1 /*****************************************************************************
2 * RRDtool 1.2.99907080300 Copyright by Tobi Oetiker, 1997-2007
3 *****************************************************************************
4 * rrd_format.h RRD Database Format header
5 *****************************************************************************/
7 #ifndef _RRD_FORMAT_H
8 #define _RRD_FORMAT_H
10 #include "rrd.h"
12 /*****************************************************************************
13 * put this in your /usr/lib/magic file (/etc/magic on HPUX)
14 *
15 * # rrd database format
16 * 0 string RRD\0 rrd file
17 * >5 string >\0 version '%s'
18 *
19 *****************************************************************************/
21 #define RRD_COOKIE "RRD"
22 /* #define RRD_VERSION "0002" */
23 /* changed because microsecond precision requires another field */
24 #define RRD_VERSION "0004"
25 #define RRD_VERSION3 "0003"
26 #define FLOAT_COOKIE 8.642135E130
28 typedef union unival {
29 unsigned long u_cnt;
30 rrd_value_t u_val;
31 } unival;
34 /****************************************************************************
35 * The RRD Database Structure
36 * ---------------------------
37 *
38 * In oder to properly describe the database structure lets define a few
39 * new words:
40 *
41 * ds - Data Source (ds) providing input to the database. A Data Source (ds)
42 * can be a traffic counter, a temperature, the number of users logged
43 * into a system. The rrd database format can handle the input of
44 * several Data Sources (ds) in a singe database.
45 *
46 * dst - Data Source Type (dst). The Data Source Type (dst) defines the rules
47 * applied to Build Primary Data Points from the input provided by the
48 * data sources (ds).
49 *
50 * pdp - Primary Data Point (pdp). After the database has accepted the
51 * input from the data sources (ds). It starts building Primary
52 * Data Points (pdp) from the data. Primary Data Points (pdp)
53 * are evenly spaced along the time axis (pdp_step). The values
54 * of the Primary Data Points are calculated from the values of
55 * the data source (ds) and the exact time these values were
56 * provided by the data source (ds).
57 *
58 * pdp_st - PDP Start (pdp_st). The moments (pdp_st) in time where
59 * these steps occur are defined by the moments where the
60 * number of seconds since 1970-jan-1 modulo pdp_step equals
61 * zero (pdp_st).
62 *
63 * cf - Consolidation Function (cf). An arbitrary Consolidation Function (cf)
64 * (averaging, min, max) is applied to the primary data points (pdp) to
65 * calculate the consolidated data point.
66 *
67 * cdp - Consolidated Data Point (cdp) is the long term storage format for data
68 * in the rrd database. Consolidated Data Points represent one or
69 * several primary data points collected along the time axis. The
70 * Consolidated Data Points (cdp) are stored in Round Robin Archives
71 * (rra).
72 *
73 * rra - Round Robin Archive (rra). This is the place where the
74 * consolidated data points (cdp) get stored. The data is
75 * organized in rows (row) and columns (col). The Round Robin
76 * Archive got its name from the method data is stored in
77 * there. An RRD database can contain several Round Robin
78 * Archives. Each Round Robin Archive can have a different row
79 * spacing along the time axis (pdp_cnt) and a different
80 * consolidation function (cf) used to build its consolidated
81 * data points (cdp).
82 *
83 * rra_st - RRA Start (rra_st). The moments (rra_st) in time where
84 * Consolidated Data Points (cdp) are added to an rra are
85 * defined by the moments where the number of seconds since
86 * 1970-jan-1 modulo pdp_cnt*pdp_step equals zero (rra_st).
87 *
88 * row - Row (row). A row represent all consolidated data points (cdp)
89 * in a round robin archive who are of the same age.
90 *
91 * col - Column (col). A column (col) represent all consolidated
92 * data points (cdp) in a round robin archive (rra) who
93 * originated from the same data source (ds).
94 *
95 */
97 /****************************************************************************
98 * POS 1: stat_head_t static header of the database
99 ****************************************************************************/
101 typedef struct stat_head_t {
103 /* Data Base Identification Section ** */
104 char cookie[4]; /* RRD */
105 char version[5]; /* version of the format */
106 double float_cookie; /* is it the correct double
107 * representation ? */
109 /* Data Base Structure Definition **** */
110 unsigned long ds_cnt; /* how many different ds provide
111 * input to the rrd */
112 unsigned long rra_cnt; /* how many rras will be maintained
113 * in the rrd */
114 unsigned long pdp_step; /* pdp interval in seconds */
116 unival par[10]; /* global parameters ... unused
117 at the moment */
118 } stat_head_t;
121 /****************************************************************************
122 * POS 2: ds_def_t (* ds_cnt) Data Source definitions
123 ****************************************************************************/
125 enum dst_en { DST_COUNTER = 0, /* data source types available */
126 DST_ABSOLUTE,
127 DST_GAUGE,
128 DST_DERIVE,
129 DST_CDEF
130 };
132 enum ds_param_en { DS_mrhb_cnt = 0, /* minimum required heartbeat. A
133 * data source must provide input at
134 * least every ds_mrhb seconds,
135 * otherwise it is regarded dead and
136 * will be set to UNKNOWN */
137 DS_min_val, /* the processed input of a ds must */
138 DS_max_val, /* be between max_val and min_val
139 * both can be set to UNKNOWN if you
140 * do not care. Data outside the limits
141 * set to UNKNOWN */
142 DS_cdef = DS_mrhb_cnt
143 }; /* pointer to encoded rpn
144 * expression only applies to DST_CDEF */
146 /* The magic number here is one less than DS_NAM_SIZE */
147 #define DS_NAM_FMT "%19[a-zA-Z0-9_-]"
148 #define DS_NAM_SIZE 20
150 #define DST_FMT "%19[A-Z]"
151 #define DST_SIZE 20
153 typedef struct ds_def_t {
154 char ds_nam[DS_NAM_SIZE]; /* Name of the data source (null terminated) */
155 char dst[DST_SIZE]; /* Type of data source (null terminated) */
156 unival par[10]; /* index of this array see ds_param_en */
157 } ds_def_t;
159 /****************************************************************************
160 * POS 3: rra_def_t ( * rra_cnt) one for each store to be maintained
161 ****************************************************************************/
162 enum cf_en { CF_AVERAGE = 0, /* data consolidation functions */
163 CF_MINIMUM,
164 CF_MAXIMUM,
165 CF_LAST,
166 CF_HWPREDICT,
167 /* An array of predictions using the seasonal
168 * Holt-Winters algorithm. Requires an RRA of type
169 * CF_SEASONAL for this data source. */
170 CF_SEASONAL,
171 /* An array of seasonal effects. Requires an RRA of
172 * type CF_HWPREDICT for this data source. */
173 CF_DEVPREDICT,
174 /* An array of deviation predictions based upon
175 * smoothed seasonal deviations. Requires an RRA of
176 * type CF_DEVSEASONAL for this data source. */
177 CF_DEVSEASONAL,
178 /* An array of smoothed seasonal deviations. Requires
179 * an RRA of type CF_HWPREDICT for this data source.
180 * */
181 CF_FAILURES,
182 /* HWPREDICT that follows a moving baseline */
183 CF_MHWPREDICT
184 /* new entries must come last !!! */
185 };
187 /* A binary array of failure indicators: 1 indicates
188 * that the number of violations in the prescribed
189 * window exceeded the prescribed threshold. */
191 #define MAX_RRA_PAR_EN 10
192 enum rra_par_en { RRA_cdp_xff_val = 0, /* what part of the consolidated
193 * datapoint must be known, to produce a
194 * valid entry in the rra */
195 /* CF_HWPREDICT: */
196 RRA_hw_alpha = 1,
197 /* exponential smoothing parameter for the intercept in
198 * the Holt-Winters prediction algorithm. */
199 RRA_hw_beta = 2,
200 /* exponential smoothing parameter for the slope in
201 * the Holt-Winters prediction algorithm. */
203 RRA_dependent_rra_idx = 3,
204 /* For CF_HWPREDICT: index of the RRA with the seasonal
205 * effects of the Holt-Winters algorithm (of type
206 * CF_SEASONAL).
207 * For CF_DEVPREDICT: index of the RRA with the seasonal
208 * deviation predictions (of type CF_DEVSEASONAL).
209 * For CF_SEASONAL: index of the RRA with the Holt-Winters
210 * intercept and slope coefficient (of type CF_HWPREDICT).
211 * For CF_DEVSEASONAL: index of the RRA with the
212 * Holt-Winters prediction (of type CF_HWPREDICT).
213 * For CF_FAILURES: index of the CF_DEVSEASONAL array.
214 * */
216 /* CF_SEASONAL and CF_DEVSEASONAL: */
217 RRA_seasonal_gamma = 1,
218 /* exponential smoothing parameter for seasonal effects. */
220 RRA_seasonal_smoothing_window = 2,
221 /* fraction of the season to include in the running average
222 * smoother */
224 /* RRA_dependent_rra_idx = 3, */
226 RRA_seasonal_smooth_idx = 4,
227 /* an integer between 0 and row_count - 1 which
228 * is index in the seasonal cycle for applying
229 * the period smoother. */
231 /* CF_FAILURES: */
232 RRA_delta_pos = 1, /* confidence bound scaling parameters */
233 RRA_delta_neg = 2,
234 /* RRA_dependent_rra_idx = 3, */
235 RRA_window_len = 4,
236 RRA_failure_threshold = 5,
237 /* For CF_FAILURES, number of violations within the last
238 * window required to mark a failure. */
239 };
241 /* For CF_FAILURES, the length of the window for measuring
242 * failures. */
244 #define CF_NAM_FMT "%19[A-Z]"
245 #define CF_NAM_SIZE 20
247 typedef struct rra_def_t {
248 char cf_nam[CF_NAM_SIZE]; /* consolidation function (null term) */
249 unsigned long row_cnt; /* number of entries in the store */
250 unsigned long pdp_cnt; /* how many primary data points are
251 * required for a consolidated data
252 * point?*/
253 unival par[MAX_RRA_PAR_EN]; /* index see rra_param_en */
255 } rra_def_t;
258 /****************************************************************************
259 ****************************************************************************
260 ****************************************************************************
261 * LIVE PART OF THE HEADER. THIS WILL BE WRITTEN ON EVERY UPDATE *
262 ****************************************************************************
263 ****************************************************************************
264 ****************************************************************************/
265 /****************************************************************************
266 * POS 4: live_head_t
267 ****************************************************************************/
269 typedef struct live_head_t {
270 time_t last_up; /* when was rrd last updated */
271 long last_up_usec; /* micro seconds part of the
272 update timestamp. Always >= 0 */
273 } live_head_t;
276 /****************************************************************************
277 * POS 5: pdp_prep_t (* ds_cnt) here we prepare the pdps
278 ****************************************************************************/
279 #define LAST_DS_LEN 30 /* DO NOT CHANGE THIS ... */
281 enum pdp_par_en { PDP_unkn_sec_cnt = 0, /* how many seconds of the current
282 * pdp value is unknown data? */
284 PDP_val
285 }; /* current value of the pdp.
286 this depends on dst */
288 typedef struct pdp_prep_t {
289 char last_ds[LAST_DS_LEN]; /* the last reading from the data
290 * source. this is stored in ASCII
291 * to cater for very large counters
292 * we might encounter in connection
293 * with SNMP. */
294 unival scratch[10]; /* contents according to pdp_par_en */
295 } pdp_prep_t;
297 /* data is passed from pdp to cdp when seconds since epoch modulo pdp_step == 0
298 obviously the updates do not occur at these times only. Especially does the
299 format allow for updates to occur at different times for each data source.
300 The rules which makes this work is as follows:
302 * DS updates may only occur at ever increasing points in time
303 * When any DS update arrives after a cdp update time, the *previous*
304 update cycle gets executed. All pdps are transfered to cdps and the
305 cdps feed the rras where necessary. Only then the new DS value
306 is loaded into the PDP. */
309 /****************************************************************************
310 * POS 6: cdp_prep_t (* rra_cnt * ds_cnt ) data prep area for cdp values
311 ****************************************************************************/
312 #define MAX_CDP_PAR_EN 10
313 #define MAX_CDP_FAILURES_IDX 8
314 /* max CDP scratch entries avail to record violations for a FAILURES RRA */
315 #define MAX_FAILURES_WINDOW_LEN 28
316 enum cdp_par_en { CDP_val = 0,
317 /* the base_interval is always an
318 * average */
319 CDP_unkn_pdp_cnt,
320 /* how many unknown pdp were
321 * integrated. This and the cdp_xff
322 * will decide if this is going to
323 * be a UNKNOWN or a valid value */
324 CDP_hw_intercept,
325 /* Current intercept coefficient for the Holt-Winters
326 * prediction algorithm. */
327 CDP_hw_last_intercept,
328 /* Last iteration intercept coefficient for the Holt-Winters
329 * prediction algorihtm. */
330 CDP_hw_slope,
331 /* Current slope coefficient for the Holt-Winters
332 * prediction algorithm. */
333 CDP_hw_last_slope,
334 /* Last iteration slope coeffient. */
335 CDP_null_count,
336 /* Number of sequential Unknown (DNAN) values + 1 preceding
337 * the current prediction.
338 * */
339 CDP_last_null_count,
340 /* Last iteration count of Unknown (DNAN) values. */
341 CDP_primary_val = 8,
342 /* optimization for bulk updates: the value of the first CDP
343 * value to be written in the bulk update. */
344 CDP_secondary_val = 9,
345 /* optimization for bulk updates: the value of subsequent
346 * CDP values to be written in the bulk update. */
347 CDP_hw_seasonal = CDP_hw_intercept,
348 /* Current seasonal coefficient for the Holt-Winters
349 * prediction algorithm. This is stored in CDP prep to avoid
350 * redundant seek operations. */
351 CDP_hw_last_seasonal = CDP_hw_last_intercept,
352 /* Last iteration seasonal coeffient. */
353 CDP_seasonal_deviation = CDP_hw_intercept,
354 CDP_last_seasonal_deviation = CDP_hw_last_intercept,
355 CDP_init_seasonal = CDP_null_count
356 };
358 /* init_seasonal is a flag which when > 0, forces smoothing updates
359 * to occur when rra_ptr.cur_row == 0 */
361 typedef struct cdp_prep_t {
362 unival scratch[MAX_CDP_PAR_EN];
363 /* contents according to cdp_par_en *
364 * init state should be NAN */
366 } cdp_prep_t;
368 /****************************************************************************
369 * POS 7: rra_ptr_t (* rra_cnt) pointers to the current row in each rra
370 ****************************************************************************/
372 typedef struct rra_ptr_t {
373 unsigned long cur_row; /* current row in the rra */
374 } rra_ptr_t;
377 /****************************************************************************
378 ****************************************************************************
379 * One single struct to hold all the others. For convenience.
380 ****************************************************************************
381 ****************************************************************************/
382 typedef struct rrd_t {
383 stat_head_t *stat_head; /* the static header */
384 ds_def_t *ds_def; /* list of data source definitions */
385 rra_def_t *rra_def; /* list of round robin archive def */
386 live_head_t *live_head;
387 pdp_prep_t *pdp_prep; /* pdp data prep area */
388 cdp_prep_t *cdp_prep; /* cdp prep area */
389 rra_ptr_t *rra_ptr; /* list of rra pointers */
390 rrd_value_t *rrd_value; /* list of rrd values */
391 } rrd_t;
393 /****************************************************************************
394 ****************************************************************************
395 * AFTER the header section we have the DATA STORAGE AREA it is made up from
396 * Consolidated Data Points organized in Round Robin Archives.
397 ****************************************************************************
398 ****************************************************************************
400 *RRA 0
401 (0,0) .................... ( ds_cnt -1 , 0)
402 .
403 .
404 .
405 (0, row_cnt -1) ... (ds_cnt -1, row_cnt -1)
407 *RRA 1
408 *RRA 2
410 *RRA rra_cnt -1
412 ****************************************************************************/
415 #endif