1 RRDCREATE(1) rrdtool RRDCREATE(1)
6 rrdcreate - Set up a new Round Robin Database
9 r\brr\brd\bdt\bto\boo\bol\bl c\bcr\bre\bea\bat\bte\be _\bf_\bi_\bl_\be_\bn_\ba_\bm_\be [-\b--\b-s\bst\bta\bar\brt\bt|-\b-b\bb _\bs_\bt_\ba_\br_\bt _\bt_\bi_\bm_\be] [-\b--\b-s\bst\bte\bep\bp|-\b-s\bs _\bs_\bt_\be_\bp]
10 [-\b--\b-n\bno\bo-\b-o\bov\bve\ber\brw\bwr\bri\bit\bte\be] [D\bDS\bS:\b:_\bd_\bs_\b-_\bn_\ba_\bm_\be:\b:_\bD_\bS_\bT:\b:_\bd_\bs_\bt _\ba_\br_\bg_\bu_\bm_\be_\bn_\bt_\bs] [R\bRR\bRA\bA:\b:_\bC_\bF:\b:_\bc_\bf _\ba_\br_\bg_\bu_\bm_\be_\bn_\bt_\bs]
13 The create function of RRDtool lets you set up new Round Robin Database
21 -\b--\b-s\bst\bta\bar\brt\bt|\b|-\b-b\bb _\bs_\bt_\ba_\br_\bt _\bt_\bi_\bm_\be (\b(d\bde\bef\bfa\bau\bul\blt\bt:\b: n\bno\bow\bw -\b- 1\b10\b0s\bs)\b)
22 Specifies the time in seconds since 1970-01-01 UTC when the first value
24 before or at the time specified.
27 documentation for other ways to specify time.
29 -\b--\b-s\bst\bte\bep\bp|\b|-\b-s\bs _\bs_\bt_\be_\bp (\b(d\bde\bef\bfa\bau\bul\blt\bt:\b: 3\b30\b00\b0 s\bse\bec\bco\bon\bnd\bds\bs)\b)
30 Specifies the base interval in seconds with which data will be fed into
34 Do not clobber an existing file of the same name.
36 D\bDS\bS:\b:_\bd_\bs_\b-_\bn_\ba_\bm_\be:\b:_\bD_\bS_\bT:\b:_\bd_\bs_\bt _\ba_\br_\bg_\bu_\bm_\be_\bn_\bt_\bs
38 example incoming and outgoing traffic on a specific communication line.
43 source from an R\bRR\bRD\bD. A _\bd_\bs_\b-_\bn_\ba_\bm_\be must be 1 to 19 characters long in the
44 characters [a-zA-Z0-9_].
47 source entry depend on the data source type. For GAUGE, COUNTER,
48 DERIVE, and ABSOLUTE the format for a data source entry is:
50 D\bDS\bS:\b:_\bd_\bs_\b-_\bn_\ba_\bm_\be:\b:_\bG_\bA_\bU_\bG_\bE _\b| _\bC_\bO_\bU_\bN_\bT_\bE_\bR _\b| _\bD_\bE_\bR_\bI_\bV_\bE _\b| _\bA_\bB_\bS_\bO_\bL_\bU_\bT_\bE:\b:_\bh_\be_\ba_\br_\bt_\bb_\be_\ba_\bt:\b:_\bm_\bi_\bn:\b:_\bm_\ba_\bx
52 For COMPUTE data sources, the format is:
54 D\bDS\bS:\b:_\bd_\bs_\b-_\bn_\ba_\bm_\be:\b:_\bC_\bO_\bM_\bP_\bU_\bT_\bE:\b:_\br_\bp_\bn_\b-_\be_\bx_\bp_\br_\be_\bs_\bs_\bi_\bo_\bn
56 In order to decide which data source type to use, review the
57 definitions that follow. Also consult the section on "HOW TO MEASURE"
58 for further insight.
61 is for things like temperatures or number of people in a room or
62 the value of a RedHat share.
65 is for continuous incrementing counters like the ifInOctets counter
67 decreases, except when a counter overflows. The update function
68 takes the overflow into account. The counter is stored as a per-
69 second rate. When the counter overflows, RRDtool checks if the
70 overflow happened at the 32bit or 64bit border and acts accordingly
71 by adding an appropriate value to the result.
74 will store the derivative of the line going from the last to the
75 current value of the data source. This can be useful for gauges,
76 for example, to measure the rate of people entering or leaving a
77 room. Internally, derive works exactly like COUNTER but without
78 overflow checks. So if your counter does not reset at 32 or 64 bit
79 you might want to use DERIVE and combine it with a MIN value of 0.
83 by Don Baarda <don.baarda@baesystems.com>
85 If you cannot tolerate ever mistaking the occasional counter reset
86 for a legitimate counter wrap, and would prefer "Unknowns" for all
87 legitimate counter wraps and resets, always use DERIVE with min=0.
88 Otherwise, using COUNTER with a suitable max will return correct
89 values for all legitimate counter wraps, mark some counter resets
90 as "Unknown", but can mistake some counter resets for a legitimate
91 counter wrap.
93 For a 5 minute step and 32-bit counter, the probability of
94 mistaking a counter reset for a legitimate wrap is arguably about
95 0.8% per 1Mbps of maximum bandwidth. Note that this equates to 80%
96 for 100Mbps interfaces, so for high bandwidth interfaces and a
97 32bit counter, DERIVE with min=0 is probably preferable. If you are
98 using a 64bit counter, just about any max setting will eliminate
99 the possibility of mistaking a reset for a counter wrap.
102 is for counters which get reset upon reading. This is used for fast
103 counters which tend to overflow. So instead of reading them
104 normally you reset them after every read to make sure you have a
105 maximum time available before the next overflow. Another usage is
106 for things you count like number of messages since the last update.
109 is for storing the result of a formula applied to other data
111 update, but rather its Primary Data Points (PDPs) are computed from
112 the PDPs of the data sources according to the rpn-expression that
113 defines the formula. Consolidation functions are then applied
114 normally to the PDPs of the COMPUTE data source (that is the rpn-
115 expression is only applied to generate PDPs). In database software,
116 such data sets are referred to as "virtual" or "computed" columns.
118 _\bh_\be_\ba_\br_\bt_\bb_\be_\ba_\bt defines the maximum number of seconds that may pass between
119 two updates of this data source before the value of the data source is
124 defined range will be regarded as _\b*_\bU_\bN_\bK_\bN_\bO_\bW_\bN_\b*. If you do not know or care
125 about min and max, set them to U for unknown. Note that min and max
127 type DS this would be the maximum and minimum data-rate expected from
128 the device.
130 _\bI_\bf _\bi_\bn_\bf_\bo_\br_\bm_\ba_\bt_\bi_\bo_\bn _\bo_\bn _\bm_\bi_\bn_\bi_\bm_\ba_\bl_\b/_\bm_\ba_\bx_\bi_\bm_\ba_\bl _\be_\bx_\bp_\be_\bc_\bt_\be_\bd _\bv_\ba_\bl_\bu_\be_\bs _\bi_\bs _\ba_\bv_\ba_\bi_\bl_\ba_\bb_\bl_\be_\b, _\ba_\bl_\bw_\ba_\by_\bs
131 _\bs_\be_\bt _\bt_\bh_\be _\bm_\bi_\bn _\ba_\bn_\bd_\b/_\bo_\br _\bm_\ba_\bx _\bp_\br_\bo_\bp_\be_\br_\bt_\bi_\be_\bs_\b. _\bT_\bh_\bi_\bs _\bw_\bi_\bl_\bl _\bh_\be_\bl_\bp _\bR_\bR_\bD_\bt_\bo_\bo_\bl _\bi_\bn _\bd_\bo_\bi_\bn_\bg _\ba
132 _\bs_\bi_\bm_\bp_\bl_\be _\bs_\ba_\bn_\bi_\bt_\by _\bc_\bh_\be_\bc_\bk _\bo_\bn _\bt_\bh_\be _\bd_\ba_\bt_\ba _\bs_\bu_\bp_\bp_\bl_\bi_\be_\bd _\bw_\bh_\be_\bn _\br_\bu_\bn_\bn_\bi_\bn_\bg _\bu_\bp_\bd_\ba_\bt_\be_\b.
134 _\br_\bp_\bn_\b-_\be_\bx_\bp_\br_\be_\bs_\bs_\bi_\bo_\bn defines the formula used to compute the PDPs of a
135 COMPUTE data source from other data sources in the same <RRD>. It is
137 to that manual page for a list and description of RPN operations
138 supported. For COMPUTE data sources, the following RPN operations are
139 not supported: COUNT, PREV, TIME, and LTIME. In addition, in defining
140 the RPN expression, the COMPUTE data source may only refer to the names
141 of data source listed previously in the create command. This is similar
142 to the restriction that C\bCD\bDE\bEF\bFs must refer only to D\bDE\bEF\bFs and C\bCD\bDE\bEF\bFs
143 previously defined in the same graph command.
151 the length defined with the -\b-s\bs option, thus becoming a _\bp_\br_\bi_\bm_\ba_\br_\by _\bd_\ba_\bt_\ba
155 archive. There are several consolidation functions that consolidate
156 primary data points via an aggregate function: A\bAV\bVE\bER\bRA\bAG\bGE\bE, M\bMI\bIN\bN, M\bMA\bAX\bX, L\bLA\bAS\bST\bT.
158 AVERAGE
159 the average of the data points is stored.
161 MIN the smallest of the data points is stored.
163 MAX the largest of the data points is stored.
165 LAST
166 the last data points is used.
168 Note that data aggregation inevitably leads to loss of precision and
169 information. The trick is to pick the aggregate function such that the
170 _\bi_\bn_\bt_\be_\br_\be_\bs_\bt_\bi_\bn_\bg properties of your data is kept across the aggregation
171 process.
175 R\bRR\bRA\bA:\b:_\bA_\bV_\bE_\bR_\bA_\bG_\bE _\b| _\bM_\bI_\bN _\b| _\bM_\bA_\bX _\b| _\bL_\bA_\bS_\bT:\b:_\bx_\bf_\bf:\b:_\bs_\bt_\be_\bp_\bs:\b:_\br_\bo_\bw_\bs
179 regarded as known. It is given as the ratio of allowed _\b*_\bU_\bN_\bK_\bN_\bO_\bW_\bN_\b* PDPs
180 to the number of PDPs in the interval. Thus, it ranges from 0 to 1
181 (exclusive).
183 _\bs_\bt_\be_\bp_\bs defines how many of these _\bp_\br_\bi_\bm_\ba_\br_\by _\bd_\ba_\bt_\ba _\bp_\bo_\bi_\bn_\bt_\bs are used to build a
184 _\bc_\bo_\bn_\bs_\bo_\bl_\bi_\bd_\ba_\bt_\be_\bd _\bd_\ba_\bt_\ba _\bp_\bo_\bi_\bn_\bt which then goes into the archive.
187 Obviously, this has to be greater than zero.
189 A\bAb\bbe\ber\brr\bra\ban\bnt\bt B\bBe\beh\bha\bav\bvi\bio\bor\br D\bDe\bet\bte\bec\bct\bti\bio\bon\bn w\bwi\bit\bth\bh H\bHo\bol\blt\bt-\b-W\bWi\bin\bnt\bte\ber\brs\bs F\bFo\bor\bre\bec\bca\bas\bst\bti\bin\bng\bg
190 In addition to the aggregate functions, there are a set of specialized
192 Winters forecasting algorithm), confidence bands, and the flagging
193 aberrant behavior in the data source time series:
195 · R\bRR\bRA\bA:\b:_\bH_\bW_\bP_\bR_\bE_\bD_\bI_\bC_\bT:\b:_\br_\bo_\bw_\bs:\b:_\ba_\bl_\bp_\bh_\ba:\b:_\bb_\be_\bt_\ba:\b:_\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd[:\b:_\br_\br_\ba_\b-_\bn_\bu_\bm]
197 · R\bRR\bRA\bA:\b:_\bM_\bH_\bW_\bP_\bR_\bE_\bD_\bI_\bC_\bT:\b:_\br_\bo_\bw_\bs:\b:_\ba_\bl_\bp_\bh_\ba:\b:_\bb_\be_\bt_\ba:\b:_\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd[:\b:_\br_\br_\ba_\b-_\bn_\bu_\bm]
199 · R\bRR\bRA\bA:\b:_\bS_\bE_\bA_\bS_\bO_\bN_\bA_\bL:\b:_\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd:\b:_\bg_\ba_\bm_\bm_\ba:\b:_\br_\br_\ba_\b-
200 _\bn_\bu_\bm[:\b:s\bsm\bmo\boo\bot\bth\bhi\bin\bng\bg-\b-w\bwi\bin\bnd\bdo\bow\bw=\b=_\bf_\br_\ba_\bc_\bt_\bi_\bo_\bn]
202 · R\bRR\bRA\bA:\b:_\bD_\bE_\bV_\bS_\bE_\bA_\bS_\bO_\bN_\bA_\bL:\b:_\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd:\b:_\bg_\ba_\bm_\bm_\ba:\b:_\br_\br_\ba_\b-
203 _\bn_\bu_\bm[:\b:s\bsm\bmo\boo\bot\bth\bhi\bin\bng\bg-\b-w\bwi\bin\bnd\bdo\bow\bw=\b=_\bf_\br_\ba_\bc_\bt_\bi_\bo_\bn]
205 · R\bRR\bRA\bA:\b:_\bD_\bE_\bV_\bP_\bR_\bE_\bD_\bI_\bC_\bT:\b:_\br_\bo_\bw_\bs:\b:_\br_\br_\ba_\b-_\bn_\bu_\bm
207 · R\bRR\bRA\bA:\b:_\bF_\bA_\bI_\bL_\bU_\bR_\bE_\bS:\b:_\br_\bo_\bw_\bs:\b:_\bt_\bh_\br_\be_\bs_\bh_\bo_\bl_\bd:\b:_\bw_\bi_\bn_\bd_\bo_\bw _\bl_\be_\bn_\bg_\bt_\bh:\b:_\br_\br_\ba_\b-_\bn_\bu_\bm
212 confidence bounds, a matched set of SEASONAL, DEVSEASONAL, DEVPREDICT,
213 and either HWPREDICT or MHWPREDICT must exist. Generating smoothed
216 FAILURES, DEVSEASONAL, SEASONAL, and either HWPREDICT or MHWPREDICT.
218 The predicted, or smoothed, values are stored in the HWPREDICT or
220 the Holt-Winters method. They are interchangeable. Both attempt to
221 decompose data into three components: a baseline, a trend, and a
222 seasonal coefficient. HWPREDICT adds its seasonal coefficient to the
223 baseline to form a prediction, whereas MHWPREDICT multiplies its
224 seasonal coefficient by the baseline to form a prediction. The
225 difference is noticeable when the baseline changes significantly in the
226 course of a season; HWPREDICT will predict the seasonality to stay
227 constant as the baseline changes, but MHWPREDICT will predict the
228 seasonality to grow or shrink in proportion to the baseline. The proper
229 choice of method depends on the thing being modeled. For simplicity,
230 the rest of this discussion will refer to HWPREDICT, but MHWPREDICT may
231 be substituted in its place.
233 The predicted deviations are stored in DEVPREDICT (think a standard
234 deviation which can be scaled to yield a confidence band). The FAILURES
236 failure; that is, the number of confidence bounds violations in the
237 preceding window of observations met or exceeded a specified threshold.
239 appears in rrdgraph.
242 the Holt-Winters forecasting algorithm and the seasonal deviations,
243 respectively. There is one entry per observation time point in the
244 seasonal cycle. For example, if primary data points are generated every
245 five minutes and the seasonal cycle is 1 day, both SEASONAL and
246 DEVSEASONAL will have 288 rows.
248 In order to simplify the creation for the novice user, in addition to
249 supporting explicit creation of the HWPREDICT, SEASONAL, DEVPREDICT,
250 DEVSEASONAL, and FAILURES R\bRR\bRA\bAs\bs, the R\bRR\bRD\bDt\bto\boo\bol\bl create command supports
251 implicit creation of the other four when HWPREDICT is specified alone
255 that there is a one-to-one correspondence between primary data points
257 than the _\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd. If the DEVPREDICT R\bRR\bRA\bA is implicitly created,
260 _\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd argument of the HWPREDICT R\bRR\bRA\bA. Of course, the R\bRR\bRD\bDt\bto\boo\bol\bl
262 the creator wishes to avoid explicit creations of the other specialized
265 _\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd specifies the number of primary data points in a
266 seasonal cycle. If SEASONAL and DEVSEASONAL are implicitly created,
268 specified by HWPREDICT. If they are explicitly created, the creator
269 should verify that all three _\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd arguments agree.
272 coefficient in the Holt-Winters forecasting algorithm. See rrdtool for
274 value closer to 1 means that more recent observations carry greater
275 weight in predicting the baseline component of the forecast. A value
276 closer to 0 means that past history carries greater weight in
277 predicting the baseline component.
282 predicted linear trend.
285 Holt-Winters forecasting algorithm (HWPREDICT) or the adaption
286 parameter in the exponential smoothing update of the seasonal
287 deviations. It must lie between 0 and 1. If the SEASONAL and
289 value for _\bg_\ba_\bm_\bm_\ba: the value specified for the HWPREDICT _\ba_\bl_\bp_\bh_\ba argument.
290 Note that because there is one seasonal coefficient (or deviation) for
291 each time point during the seasonal cycle, the adaptation rate is much
292 slower than the baseline. Each seasonal coefficient is only updated (or
293 adapts) when the observed value occurs at the offset in the seasonal
294 cycle corresponding to that coefficient.
296 If SEASONAL and DEVSEASONAL R\bRR\bRA\bAs\bs are created explicitly, _\bg_\ba_\bm_\bm_\ba need not
300 _\bs_\bm_\bo_\bo_\bt_\bh_\bi_\bn_\bg_\b-_\bw_\bi_\bn_\bd_\bo_\bw specifies the fraction of a season that should be
301 averaged around each point. By default, the value of _\bs_\bm_\bo_\bo_\bt_\bh_\bi_\bn_\bg_\b-_\bw_\bi_\bn_\bd_\bo_\bw
302 is 0.05, which means each value in SEASONAL and DEVSEASONAL will be
303 occasionally replaced by averaging it with its (_\bs_\be_\ba_\bs_\bo_\bn_\ba_\bl _\bp_\be_\br_\bi_\bo_\bd*0.05)
304 nearest neighbors. Setting _\bs_\bm_\bo_\bo_\bt_\bh_\bi_\bn_\bg_\b-_\bw_\bi_\bn_\bd_\bo_\bw to zero will disable the
305 running-average smoother altogether.
307 _\br_\br_\ba_\b-_\bn_\bu_\bm provides the links between related R\bRR\bRA\bAs\bs. If HWPREDICT is
312 and another R\bRR\bRA\bA. The _\br_\br_\ba_\b-_\bn_\bu_\bm argument is the 1-based index in the order
313 of R\bRR\bRA\bA creation (that is, the order they appear in the _\bc_\br_\be_\ba_\bt_\be command).
314 The dependent R\bRR\bRA\bA for each R\bRR\bRA\bA requiring the _\br_\br_\ba_\b-_\bn_\bu_\bm argument is listed
315 here:
327 _\bt_\bh_\br_\be_\bs_\bh_\bo_\bl_\bd is the minimum number of violations (observed values outside
328 the confidence bounds) within a window that constitutes a failure. If
331 _\bw_\bi_\bn_\bd_\bo_\bw _\bl_\be_\bn_\bg_\bt_\bh is the number of time points in the window. Specify an
332 integer greater than or equal to the threshold and less than or equal
333 to 28. The time interval this window represents depends on the
335 created, the default value is 9.
338 Here is an explanation by Don Baarda on the inner workings of RRDtool.
339 It may help you to sort out why all this *UNKNOWN* data is popping up
340 in your databases:
342 RRDtool gets fed samples/updates at arbitrary times. From these it
343 builds Primary Data Points (PDPs) on every "step" interval. The PDPs
344 are then accumulated into the RRAs.
346 The "heartbeat" defines the maximum acceptable interval between
347 samples/updates. If the interval between samples is less than
348 "heartbeat", then an average rate is calculated and applied for that
349 interval. If the interval between samples is longer than "heartbeat",
350 then that entire interval is considered "unknown". Note that there are
351 other things that can make a sample interval "unknown", such as the
352 rate exceeding limits, or a sample that was explicitly marked as
353 unknown.
355 The known rates during a PDP's "step" interval are used to calculate an
356 average rate for that PDP. If the total "unknown" time accounts for
358 means that a mixture of known and "unknown" sample times in a single
359 PDP "step" may or may not add up to enough "known" time to warrant a
360 known PDP.
362 The "heartbeat" can be short (unusual) or long (typical) relative to
363 the "step" interval between PDPs. A short "heartbeat" means you require
364 multiple samples per PDP, and if you don't get them mark the PDP
365 unknown. A long heartbeat can span multiple "steps", which means it is
366 acceptable to have multiple PDPs calculated from a single sample. An
367 extreme example of this might be a "step" of 5 minutes and a
368 "heartbeat" of one day, in which case a single sample every day will
369 result in all the PDPs for that entire day period being set to the same
370 average rate. _\b-_\b- _\bD_\bo_\bn _\bB_\ba_\ba_\br_\bd_\ba _\b<_\bd_\bo_\bn_\b._\bb_\ba_\ba_\br_\bd_\ba_\b@_\bb_\ba_\be_\bs_\by_\bs_\bt_\be_\bm_\bs_\b._\bc_\bo_\bm_\b>
372 time|
373 axis|
374 begin__|00|
375 |01|
376 u|02|----* sample1, restart "hb"-timer
377 u|03| /
378 u|04| /
379 u|05| /
380 u|06|/ "hbt" expired
381 u|07|
382 |08|----* sample2, restart "hb"
383 |09| /
384 |10| /
385 u|11|----* sample3, restart "hb"
386 u|12| /
387 u|13| /
388 step1_u|14| /
389 u|15|/ "swt" expired
390 u|16|
391 |17|----* sample4, restart "hb", create "pdp" for step1 =
392 |18| / = unknown due to 10 "u" labled secs > 0.5 * step
393 |19| /
394 |20| /
395 |21|----* sample5, restart "hb"
396 |22| /
397 |23| /
398 |24|----* sample6, restart "hb"
399 |25| /
400 |26| /
401 |27|----* sample7, restart "hb"
402 step2__|28| /
403 |22| /
404 |23|----* sample8, restart "hb", create "pdp" for step1, create "cdp"
405 |24| /
406 |25| /
408 graphics by _\bv_\bl_\ba_\bd_\bi_\bm_\bi_\br_\b._\bl_\ba_\bv_\br_\bo_\bv_\b@_\bd_\be_\bs_\by_\b._\bd_\be.
411 Here are a few hints on how to measure:
413 Temperature
414 Usually you have some type of meter you can read to get the
415 temperature. The temperature is not really connected with a time.
416 The only connection is that the temperature reading happened at a
418 RRDtool will then record your reading together with the time.
420 Mail Messages
421 Assume you have a method to count the number of messages
422 transported by your mail server in a certain amount of time, giving
423 you data like '5 messages in the last 65 seconds'. If you look at
425 RRD with the number 5 and the end time of your monitoring period.
426 RRDtool will then record the number of messages per second. If at
427 some later stage you want to know the number of messages
428 transported in a day, you can get the average messages per second
429 from RRDtool for the day in question and multiply this number with
430 the number of seconds in a day. Because all math is run with
431 Doubles, the precision should be acceptable.
433 It's always a Rate
434 RRDtool stores rates in amount/second for COUNTER, DERIVE and
435 ABSOLUTE data. When you plot the data, you will get on the y axis
436 amount/second which you might be tempted to convert to an absolute
437 amount by multiplying by the delta-time between the points. RRDtool
438 plots continuous data, and as such is not appropriate for plotting
439 absolute amounts as for example "total bytes" sent and received in
440 a router. What you probably want is plot rates that you can scale
441 to bytes/hour, for example, or plot absolute amounts with another
442 tool that draws bar-plots, where the delta-time is clear on the
443 plot for each point (such that when you read the graph you see for
444 example GB on the y axis, days on the x axis and one bar for each
445 day).
448 rrdtool create temperature.rrd --step 300 \
449 DS:temp:GAUGE:600:-273:5000 \
450 RRA:AVERAGE:0.5:1:1200 \
451 RRA:MIN:0.5:12:2400 \
452 RRA:MAX:0.5:12:2400 \
453 RRA:AVERAGE:0.5:12:2400
455 This sets up an R\bRR\bRD\bD called _\bt_\be_\bm_\bp_\be_\br_\ba_\bt_\bu_\br_\be_\b._\br_\br_\bd which accepts one
456 temperature value every 300 seconds. If no new data is supplied for
457 more than 600 seconds, the temperature becomes _\b*_\bU_\bN_\bK_\bN_\bO_\bW_\bN_\b*. The minimum
458 acceptable value is -273 and the maximum is 5'000.
460 A few archive areas are also defined. The first stores the temperatures
461 supplied for 100 hours (1'200 * 300 seconds = 100 hours). The second
462 RRA stores the minimum temperature recorded over every hour (12 * 300
463 seconds = 1 hour), for 100 days (2'400 hours). The third and the fourth
464 RRA's do the same for the maximum and average temperature,
465 respectively.
468 rrdtool create monitor.rrd --step 300 \
469 DS:ifOutOctets:COUNTER:1800:0:4294967295 \
470 RRA:AVERAGE:0.5:1:2016 \
471 RRA:HWPREDICT:1440:0.1:0.0035:288
475 functions R\bRR\bRA\bAs\bs for aberrant behavior detection. Note that the _\br_\br_\ba_\b-_\bn_\bu_\bm
477 created with default parameter values. In this example, the forecasting
478 algorithm baseline adapts quickly; in fact the most recent one hour of
479 observations (each at 5 minute intervals) accounts for 75% of the
480 baseline prediction. The linear trend forecast adapts much more slowly.
481 Observations made during the last day (at 288 observations per day)
482 account for only 65% of the predicted linear trend. Note: these
483 computations rely on an exponential smoothing formula described in the
484 LISA 2000 paper.
486 The seasonal cycle is one day (288 data points at 300 second
487 intervals), and the seasonal adaption parameter will be set to 0.1. The
488 RRD file will store 5 days (1'440 data points) of forecasts and
489 deviation predictions before wrap around. The file will store 1 day (a
495 rrdtool create monitor.rrd --step 300 \
496 DS:ifOutOctets:COUNTER:1800:0:4294967295 \
497 RRA:AVERAGE:0.5:1:2016 \
498 RRA:HWPREDICT:1440:0.1:0.0035:288:3 \
499 RRA:SEASONAL:288:0.1:2 \
500 RRA:DEVPREDICT:1440:5 \
501 RRA:DEVSEASONAL:288:0.1:2 \
502 RRA:FAILURES:288:7:9:5
504 Of course, explicit creation need not replicate implicit create, a
505 number of arguments could be changed.
508 rrdtool create proxy.rrd --step 300 \
509 DS:Total:DERIVE:1800:0:U \
510 DS:Duration:DERIVE:1800:0:U \
511 DS:AvgReqDur:COMPUTE:Duration,Requests,0,EQ,1,Requests,IF,/ \
512 RRA:AVERAGE:0.5:1:2016
514 This example is monitoring the average request duration during each 300
515 sec interval for requests processed by a web proxy during the interval.
516 In this case, the proxy exposes two counters, the number of requests
517 processed since boot and the total cumulative duration of all processed
518 requests. Clearly these counters both have some rollover point, but
519 using the DERIVE data source also handles the reset that occurs when
520 the web proxy is stopped and restarted.
523 during the interval. The second data source stores the total duration
524 of all requests processed during the interval divided by 300. The
525 COMPUTE data source divides each PDP of the AccumDuration by the
526 corresponding PDP of TotalRequests and stores the average request
527 duration. The remainder of the RPN expression handles the divide by
528 zero case.
531 Tobias Oetiker <tobi@oetiker.ch>
535 1.4.8 2013-05-23 RRDCREATE(1)