38.06
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nf-ct-add
11.8
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nf-ct-list
15.84
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nf-exp-add
16.21
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nf-exp-delete
15.99
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nf-exp-list
11.8
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nf-log
11.23
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nf-monitor
11.18
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nf-queue
11.27
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nfsiostat-sysstat
52.52
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ngettext
35.95
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nice
32.32
KB
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nisdomainname
15.41
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nl
40.6
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nl-addr-add
11.65
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nl-addr-delete
11.73
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nl-addr-list
15.88
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nl-class-add
11.7
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nl-class-delete
11.55
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nl-class-list
11.48
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nl-classid-lookup
11.29
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nl-cls-add
11.76
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nl-cls-delete
11.68
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nl-cls-list
11.58
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nl-fib-lookup
11.41
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nl-link-enslave
7.05
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nl-link-ifindex2name
7.06
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nl-link-list
11.52
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nl-link-name2ifindex
7.05
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nl-link-release
7.05
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nl-link-set
11.64
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nl-link-stats
11.39
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nl-list-caches
11.08
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nl-list-sockets
7.06
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nl-monitor
11.2
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nl-neigh-add
11.51
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nl-neigh-delete
11.57
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nl-neigh-list
11.46
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nl-neightbl-list
11.27
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nl-pktloc-lookup
11.36
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nl-qdisc-add
11.6
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nl-qdisc-delete
11.54
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nl-qdisc-list
11.63
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nl-route-add
11.73
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nl-route-delete
15.86
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nl-route-get
11.18
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nl-route-list
11.77
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nl-rule-list
11.3
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nl-tctree-list
11.53
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nl-util-addr
7.03
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nm
45.43
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nm-online
15.16
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nmcli
809.16
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nmtui
646.77
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nmtui-connect
646.77
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nmtui-edit
646.77
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nmtui-hostname
646.77
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nohup
32.42
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nomarch
19.6
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nproc
32.37
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nroff
3.31
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nsenter
28.22
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nslookup
130.93
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nss-policy-check
15.26
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nsupdate
65.2
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numfmt
64.71
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-rwxr-xr-x
objcopy
227.34
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-rwxr-xr-x
objdump
357.74
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od
64.81
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-rwxr-xr-x
offlineimap
926
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oldfind
186.41
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onig-config
1.31
KB
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opax
110.53
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open
19.48
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-rwxr-xr-x
openssl
542.27
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-rwxr-xr-x
openvt
19.48
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os-prober
5.51
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p11-kit
32.18
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package-cleanup
17.39
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package-stash-conflicts
487
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page_owner_sort
10.2
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pango-list
11.1
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pango-querymodules-64
28.26
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pango-view
49.47
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paperconf
11.23
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passwd
27.2
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paste
32.34
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pathchk
32.31
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pax
110.53
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pchrt
3.93
KB
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pcre-config
2.09
KB
-rwxr-xr-x
perl
11.14
KB
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perl5.16.3
11.14
KB
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perlbug
43.61
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perldoc
203
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perlivp
10.52
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perlthanks
43.61
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perror
3.72
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pflags
2.06
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pg_config
28
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pg_dump
305.78
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pg_dumpall
73.89
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pg_restore
126.79
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pgawk
418.63
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pgrep
27.67
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php
41.44
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pic
180.41
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piconv
7.99
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pidstat
68.89
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pinentry
2.54
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pinentry-curses
49.19
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ping
64.63
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ping6
64.63
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pinky
36.57
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-rwxr-xr-x
pip-3
407
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pip-3.6
407
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pip3
407
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pip3.6
407
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pk12util
103.22
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pkaction
15
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pkcheck
23.03
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pkcs1-conv
15.52
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pkexec
27.02
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pkg-config
44.38
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pkgdata
36.7
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pkill
27.67
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pkla-admin-identities
19.23
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pkla-check-authorization
27.3
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pkttyagent
18.98
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pl2pm
4.42
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pldd
14.11
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plymouth
39.77
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pmap
27.61
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pod2html
4
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pod2man
13.26
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pod2text
10.75
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pod2usage
3.67
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post-grohtml
187.55
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powernow-k8-decode
6.15
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pr
65.11
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pre-grohtml
86.24
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precat
5.52
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preconv
40.88
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preunzip
5.52
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prezip
5.52
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prezip-bin
11.05
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printenv
28.28
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printf
48.61
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prlimit
41.2
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procan
76.99
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procmail
105.45
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prove
13.13
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ps
97.77
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psed
52.08
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psfaddtable
19.48
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psfgettable
19.48
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psfstriptable
19.48
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psfxtable
19.48
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pspell-config
384
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438.74
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pstruct
35.75
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pt-align
39.89
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pt-archiver
255.74
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pt-config-diff
164.27
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pt-deadlock-logger
161.56
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pt-diskstats
160.3
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pt-duplicate-key-checker
164.22
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pt-fifo-split
48.11
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pt-find
145.46
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pt-fingerprint
64.85
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pt-fk-error-logger
129.3
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pt-heartbeat
186.97
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pt-index-usage
219.97
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pt-ioprofile
31.59
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pt-kill
242.13
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pt-mext
21.24
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pt-mysql-summary
98.62
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pt-online-schema-change
374.96
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pt-pmp
24.02
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pt-query-digest
505.41
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pt-show-grants
70.84
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pt-sift
36.84
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pt-slave-delay
141.38
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pt-slave-find
124
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pt-slave-restart
174.58
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pt-stalk
67.93
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pt-summary
87.76
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pt-table-checksum
408.52
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pt-table-sync
386.36
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pt-table-usage
217.38
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pt-upgrade
322.26
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pt-variable-advisor
172.12
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pt-visual-explain
99.27
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ptar
3.43
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ptardiff
2.41
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ptargrep
4.13
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ptaskset
3.8
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ptx
65.08
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pure-ftpwho
6.95
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pure-pw
39.5
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pure-pwconvert
10.95
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pure-statsdecode
10.95
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pwd
32.45
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pwdx
11.27
KB
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pwmake
11.13
KB
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pwscore
11.13
KB
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pydoc
78
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pydoc3
78
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pydoc3.6
78
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python
6.98
KB
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python2
6.98
KB
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python2.7
6.98
KB
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python3
11.07
KB
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python3.6
11.07
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python3.6m
11.07
KB
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pyvenv
435
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pyvenv-3.6
435
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qemu-ga
267.8
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quota
83.31
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quotasync
70.84
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ranlib
61.22
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raw
15.27
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razor-admin
905
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razor-check
907
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razor-client
624
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razor-report
911
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razor-revoke
911
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28
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509.83
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readlink
40.82
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realpath
61.23
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rearj
60.17
KB
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recode
39.87
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recode-sr-latin
15.29
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1.28
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2.79
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redis-check-rdb
2.79
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926.3
KB
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2.79
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redis-server
2.79
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57.27
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11.26
KB
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11.21
KB
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3.51
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4.09
KB
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repo-rss
10.07
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11.42
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repodiff
13.97
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repomanage
6.88
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repoquery
55.68
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reposync
14.14
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repotrack
9.86
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rescan-scsi-bus.sh
33.81
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19.6
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19.63
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3.53
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3.53
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11.26
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rhash
71.57
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rkhunter
562.04
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rm
61.4
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rmail
262
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rmail.postfix
262
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rmdir
44.46
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rnano
201.08
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rpcgen
90.45
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rpm
15.75
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rpm2cpio
11.16
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rpmdb
11.73
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rpmgraph
15.63
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rpmkeys
11.73
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rpmquery
15.75
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rpmverify
15.75
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rrdcached
52.98
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rrdcgi
27.81
KB
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rrdcreate
89.35
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rrdinfo
89.35
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rrdtool
27.49
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rrdupdate
89.35
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rsync
488.38
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rsyslog-recover-qi.pl
5.96
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2.04
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run-with-aspell
85
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runcon
32.47
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rvi
906.45
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rview
906.45
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s2p
52.08
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sa-awl
4.91
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sa-check_spamd
14.45
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sa-compile
21.62
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sa-learn
44.5
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sa-update
68.06
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sadf
168.45
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17.52
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sar
95.38
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sasl2-sample-client
19.27
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sasl2-sample-server
19.1
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scp
89.23
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screen
464.1
KB
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script
19.61
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scriptreplay
15.29
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scsi-rescan
33.81
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scsi_logging_level
7.72
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scsi_mandat
3.55
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scsi_readcap
1.3
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scsi_ready
1.09
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scsi_satl
3.76
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scsi_start
1.25
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scsi_stop
1.44
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scsi_temperature
936
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sdiff
48.41
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secon
24.06
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sed
74.29
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sedismod
249.42
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sedispol
176.32
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semodule_package
15.3
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seq
48.48
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sessreg
11.24
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setarch
15.27
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setfacl
36.73
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setfont
40.38
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setkeycodes
11.16
KB
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setleds
11.16
KB
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setmetamode
11.21
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setpriv
36.06
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setsid
11.23
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setterm
27.48
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setup-nsssysinit
1.5
KB
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setup-nsssysinit.sh
1.5
KB
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setvtrgb
11.34
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sexp-conv
23.63
KB
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sftp
142.01
KB
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sfv-hash
71.57
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sg
40.95
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sg_compare_and_write
15.82
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sg_copy_results
20.02
KB
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sg_dd
43.63
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sg_decode_sense
15.49
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sg_emc_trespass
11.09
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sg_format
24.05
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sg_get_config
28.22
KB
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sg_get_lba_status
15.5
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sg_ident
15.46
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sg_inq
83.68
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sg_logs
92.48
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sg_luns
19.65
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-rwxr-xr-x
sg_map
15.23
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-rwxr-xr-x
sg_map26
23.77
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-rwxr-xr-x
sg_modes
29.3
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-rwxr-xr-x
sg_opcodes
23.88
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-rwxr-xr-x
sg_persist
28.34
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-rwxr-xr-x
sg_prevent
11.29
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-rwxr-xr-x
sg_raw
19.78
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-rwxr-xr-x
sg_rbuf
19.66
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-rwxr-xr-x
sg_rdac
15.13
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-rwxr-xr-x
sg_read
23.33
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-rwxr-xr-x
sg_read_block_limits
11.31
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-rwxr-xr-x
sg_read_buffer
15.53
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-rwxr-xr-x
sg_read_long
15.55
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-rwxr-xr-x
sg_readcap
19.66
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-rwxr-xr-x
sg_reassign
15.54
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-rwxr-xr-x
sg_referrals
15.48
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-rwxr-xr-x
sg_requests
15.58
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-rwxr-xr-x
sg_reset
11.46
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-rwxr-xr-x
sg_rmsn
11.32
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-rwxr-xr-x
sg_rtpg
15.39
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-rwxr-xr-x
sg_safte
19.59
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-rwxr-xr-x
sg_sanitize
19.88
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-rwxr-xr-x
sg_sat_identify
15.55
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-rwxr-xr-x
sg_sat_phy_event
15.87
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-rwxr-xr-x
sg_sat_set_features
15.41
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-rwxr-xr-x
sg_scan
15.34
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-rwxr-xr-x
sg_senddiag
20.02
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-rwxr-xr-x
sg_ses
67.55
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-rwxr-xr-x
sg_start
19.7
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-rwxr-xr-x
sg_stpg
19.61
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-rwxr-xr-x
sg_sync
15.52
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-rwxr-xr-x
sg_test_rwbuf
15.6
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-rwxr-xr-x
sg_turs
15.48
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-rwxr-xr-x
sg_unmap
15.5
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-rwxr-xr-x
sg_verify
15.7
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-rwxr-xr-x
sg_vpd
77.67
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-rwxr-xr-x
sg_wr_mode
19.55
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-rwxr-xr-x
sg_write_buffer
15.66
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-rwxr-xr-x
sg_write_long
15.55
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-rwxr-xr-x
sg_write_same
19.9
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-rwxr-xr-x
sg_xcopy
35.61
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-rwxr-xr-x
sginfo
65.8
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-rwxr-xr-x
sgm_dd
31.52
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-rwxr-xr-x
sgp_dd
35.83
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-rwxr-xr-x
sh
941.93
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-rwxr-xr-x
sha1sum
36.57
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-rwxr-xr-x
sha224sum
40.63
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-rwxr-xr-x
sha256sum
40.63
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-rwxr-xr-x
sha384sum
40.65
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-rwxr-xr-x
sha512sum
40.65
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-rwxr-xr-x
shasum
8.4
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-rwxr-xr-x
show-changed-rco
10.13
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-rwxr-xr-x
show-installed
16.18
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-rwxr-xr-x
showconsolefont
15.47
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-rwxr-xr-x
showkey
15.23
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-rwxr-xr-x
showrgb
7.08
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-rwxr-xr-x
shred
52.94
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-rwxr-xr-x
shuf
49.13
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-rwxr-xr-x
sieve-dump
23.05
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-rwxr-xr-x
sieve-filter
27.06
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-rwxr-xr-x
sieve-test
27.13
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-rwxr-xr-x
sievec
23.06
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-rwxr-xr-x
signver
102.6
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-rwxr-xr-x
sigtool
207.89
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-rwxr-xr-x
sim_client
14.97
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-rwxr-xr-x
size
32.35
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-rwxr-xr-x
skill
23.62
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-rwxr-xr-x
slabinfo
34.96
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-rwxr-xr-x
slabtop
19.52
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-rwxr-xr-x
sleep
32.35
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-rwxr-xr-x
slogin
756.4
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-rwxr-xr-x
snice
23.62
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-rwxr-xr-x
snmpconf
25.52
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-rwxr-xr-x
socat
380.43
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-rwxr-xr-x
soelim
32.59
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-rwxr-xr-x
sort
114.94
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-rwxr-xr-x
sotruss
4.24
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-rwxr-xr-x
spamassassin
29.22
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-rwxr-xr-x
spamc
45.19
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-rwxr-xr-x
spamd
125.25
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-rwxr-xr-x
spell
122
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-rwxr-xr-x
spfquery
4.49
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-rwxr-xr-x
splain
18.03
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-rwxr-xr-x
split
69.47
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-rwxr-xr-x
sprof
22.1
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-rwxr-xr-x
sqlite3
54.95
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-rwxr-xr-x
ssh
756.4
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-rwxr-xr-x
ssh-add
352.46
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-rwxr-xr-x
ssh-agent
373.25
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---x--s--x
ssh-copy-id
10.22
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-rwxr-xr-x
ssh-keygen
409.38
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-rwxr-xr-x
ssh-keyscan
430.7
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-rwxr-xr-x
sshpass
15.37
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-rwxr-xr-x
ssltap
118.41
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-rwxr-xr-x
stat
77.19
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-rwxr-xr-x
statist
11.18
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-rwxr-xr-x
stdbuf
64.88
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-rwxr-xr-x
stream
7.04
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-rwxr-xr-x
strings
32.55
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-rwxr-xr-x
strip
227.34
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-rwxr-xr-x
stty
68.61
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-rwxr-xr-x
su
31.38
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-rwsr-xr-x
sudo
147.88
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---s--x--x
sudoedit
147.88
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---s--x--x
sudoreplay
56.11
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---x--x--x
sum
36.55
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-rwxr-xr-x
svn
232.45
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svnadmin
67.4
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svndumpfilter
35.32
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svnlook
67.45
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svnrdump
51.54
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svnserve
83.95
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svnsync
51.59
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svnversion
15.15
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sxpm
19.83
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sync
28.33
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systemctl
704.8
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systemd-analyze
1.49
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-rwxr-xr-x
systemd-ask-password
60.38
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systemd-cat
39.98
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-rwxr-xr-x
systemd-cgls
326.29
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-rwxr-xr-x
systemd-cgtop
85.09
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systemd-coredumpctl
154.52
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systemd-delta
76.84
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systemd-detect-virt
39.97
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systemd-escape
48.2
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systemd-firstboot
101.52
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systemd-hwdb
85.31
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systemd-inhibit
309.83
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systemd-loginctl
489.62
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systemd-machine-id-setup
52.23
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systemd-notify
48.13
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systemd-nspawn
545.88
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systemd-path
52.16
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systemd-run
387.05
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systemd-stdio-bridge
305.77
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systemd-sysv-convert
3.89
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systemd-tmpfiles
146.13
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systemd-tty-ask-password-agent
84.75
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tabs
15.31
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tac
32.48
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tail
65.25
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tailf
23.88
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tapestat
52.55
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tar
338.02
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taskset
32.22
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tbl
115.96
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tcamgr
23.47
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tcamttest
19.37
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tcatest
52.78
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tcbmgr
27.66
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tcbmttest
47.96
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tcbtest
64.47
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tcfmgr
19.5
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tcfmttest
31.79
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tcftest
43.86
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tchmgr
23.52
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tchmttest
43.87
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tchtest
52.29
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tctmgr
31.82
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tctmttest
39.72
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tcttest
51.9
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tcucodec
31.75
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tcumttest
19.52
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tcutest
65.61
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teamd
155.09
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teamdctl
28.98
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teamnl
19.09
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tee
32.38
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test
36.46
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testgdbm
29.77
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tic
64.26
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tiger-hash
71.57
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timedatectl
330.22
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timeout
53.31
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tload
15.38
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tmon
31.11
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toe
15.43
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top
104.38
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touch
61.02
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tput
15.41
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tr
44.61
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tracepath
15.05
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tracepath6
15.05
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troff
512.96
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true
28.26
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truncate
52.68
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trust
179.08
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tset
19.6
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tsort
36.47
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tth-hash
71.57
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tty
28.29
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turbostat
113.15
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type99
4.57
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tzselect
7.17
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uconv
52.57
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ucs2any
19.47
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udevadm
414.27
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ul
19.47
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umask
29
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umount
31.23
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unalias
31
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uname
32.3
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unarj
74
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unexpand
32.45
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unfreeze
23.82
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unicode_start
2.5
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unicode_stop
363
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uniq
44.71
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unlink
28.3
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unlz4
105.84
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unshare
15.45
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unxz
73.52
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unzip
185.16
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unzipsfx
88.66
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unzoo
27.67
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update-ca-trust
1.03
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update-mime-database
52.82
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updatedb
47.65
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uptime
11.22
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urlgrabber
12.17
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users
32.42
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usleep
10.95
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usx2yloader
15.41
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utmpdump
15.45
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uuclient
14.97
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uuidgen
11.21
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vacuumdb
57.35
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varnishadm
124.63
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varnishhist
55.02
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varnishlog
30.09
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varnishncsa
98.75
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varnishstat
88.88
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varnishtest
1.19
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varnishtop
61.65
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vdir
114.85
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verifytree
10.79
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vi
906.45
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view
906.45
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vlock
15.73
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vmstat
31.48
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vxloader
15.38
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w
19.45
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wait
28
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wall
14.98
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watch
24.14
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watchgnupg
15.35
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wc
40.67
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wdctl
40.7
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wget
408.96
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whatis
45.49
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whereis
20.2
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which
23.77
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whiptail
27.84
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whirlpool-hash
71.57
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who
48.7
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whoami
28.3
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word-list-compress
11.03
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write
19.09
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wsrep_sst_backup
2.95
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wsrep_sst_common
54.08
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wsrep_sst_mariabackup
50.86
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wsrep_sst_mysqldump
7.7
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wsrep_sst_rsync
32.2
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wsrep_sst_rsync_wan
32.2
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x86_64
15.27
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x86_64-redhat-linux-c++
754.59
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x86_64-redhat-linux-g++
754.59
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x86_64-redhat-linux-gcc
750.59
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x86_energy_perf_policy
10.23
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xargs
60.91
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xgamma
11.15
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xgettext
265.35
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xhost
15.38
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xinput
52.81
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xkill
15.27
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xml2-config
1.68
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xmlcatalog
15.3
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xmllint
61.94
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xmlwf
24
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xmodmap
32.28
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xorg-x11-fonts-update-dirs
1.29
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xrandr
60.06
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xrdb
27.78
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xrefresh
11.16
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xset
31.72
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xsetmode
11.1
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xsetpointer
11.13
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xsetroot
19.38
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xslt-config
2.36
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xsltproc
23.51
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xstdcmap
15.77
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xsubpp
4.45
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xz
73.52
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xzcat
73.52
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xzcmp
6.48
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xzdec
11.21
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xzdiff
6.48
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xzegrep
5.76
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xzfgrep
5.76
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xzgrep
5.76
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xzless
1.76
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xzmore
2.11
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yes
28.3
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ypdomainname
15.41
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yum
801
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yum-builddep
9.95
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yum-config-manager
9.35
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yum-debug-dump
8.34
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yum-debug-restore
7.72
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yum-groups-manager
10.77
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yumdownloader
10.85
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zcat
1.9
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zcmp
1.72
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zdiff
5.63
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zegrep
123
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zfgrep
123
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zforce
2.09
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zgrep
5.98
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zip
210.78
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zipcloak
98.1
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zipdetails
47.32
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zipgrep
2.88
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zipinfo
185.16
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zipnote
93.73
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zipsplit
97.75
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zless
1.99
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zmore
2.79
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znew
5.22
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zsoelim
32.59
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Code Editor : sa-learn
#!/usr/bin/perl -T -w eval 'exec /usr/bin/perl -T -w -S $0 ${1+"$@"}' if 0; # not running under some shell # <@LICENSE> # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to you under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at: # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # </@LICENSE> use strict; use bytes; use Errno qw(EBADF); use Getopt::Long; use Pod::Usage; use File::Spec; use vars qw( $spamtest %opt $isspam $forget $messagecount $learnedcount $messagelimit $progress $total_messages $init_results $start_time $synconly $learnprob @targets $bayes_override_path ); my $PREFIX = '/usr'; # substituted at 'make' time my $DEF_RULES_DIR = '/usr/share/spamassassin'; # substituted at 'make' time my $LOCAL_RULES_DIR = '/etc/mail/spamassassin'; # substituted at 'make' time use lib '/usr/share/perl5/vendor_perl'; # substituted at 'make' time BEGIN { # see comments in "spamassassin.raw" for doco my @bin = File::Spec->splitpath($0); my $bin = ($bin[0] ? File::Spec->catpath(@bin[0..1]) : $bin[1]) || File::Spec->curdir; if (-e $bin.'/lib/Mail/SpamAssassin.pm' || !-e '/usr/share/perl5/vendor_perl/Mail/SpamAssassin.pm' ) { my $searchrelative; if ($searchrelative && $bin eq '../' && -e '../blib/lib/Mail/SpamAssassin.pm') { unshift ( @INC, '../blib/lib' ); } else { foreach ( qw(lib ../lib/site_perl ../lib/spamassassin ../share/spamassassin/lib)) { my $dir = File::Spec->catdir( $bin, split ( '/', $_ ) ); if ( -f File::Spec->catfile( $dir, "Mail", "SpamAssassin.pm" ) ) { unshift ( @INC, $dir ); last; } } } } } use Mail::SpamAssassin; use Mail::SpamAssassin::ArchiveIterator; use Mail::SpamAssassin::Message; use Mail::SpamAssassin::PerMsgLearner; use Mail::SpamAssassin::Util::Progress; use Mail::SpamAssassin::Logger; ########################################################################### $SIG{PIPE} = 'IGNORE'; # used to be CmdLearn::cmd_run() ... %opt = ( 'force-expire' => 0, 'use-ignores' => 0, 'nosync' => 0, 'cf' => [] ); Getopt::Long::Configure( qw(bundling no_getopt_compat permute no_auto_abbrev no_ignore_case) ); GetOptions( 'forget' => \$forget, 'ham|nonspam' => sub { $isspam = 0; }, 'spam' => sub { $isspam = 1; }, 'sync' => \$synconly, 'rebuild' => sub { $synconly = 1; warn "The --rebuild option has been deprecated. Please use --sync instead.\n" }, 'username|u=s' => \$opt{'username'}, 'configpath|config-file|config-dir|c|C=s' => \$opt{'configpath'}, 'prefspath|prefs-file|p=s' => \$opt{'prefspath'}, 'siteconfigpath=s' => \$opt{'siteconfigpath'}, 'cf=s' => \@{$opt{'cf'}}, 'folders|f=s' => \$opt{'folders'}, 'force-expire|expire' => \$opt{'force-expire'}, 'local|L' => \$opt{'local'}, 'no-sync|nosync' => \$opt{'nosync'}, 'showdots' => \$opt{'showdots'}, 'progress' => \$opt{'progress'}, 'use-ignores' => \$opt{'use-ignores'}, 'no-rebuild|norebuild' => sub { $opt{'nosync'} = 1; warn "The --no-rebuild option has been deprecated. Please use --no-sync instead.\n" }, 'learnprob=f' => \$opt{'learnprob'}, 'randseed=i' => \$opt{'randseed'}, 'stopafter=i' => \$opt{'stopafter'}, 'max-size=i' => \$opt{'max-size'}, 'debug|debug-level|D:s' => \$opt{'debug'}, 'help|h|?' => \$opt{'help'}, 'version|V' => \$opt{'version'}, 'dump:s' => \$opt{'dump'}, 'import' => \$opt{'import'}, 'backup' => \$opt{'backup'}, 'clear' => \$opt{'clear'}, 'restore=s' => \$opt{'restore'}, 'dir' => sub { $opt{'old_format'} = 'dir'; }, 'file' => sub { $opt{'old_format'} = 'file'; }, 'mbox' => sub { $opt{'format'} = 'mbox'; }, 'mbx' => sub { $opt{'format'} = 'mbx'; }, 'single' => sub { $opt{'old_format'} = 'single'; }, 'db|dbpath=s' => \$bayes_override_path, 're|regexp=s' => \$opt{'regexp'}, '<>' => \&target, ) or usage( 0, "Unknown option!" ); if ( defined $opt{'help'} ) { usage( 0, "For more information read the manual page" ); } if ( defined $opt{'version'} ) { print "SpamAssassin version " . Mail::SpamAssassin::Version() . "\n"; exit 0; } # set debug areas, if any specified (only useful for command-line tools) if (defined $opt{'debug'}) { $opt{'debug'} ||= 'all'; } if ( $opt{'force-expire'} ) { $synconly = 1; } if ($opt{'showdots'} && $opt{'progress'}) { print "--showdots and --progress may not be used together, please select just one\n"; exit 0; } if ( !defined $isspam && !defined $synconly && !defined $forget && !defined $opt{'dump'} && !defined $opt{'import'} && !defined $opt{'clear'} && !defined $opt{'backup'} && !defined $opt{'restore'} && !defined $opt{'folders'} ) { usage( 0, "Please select either --spam, --ham, --folders, --forget, --sync, --import,\n--dump, --clear, --backup or --restore" ); } # We need to make sure the journal syncs pre-forget... if ( defined $forget && $opt{'nosync'} ) { $opt{'nosync'} = 0; warn "sa-learn warning: --forget requires read/write access to the database, and is incompatible with --no-sync\n"; } if ( defined $opt{'old_format'} ) { #Format specified in the 2.5x form of --dir, --file, --mbox, --mbx or --single. #Convert it to the new behavior: if ( $opt{'old_format'} eq 'single' ) { push ( @ARGV, '-' ); } } my $post_config = ''; # kluge to support old check_bayes_db operation # bug 3799: init() will go r/o with the configured DB, and then dbpath needs # to override. Just access the dbpath version via post_config_text. if ( defined $bayes_override_path ) { # Add a default prefix if the path is a directory if ( -d $bayes_override_path ) { $bayes_override_path = File::Spec->catfile( $bayes_override_path, 'bayes' ); } $post_config .= "bayes_path $bayes_override_path\n"; } # These options require bayes_scanner, which requires "use_bayes 1", but # that's not necessary for these commands. if (defined $opt{'dump'} || defined $opt{'import'} || defined $opt{'clear'} || defined $opt{'backup'} || defined $opt{'restore'}) { $post_config .= "use_bayes 1\n"; } $post_config .= join("\n", @{$opt{'cf'}})."\n"; # create the tester factory $spamtest = new Mail::SpamAssassin( { rules_filename => $opt{'configpath'}, site_rules_filename => $opt{'siteconfigpath'}, userprefs_filename => $opt{'prefspath'}, username => $opt{'username'}, debug => $opt{'debug'}, local_tests_only => $opt{'local'}, dont_copy_prefs => 1, PREFIX => $PREFIX, DEF_RULES_DIR => $DEF_RULES_DIR, LOCAL_RULES_DIR => $LOCAL_RULES_DIR, post_config_text => $post_config, } ); $spamtest->init(1); dbg("sa-learn: spamtest initialized"); # Bug 6228 hack: bridge the transition gap of moving Bayes.pm into a plugin; # To be resolved more cleanly!!! if ($spamtest->{bayes_scanner}) { foreach my $plugin ( @{ $spamtest->{plugins}->{plugins} } ) { if ($plugin->isa('Mail::SpamAssassin::Plugin::Bayes')) { # copy plugin's "store" object ref one level up! $spamtest->{bayes_scanner}->{store} = $plugin->{store}; } } } if (Mail::SpamAssassin::Util::am_running_on_windows()) { binmode(STDIN) or die "cannot set binmode on STDIN: $!"; # bug 4363 binmode(STDOUT) or die "cannot set binmode on STDOUT: $!"; } if ( defined $opt{'dump'} ) { my ( $magic, $toks ); if ( $opt{'dump'} eq 'all' || $opt{'dump'} eq '' ) { # show us all tokens! ( $magic, $toks ) = ( 1, 1 ); } elsif ( $opt{'dump'} eq 'magic' ) { # show us magic tokens only ( $magic, $toks ) = ( 1, 0 ); } elsif ( $opt{'dump'} eq 'data' ) { # show us data tokens only ( $magic, $toks ) = ( 0, 1 ); } else { # unknown option warn "Unknown dump option '" . $opt{'dump'} . "'\n"; $spamtest->finish_learner(); exit 1; } if (!$spamtest->dump_bayes_db( $magic, $toks, $opt{'regexp'}) ) { $spamtest->finish_learner(); die "ERROR: Bayes dump returned an error, please re-run with -D for more information\n"; } $spamtest->finish_learner(); # make sure we notice any write errors while flushing output buffer close STDOUT or die "error closing STDOUT: $!"; close STDIN or die "error closing STDIN: $!"; exit 0; } if ( defined $opt{'import'} ) { my $ret = $spamtest->{bayes_scanner}->{store}->perform_upgrade(); $spamtest->finish_learner(); # make sure we notice any write errors while flushing output buffer close STDOUT or die "error closing STDOUT: $!"; close STDIN or die "error closing STDIN: $!"; exit( !$ret ); } if (defined $opt{'clear'}) { unless ($spamtest->{bayes_scanner}->{store}->clear_database()) { $spamtest->finish_learner(); die "ERROR: Bayes clear returned an error, please re-run with -D for more information\n"; } $spamtest->finish_learner(); # make sure we notice any write errors while flushing output buffer close STDOUT or die "error closing STDOUT: $!"; close STDIN or die "error closing STDIN: $!"; exit 0; } if (defined $opt{'backup'}) { unless ($spamtest->{bayes_scanner}->{store}->backup_database()) { $spamtest->finish_learner(); die "ERROR: Bayes backup returned an error, please re-run with -D for more information\n"; } $spamtest->finish_learner(); # make sure we notice any write errors while flushing output buffer close STDOUT or die "error closing STDOUT: $!"; close STDIN or die "error closing STDIN: $!"; exit 0; } if (defined $opt{'restore'}) { my $filename = $opt{'restore'}; unless ($filename) { $spamtest->finish_learner(); die "ERROR: You must specify a filename to restore.\n"; } unless ($spamtest->{bayes_scanner}->{store}->restore_database($filename, $opt{'showdots'})) { $spamtest->finish_learner(); die "ERROR: Bayes restore returned an error, please re-run with -D for more information\n"; } $spamtest->finish_learner(); # make sure we notice any write errors while flushing output buffer close STDOUT or die "error closing STDOUT: $!"; close STDIN or die "error closing STDIN: $!"; exit 0; } if ( !$spamtest->{conf}->{use_bayes} ) { warn "ERROR: configuration specifies 'use_bayes 0', sa-learn disabled\n"; exit 1; } $spamtest->init_learner( { force_expire => $opt{'force-expire'}, learn_to_journal => $opt{'nosync'}, wait_for_lock => 1, caller_will_untie => 1 } ); $spamtest->{bayes_scanner}{use_ignores} = $opt{'use-ignores'}; if ($synconly) { $spamtest->rebuild_learner_caches( { verbose => 1, showdots => $opt{'showdots'} } ); $spamtest->finish_learner(); # make sure we notice any write errors while flushing output buffer close STDOUT or die "error closing STDOUT: $!"; close STDIN or die "error closing STDIN: $!"; exit 0; } $messagelimit = $opt{'stopafter'}; $learnprob = $opt{'learnprob'}; if ( defined $opt{'randseed'} ) { srand( $opt{'randseed'} ); } # sync the journal first if we're going to go r/w so we make sure to # learn everything before doing anything else. # if ( !$opt{nosync} ) { $spamtest->rebuild_learner_caches(); } # what is the result of the run? will end up being the exit code. my $exit_status = 0; # run this lot in an eval block, so we can catch die's and clear # up the dbs. eval { $SIG{HUP} = \&killed; $SIG{INT} = \&killed; $SIG{TERM} = \&killed; if ( $opt{folders} ) { open( F, $opt{folders} ) or die "cannot open $opt{folders}: $!"; for ($!=0; <F>; $!=0) { chomp; next if /^\s*$/; if (/^(?:ham|spam):\w*:/) { push ( @targets, $_ ); } else { target($_); } } defined $_ || $!==0 or $!==EBADF ? dbg("error reading from $opt{folders}: $!") : die "error reading from $opt{folders}: $!"; close(F) or die "error closing $opt{folders}: $!"; } ########################################################################### # Deal with the target listing, and STDIN -> tempfile my $tempfile; # will be defined if stdin -> tempfile push(@targets, @ARGV); @targets = ('-') unless @targets || $opt{folders}; for(my $elem = 0; $elem <= $#targets; $elem++) { # ArchiveIterator doesn't really like STDIN, so if "-" is specified # as a target, make it a temp file instead. if ( $targets[$elem] =~ /(?:^|:)-$/ ) { if (defined $tempfile) { # uh-oh, stdin specified multiple times? warn "skipping extra stdin target (".$targets[$elem].")\n"; splice @targets, $elem, 1; $elem--; # go back to this element again next; } else { my $handle; ( $tempfile, $handle ) = Mail::SpamAssassin::Util::secure_tmpfile(); binmode $handle or die "cannot set binmode on file $tempfile: $!"; # avoid slurping the whole file into memory, copy chunk by chunk my($inbuf,$nread); while ( $nread=sysread(STDIN,$inbuf,16384) ) { print {$handle} $inbuf or die "error writing to $tempfile: $!" } defined $nread or die "error reading from STDIN: $!"; close $handle or die "error closing $tempfile: $!"; # re-aim the targets at the tempfile instead of STDIN $targets[$elem] =~ s/-$/$tempfile/; } } # make sure the target list is in the normal AI format if ($targets[$elem] !~ /^[^:]*:[a-z]+:/) { my $item = splice @targets, $elem, 1; target($item); # add back to the list $elem--; # go back to this element again next; } } ########################################################################### my $iter = new Mail::SpamAssassin::ArchiveIterator( { # skip messages larger than max-size bytes, # 0 for no limit, undef defaults to 256 KiB 'opt_max_size' => $opt{'max-size'}, 'opt_want_date' => 0, 'opt_from_regex' => $spamtest->{conf}->{mbox_format_from_regex}, } ); $iter->set_functions(\&wanted, \&result); $messagecount = 0; $learnedcount = 0; $init_results = 0; $start_time = time; # if exit_status isn't already set to non-zero, set it to the reverse of the # run result (0 is bad, 1+ is good -- the opposite of exit status codes) my $run_ok = eval { $exit_status ||= ! $iter->run(@targets); 1 }; print STDERR "\n" if ($opt{showdots}); $progress->final() if ($opt{progress} && $progress); my $phrase = defined $forget ? "Forgot" : "Learned"; print "$phrase tokens from $learnedcount message(s) ($messagecount message(s) examined)\n"; # If we needed to make a tempfile, go delete it. if (defined $tempfile) { unlink $tempfile or die "cannot unlink temporary file $tempfile: $!"; undef $tempfile; } if (!$run_ok && $@ !~ /HITLIMIT/) { die $@ } 1; } or do { my $eval_stat = $@ ne '' ? $@ : "errno=$!"; chomp $eval_stat; $spamtest->finish_learner(); die $eval_stat; }; $spamtest->finish_learner(); # make sure we notice any write errors while flushing output buffer close STDOUT or die "error closing STDOUT: $!"; close STDIN or die "error closing STDIN: $!"; exit $exit_status; ########################################################################### sub killed { $spamtest->finish_learner(); die "interrupted"; } sub target { my ($target) = @_; my $class = ( $isspam ? "spam" : "ham" ); my $format = ( defined( $opt{'format'} ) ? $opt{'format'} : "detect" ); push ( @targets, "$class:$format:$target" ); } ########################################################################### sub init_results { $init_results = 1; return unless $opt{'progress'}; $total_messages = $Mail::SpamAssassin::ArchiveIterator::MESSAGES; $progress = Mail::SpamAssassin::Util::Progress->new({total => $total_messages,}); } ########################################################################### sub result { my ($class, $result, $time) = @_; # don't open results files until we get here to avoid overwriting files &init_results if !$init_results; $progress->update($messagecount) if ($opt{progress} && $progress); } ########################################################################### sub wanted { my ( $class, $id, $time, $dataref ) = @_; my $spam = $class eq "s" ? 1 : 0; if ( defined($learnprob) ) { if ( int( rand( 1 / $learnprob ) ) != 0 ) { print STDERR '_' if ( $opt{showdots} ); return 1; } } if ( defined($messagelimit) && $learnedcount > $messagelimit ) { $progress->final() if ($opt{progress} && $progress); die 'HITLIMIT'; } $messagecount++; my $ma = $spamtest->parse($dataref); if ( $ma->get_header("X-Spam-Checker-Version") ) { my $new_ma = $spamtest->parse($spamtest->remove_spamassassin_markup($ma), 1); $ma->finish(); $ma = $new_ma; } my $status = $spamtest->learn( $ma, undef, $spam, $forget ); my $learned = $status->did_learn(); if ( !defined $learned ) { # undef=learning unavailable die "ERROR: the Bayes learn function returned an error, please re-run with -D for more information\n"; } elsif ( $learned == 1 ) { # 1=message was learned. 0=message wasn't learned $learnedcount++; } # Do cleanup ... $status->finish(); undef $status; $ma->finish(); undef $ma; print STDERR '.' if ( $opt{showdots} ); return 1; } ########################################################################### sub usage { my ( $verbose, $message ) = @_; my $ver = Mail::SpamAssassin::Version(); print "SpamAssassin version $ver\n"; pod2usage( -verbose => $verbose, -message => $message, -exitval => 64 ); } # --------------------------------------------------------------------------- =head1 NAME sa-learn - train SpamAssassin's Bayesian classifier =head1 SYNOPSIS B<sa-learn> [options] [file]... B<sa-learn> [options] --dump [ all | data | magic ] Options: --ham Learn messages as ham (non-spam) --spam Learn messages as spam --forget Forget a message --use-ignores Use bayes_ignore_from and bayes_ignore_to --sync Synchronize the database and the journal if needed --force-expire Force a database sync and expiry run --dbpath <path> Allows commandline override (in bayes_path form) for where to read the Bayes DB from --dump [all|data|magic] Display the contents of the Bayes database Takes optional argument for what to display --regexp <re> For dump only, specifies which tokens to dump based on a regular expression. -f file, --folders=file Read list of files/directories from file --dir Ignored; historical compatibility --file Ignored; historical compatibility --mbox Input sources are in mbox format --mbx Input sources are in mbx format --max-size <b> Skip messages larger than b bytes; defaults to 256 KiB, 0 implies no limit --showdots Show progress using dots --progress Show progress using progress bar --no-sync Skip synchronizing the database and journal after learning -L, --local Operate locally, no network accesses --import Migrate data from older version/non DB_File based databases --clear Wipe out existing database --backup Backup, to STDOUT, existing database --restore <filename> Restore a database from filename -u username, --username=username Override username taken from the runtime environment, used with SQL -C path, --configpath=path, --config-file=path Path to standard configuration dir -p prefs, --prefspath=file, --prefs-file=file Set user preferences file --siteconfigpath=path Path for site configs (default: /etc/mail/spamassassin) --cf='config line' Additional line of configuration -D, --debug [area=n,...] Print debugging messages -V, --version Print version -h, --help Print usage message =head1 DESCRIPTION Given a typical selection of your incoming mail classified as spam or ham (non-spam), this tool will feed each mail to SpamAssassin, allowing it to 'learn' what signs are likely to mean spam, and which are likely to mean ham. Simply run this command once for each of your mail folders, and it will ''learn'' from the mail therein. Note that csh-style I<globbing> in the mail folder names is supported; in other words, listing a folder name as C<*> will scan every folder that matches. See C<Mail::SpamAssassin::ArchiveIterator> for more details. SpamAssassin remembers which mail messages it has learnt already, and will not re-learn those messages again, unless you use the B<--forget> option. Messages learnt as spam will have SpamAssassin markup removed, on the fly. If you make a mistake and scan a mail as ham when it is spam, or vice versa, simply rerun this command with the correct classification, and the mistake will be corrected. SpamAssassin will automatically 'forget' the previous indications. Users of C<spamd> who wish to perform training remotely, over a network, should investigate the C<spamc -L> switch. =head1 OPTIONS =over 4 =item B<--ham> Learn the input message(s) as ham. If you have previously learnt any of the messages as spam, SpamAssassin will forget them first, then re-learn them as ham. Alternatively, if you have previously learnt them as ham, it'll skip them this time around. If the messages have already been filtered through SpamAssassin, the learner will ignore any modifications SpamAssassin may have made. =item B<--spam> Learn the input message(s) as spam. If you have previously learnt any of the messages as ham, SpamAssassin will forget them first, then re-learn them as spam. Alternatively, if you have previously learnt them as spam, it'll skip them this time around. If the messages have already been filtered through SpamAssassin, the learner will ignore any modifications SpamAssassin may have made. =item B<--folders>=I<filename>, B<-f> I<filename> sa-learn will read in the list of folders from the specified file, one folder per line in the file. If the folder is prefixed with C<ham:type:> or C<spam:type:>, sa-learn will learn that folder appropriately, otherwise the folders will be assumed to be of the type specified by B<--ham> or B<--spam>. C<type> above is optional, but is the same as the standard for ArchiveIterator: mbox, mbx, dir, file, or detect (the default if not specified). =item B<--mbox> sa-learn will read in the file(s) containing the emails to be learned, and will process them in mbox format (one or more emails per file). =item B<--mbx> sa-learn will read in the file(s) containing the emails to be learned, and will process them in mbx format (one or more emails per file). =item B<--use-ignores> Don't learn the message if a from address matches configuration file item C<bayes_ignore_from> or a to address matches C<bayes_ignore_to>. The option might be used when learning from a large file of messages from which the hammy spam messages or spammy ham messages have not been removed. =item B<--sync> Synchronize the journal and databases. Upon successfully syncing the database with the entries in the journal, the journal file is removed. =item B<--force-expire> Forces an expiry attempt, regardless of whether it may be necessary or not. Note: This doesn't mean any tokens will actually expire. Please see the EXPIRATION section below. Note: C<--force-expire> also causes the journal data to be synchronized into the Bayes databases. =item B<--forget> Forget a given message previously learnt. =item B<--dbpath> Allows a commandline override of the I<bayes_path> configuration option. =item B<--dump> I<option> Display the contents of the Bayes database. Without an option or with the I<all> option, all magic tokens and data tokens will be displayed. I<magic> will only display magic tokens, and I<data> will only display the data tokens. Can also use the B<--regexp> I<RE> option to specify which tokens to display based on a regular expression. =item B<--clear> Clear an existing Bayes database by removing all traces of the database. WARNING: This is destructive and should be used with care. =item B<--backup> Performs a dump of the Bayes database in machine/human readable format. The dump will include token and seen data. It is suitable for input back into the --restore command. =item B<--restore>=I<filename> Performs a restore of the Bayes database defined by I<filename>. WARNING: This is a destructive operation, previous Bayes data will be wiped out. =item B<-h>, B<--help> Print help message and exit. =item B<-u> I<username>, B<--username>=I<username> If specified this username will override the username taken from the runtime environment. You can use this option to specify users in a virtual user configuration when using SQL as the Bayes backend. NOTE: This option will not change to the given I<username>, it will only attempt to act on behalf of that user. Because of this you will need to have proper permissions to be able to change files owned by I<username>. In the case of SQL this generally is not a problem. =item B<-C> I<path>, B<--configpath>=I<path>, B<--config-file>=I<path> Use the specified path for locating the distributed configuration files. Ignore the default directories (usually C</usr/share/spamassassin> or similar). =item B<--siteconfigpath>=I<path> Use the specified path for locating site-specific configuration files. Ignore the default directories (usually C</etc/mail/spamassassin> or similar). =item B<--cf='config line'> Add additional lines of configuration directly from the command-line, parsed after the configuration files are read. Multiple B<--cf> arguments can be used, and each will be considered a separate line of configuration. =item B<-p> I<prefs>, B<--prefspath>=I<prefs>, B<--prefs-file>=I<prefs> Read user score preferences from I<prefs> (usually C<$HOME/.spamassassin/user_prefs>). =item B<--progress> Prints a progress bar (to STDERR) showing the current progress. In the case where no valid terminal is found this option will behave very much like the --showdots option. =item B<-D> [I<area,...>], B<--debug> [I<area,...>] Produce debugging output. If no areas are listed, all debugging information is printed. Diagnostic output can also be enabled for each area individually; I<area> is the area of the code to instrument. For example, to produce diagnostic output on bayes, learn, and dns, use: spamassassin -D bayes,learn,dns For more information about which areas (also known as channels) are available, please see the documentation at: C<http://wiki.apache.org/spamassassin/DebugChannels> Higher priority informational messages that are suitable for logging in normal circumstances are available with an area of "info". =item B<--no-sync> Skip the slow synchronization step which normally takes place after changing database entries. If you plan to learn from many folders in a batch, or to learn many individual messages one-by-one, it is faster to use this switch and run C<sa-learn --sync> once all the folders have been scanned. Clarification: The state of I<--no-sync> overrides the I<bayes_learn_to_journal> configuration option. If not specified, sa-learn will learn to the database directly. If specified, sa-learn will learn to the journal file. Note: I<--sync> and I<--no-sync> can be specified on the same commandline, which is slightly confusing. In this case, the I<--no-sync> option is ignored since there is no learn operation. =item B<-L>, B<--local> Do not perform any network accesses while learning details about the mail messages. This will speed up the learning process, but may result in a slightly lower accuracy. Note that this is currently ignored, as current versions of SpamAssassin will not perform network access while learning; but future versions may. =item B<--import> If you previously used SpamAssassin's Bayesian learner without the C<DB_File> module installed, it will have created files in other formats, such as C<GDBM_File>, C<NDBM_File>, or C<SDBM_File>. This switch allows you to migrate that old data into the C<DB_File> format. It will overwrite any data currently in the C<DB_File>. Can also be used with the B<--dbpath> I<path> option to specify the location of the Bayes files to use. =back =head1 MIGRATION There are now multiple backend storage modules available for storing user's bayesian data. As such you might want to migrate from one backend to another. Here is a simple procedure for migrating from one backend to another. Note that if you have individual user databases you will have to perform a similar procedure for each one of them. =over 4 =item sa-learn --sync This will sync any outstanding journal entries =item sa-learn --backup > backup.txt This will save all your Bayes data to a plain text file. =item sa-learn --clear This is optional, but good to do to clear out the old database. =item Repeat! At this point, if you have multiple databases, you should perform the procedure above for each of them. (i.e. each user's database needs to be backed up before continuing.) =item Switch backends Once you have backed up all databases you can update your configuration for the new database backend. This will involve at least the bayes_store_module config option and may involve some additional config options depending on what is required by the module. (For example, you may need to configure an SQL database.) =item sa-learn --restore backup.txt Again, you need to do this for every database. =back If you are migrating to SQL you can make use of the -u <username> option in sa-learn to populate each user's database. Otherwise, you must run sa-learn as the user who database you are restoring. =head1 INTRODUCTION TO BAYESIAN FILTERING (Thanks to Michael Bell for this section!) For a more lengthy description of how this works, go to http://www.paulgraham.com/ and see "A Plan for Spam". It's reasonably readable, even if statistics make me break out in hives. The short semi-inaccurate version: Given training, a spam heuristics engine can take the most "spammy" and "hammy" words and apply probabilistic analysis. Furthermore, once given a basis for the analysis, the engine can continue to learn iteratively by applying both the non-Bayesian and Bayesian rulesets together to create evolving "intelligence". SpamAssassin 2.50 and later supports Bayesian spam analysis, in the form of the BAYES rules. This is a new feature, quite powerful, and is disabled until enough messages have been learnt. The pros of Bayesian spam analysis: =over 4 =item Can greatly reduce false positives and false negatives. It learns from your mail, so it is tailored to your unique e-mail flow. =item Once it starts learning, it can continue to learn from SpamAssassin and improve over time. =back And the cons: =over 4 =item A decent number of messages are required before results are useful for ham/spam determination. =item It's hard to explain why a message is or isn't marked as spam. i.e.: a straightforward rule, that matches, say, "VIAGRA" is easy to understand. If it generates a false positive or false negative, it is fairly easy to understand why. With Bayesian analysis, it's all probabilities - "because the past says it is likely as this falls into a probabilistic distribution common to past spam in your systems". Tell that to your users! Tell that to the client when he asks "what can I do to change this". (By the way, the answer in this case is "use whitelisting".) =item It will take disk space and memory. The databases it maintains take quite a lot of resources to store and use. =back =head1 GETTING STARTED Still interested? Ok, here's the guidelines for getting this working. First a high-level overview: =over 4 =item Build a significant sample of both ham and spam. I suggest several thousand of each, placed in SPAM and HAM directories or mailboxes. Yes, you MUST hand-sort this - otherwise the results won't be much better than SpamAssassin on its own. Verify the spamminess/haminess of EVERY message. You're urged to avoid using a publicly available corpus (sample) - this must be taken from YOUR mail server, if it is to be statistically useful. Otherwise, the results may be pretty skewed. =item Use this tool to teach SpamAssassin about these samples, like so: sa-learn --spam /path/to/spam/folder sa-learn --ham /path/to/ham/folder ... Let SpamAssassin proceed, learning stuff. When it finds ham and spam it will add the "interesting tokens" to the database. =item If you need SpamAssassin to forget about specific messages, use the B<--forget> option. This can be applied to either ham or spam that has run through the B<sa-learn> processes. It's a bit of a hammer, really, lowering the weighting of the specific tokens in that message (only if that message has been processed before). =item Learning from single messages uses a command like this: sa-learn --ham --no-sync mailmessage This is handy for binding to a key in your mail user agent. It's very fast, as all the time-consuming stuff is deferred until you run with the C<--sync> option. =item Autolearning is enabled by default If you don't have a corpus of mail saved to learn, you can let SpamAssassin automatically learn the mail that you receive. If you are autolearning from scratch, the amount of mail you receive will determine how long until the BAYES_* rules are activated. =back =head1 EFFECTIVE TRAINING Learning filters require training to be effective. If you don't train them, they won't work. In addition, you need to train them with new messages regularly to keep them up-to-date, or their data will become stale and impact accuracy. You need to train with both spam I<and> ham mails. One type of mail alone will not have any effect. Note that if your mail folders contain things like forwarded spam, discussions of spam-catching rules, etc., this will cause trouble. You should avoid scanning those messages if possible. (An easy way to do this is to move them aside, into a folder which is not scanned.) If the messages you are learning from have already been filtered through SpamAssassin, the learner will compensate for this. In effect, it learns what each message would look like if you had run C<spamassassin -d> over it in advance. Another thing to be aware of, is that typically you should aim to train with at least 1000 messages of spam, and 1000 ham messages, if possible. More is better, but anything over about 5000 messages does not improve accuracy significantly in our tests. Be careful that you train from the same source -- for example, if you train on old spam, but new ham mail, then the classifier will think that a mail with an old date stamp is likely to be spam. It's also worth noting that training with a very small quantity of ham, will produce atrocious results. You should aim to train with at least the same amount (or more if possible!) of ham data than spam. On an on-going basis, it is best to keep training the filter to make sure it has fresh data to work from. There are various ways to do this: =over 4 =item 1. Supervised learning This means keeping a copy of all or most of your mail, separated into spam and ham piles, and periodically re-training using those. It produces the best results, but requires more work from you, the user. (An easy way to do this, by the way, is to create a new folder for 'deleted' messages, and instead of deleting them from other folders, simply move them in there instead. Then keep all spam in a separate folder and never delete it. As long as you remember to move misclassified mails into the correct folder set, it is easy enough to keep up to date.) =item 2. Unsupervised learning from Bayesian classification Another way to train is to chain the results of the Bayesian classifier back into the training, so it reinforces its own decisions. This is only safe if you then retrain it based on any errors you discover. SpamAssassin does not support this method, due to experimental results which strongly indicate that it does not work well, and since Bayes is only one part of the resulting score presented to the user (while Bayes may have made the wrong decision about a mail, it may have been overridden by another system). =item 3. Unsupervised learning from SpamAssassin rules Also called 'auto-learning' in SpamAssassin. Based on statistical analysis of the SpamAssassin success rates, we can automatically train the Bayesian database with a certain degree of confidence that our training data is accurate. It should be supplemented with some supervised training in addition, if possible. This is the default, but can be turned off by setting the SpamAssassin configuration parameter C<bayes_auto_learn> to 0. =item 4. Mistake-based training This means training on a small number of mails, then only training on messages that SpamAssassin classifies incorrectly. This works, but it takes longer to get it right than a full training session would. =back =head1 FILES B<sa-learn> and the other parts of SpamAssassin's Bayesian learner, use a set of persistent database files to store the learnt tokens, as follows. =over 4 =item bayes_toks The database of tokens, containing the tokens learnt, their count of occurrences in ham and spam, and the timestamp when the token was last seen in a message. This database also contains some 'magic' tokens, as follows: the version number of the database, the number of ham and spam messages learnt, the number of tokens in the database, and timestamps of: the last journal sync, the last expiry run, the last expiry token reduction count, the last expiry timestamp delta, the oldest token timestamp in the database, and the newest token timestamp in the database. This is a database file, using C<DB_File>. The database 'version number' is 0 for databases from 2.5x, 1 for databases from certain 2.6x development releases, 2 for 2.6x, and 3 for 3.0 and later releases. =item bayes_seen A map of Message-Id and some data from headers and body to what that message was learnt as. This is used so that SpamAssassin can avoid re-learning a message it has already seen, and so it can reverse the training if you later decide that message was learnt incorrectly. This is a database file, using C<DB_File>. =item bayes_journal While SpamAssassin is scanning mails, it needs to track which tokens it uses in its calculations. To avoid the contention of having each SpamAssassin process attempting to gain write access to the Bayes DB, the token timestamps are written to a 'journal' file which will later (either automatically or via C<sa-learn --sync>) be used to synchronize the Bayes DB. Also, through the use of C<bayes_learn_to_journal>, or when using the C<--no-sync> option with sa-learn, the actual learning data will take be placed into the journal for later synchronization. This is typically useful for high-traffic sites to avoid the same contention as stated above. =back =head1 EXPIRATION Since SpamAssassin can auto-learn messages, the Bayes database files could increase perpetually until they fill your disk. To control this, SpamAssassin performs journal synchronization and bayes expiration periodically when certain criteria (listed below) are met. SpamAssassin can sync the journal and expire the DB tokens either manually or opportunistically. A journal sync is due if I<--sync> is passed to sa-learn (manual), or if the following is true (opportunistic): =over 4 =item - bayes_journal_max_size does not equal 0 (means don't sync) =item - the journal file exists =back and either: =over 4 =item - the journal file has a size greater than bayes_journal_max_size =back or =over 4 =item - a journal sync has previously occurred, and at least 1 day has passed since that sync =back Expiry is due if I<--force-expire> is passed to sa-learn (manual), or if all of the following are true (opportunistic): =over 4 =item - the last expire was attempted at least 12hrs ago =item - bayes_auto_expire does not equal 0 =item - the number of tokens in the DB is > 100,000 =item - the number of tokens in the DB is > bayes_expiry_max_db_size =item - there is at least a 12 hr difference between the oldest and newest token atimes =back =head2 EXPIRE LOGIC If either the manual or opportunistic method causes an expire run to start, here is the logic that is used: =over 4 =item - figure out how many tokens to keep. take the larger of either bayes_expiry_max_db_size * 75% or 100,000 tokens. therefore, the goal reduction is number of tokens - number of tokens to keep. =item - if the reduction number is < 1000 tokens, abort (not worth the effort). =item - if an expire has been done before, guesstimate the new atime delta based on the old atime delta. (new_atime_delta = old_atime_delta * old_reduction_count / goal) =item - if no expire has been done before, or the last expire looks "weird", do an estimation pass. The definition of "weird" is: =over 8 =item - last expire over 30 days ago =item - last atime delta was < 12 hrs =item - last reduction count was < 1000 tokens =item - estimated new atime delta is < 12 hrs =item - the difference between the last reduction count and the goal reduction count is > 50% =back =back =head2 ESTIMATION PASS LOGIC Go through each of the DB's tokens. Starting at 12hrs, calculate whether or not the token would be expired (based on the difference between the token's atime and the db's newest token atime) and keep the count. Work out from 12hrs exponentially by powers of 2. ie: 12hrs * 1, 12hrs * 2, 12hrs * 4, 12hrs * 8, and so on, up to 12hrs * 512 (6144hrs, or 256 days). The larger the delta, the smaller the number of tokens that will be expired. Conversely, the number of tokens goes up as the delta gets smaller. So starting at the largest atime delta, figure out which delta will expire the most tokens without going above the goal expiration count. Use this to choose the atime delta to use, unless one of the following occurs: =over 8 =item - the largest atime (smallest reduction count) would expire too many tokens. this means the learned tokens are mostly old and there needs to be new tokens learned before an expire can occur. =item - all of the atime choices result in 0 tokens being removed. this means the tokens are all newer than 12 hours and there needs to be new tokens learned before an expire can occur. =item - the number of tokens that would be removed is < 1000. the benefit isn't worth the effort. more tokens need to be learned. =back If the expire run gets past this point, it will continue to the end. A new DB is created since the majority of DB libraries don't shrink the DB file when tokens are removed. So we do the "create new, migrate old to new, remove old, rename new" shuffle. =head2 EXPIRY RELATED CONFIGURATION SETTINGS =over 4 =item C<bayes_auto_expire> is used to specify whether or not SpamAssassin ought to opportunistically attempt to expire the Bayes database. The default is 1 (yes). =item C<bayes_expiry_max_db_size> specifies both the auto-expire token count point, as well as the resulting number of tokens after expiry as described above. The default value is 150,000, which is roughly equivalent to a 6Mb database file if you're using DB_File. =item C<bayes_journal_max_size> specifies how large the Bayes journal will grow before it is opportunistically synced. The default value is 102400. =back =head1 INSTALLATION The B<sa-learn> command is part of the B<Mail::SpamAssassin> Perl module. Install this as a normal Perl module, using C<perl -MCPAN -e shell>, or by hand. =head1 SEE ALSO spamassassin(1) spamc(1) Mail::SpamAssassin(3) Mail::SpamAssassin::ArchiveIterator(3) E<lt>http://www.paulgraham.com/E<gt> Paul Graham's "A Plan For Spam" paper E<lt>http://www.linuxjournal.com/article/6467E<gt> Gary Robinson's f(x) and combining algorithms, as used in SpamAssassin E<lt>http://www.bgl.nu/~glouis/bogofilter/E<gt> 'Training on error' page. A discussion of various Bayes training regimes, including 'train on error' and unsupervised training. =head1 PREREQUISITES C<Mail::SpamAssassin> =head1 AUTHORS The SpamAssassin(tm) Project E<lt>http://spamassassin.apache.org/E<gt> =cut
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