1 /*****************************************************************************
2 * RRDtool 1.0.33 Copyright Tobias Oetiker, 1997, 1998, 1999
3 *****************************************************************************
4 * rrd_format.h RRD Database Format header
5 *****************************************************************************/
12 /*****************************************************************************
13 * put this in your /usr/lib/magic file (/etc/magic on HPUX)
15 * # rrd database format
16 * 0 string RRD\0 rrd file
17 * >5 string >\0 version '%s'
19 *****************************************************************************/
21 #define RRD_COOKIE "RRD"
22 /* #define RRD_VERSION "0002" */
23 /* changed because microsecond precision requires another field */
24 #define RRD_VERSION "0003"
25 #define FLOAT_COOKIE 8.642135E130
27 #include "rrd_nan_inf.h"
29 typedef union unival {
35 /****************************************************************************
36 * The RRD Database Structure
37 * ---------------------------
39 * In oder to properly describe the database structure lets define a few
42 * ds - Data Source (ds) providing input to the database. A Data Source (ds)
43 * can be a traffic counter, a temperature, the number of users logged
44 * into a system. The rrd database format can handle the input of
45 * several Data Sources (ds) in a singe database.
47 * dst - Data Source Type (dst). The Data Source Type (dst) defines the rules
48 * applied to Build Primary Data Points from the input provided by the
51 * pdp - Primary Data Point (pdp). After the database has accepted the
52 * input from the data sources (ds). It starts building Primary
53 * Data Points (pdp) from the data. Primary Data Points (pdp)
54 * are evenly spaced along the time axis (pdp_step). The values
55 * of the Primary Data Points are calculated from the values of
56 * the data source (ds) and the exact time these values were
57 * provided by the data source (ds).
59 * pdp_st - PDP Start (pdp_st). The moments (pdp_st) in time where
60 * these steps occur are defined by the moments where the
61 * number of seconds since 1970-jan-1 modulo pdp_step equals
64 * cf - Consolidation Function (cf). An arbitrary Consolidation Function (cf)
65 * (averaging, min, max) is applied to the primary data points (pdp) to
66 * calculate the consolidated data point.
68 * cdp - Consolidated Data Point (cdp) is the long term storage format for data
69 * in the rrd database. Consolidated Data Points represent one or
70 * several primary data points collected along the time axis. The
71 * Consolidated Data Points (cdp) are stored in Round Robin Archives
74 * rra - Round Robin Archive (rra). This is the place where the
75 * consolidated data points (cdp) get stored. The data is
76 * organized in rows (row) and columns (col). The Round Robin
77 * Archive got its name from the method data is stored in
78 * there. An RRD database can contain several Round Robin
79 * Archives. Each Round Robin Archive can have a different row
80 * spacing along the time axis (pdp_cnt) and a different
81 * consolidation function (cf) used to build its consolidated
84 * rra_st - RRA Start (rra_st). The moments (rra_st) in time where
85 * Consolidated Data Points (cdp) are added to an rra are
86 * defined by the moments where the number of seconds since
87 * 1970-jan-1 modulo pdp_cnt*pdp_step equals zero (rra_st).
89 * row - Row (row). A row represent all consolidated data points (cdp)
90 * in a round robin archive who are of the same age.
92 * col - Column (col). A column (col) represent all consolidated
93 * data points (cdp) in a round robin archive (rra) who
94 * originated from the same data source (ds).
98 /****************************************************************************
99 * POS 1: stat_head_t static header of the database
100 ****************************************************************************/
102 typedef struct stat_head_t {
104 /* Data Base Identification Section ***/
105 char cookie[4]; /* RRD */
106 char version[5]; /* version of the format */
107 double float_cookie; /* is it the correct double
108 * representation ? */
110 /* Data Base Structure Definition *****/
111 unsigned long ds_cnt; /* how many different ds provide
112 * input to the rrd */
113 unsigned long rra_cnt; /* how many rras will be maintained
115 unsigned long pdp_step; /* pdp interval in seconds */
117 unival par[10]; /* global parameters ... unused
122 /****************************************************************************
123 * POS 2: ds_def_t (* ds_cnt) Data Source definitions
124 ****************************************************************************/
126 enum dst_en { DST_COUNTER=0, /* data source types available */
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
142 DS_cdef = DS_mrhb_cnt}; /* pointer to encoded rpn
143 * expression only applies to DST_CDEF */
145 /* The magic number here is one less than DS_NAM_SIZE */
146 #define DS_NAM_FMT "%19[a-zA-Z0-9_-]"
147 #define DS_NAM_SIZE 20
149 #define DST_FMT "%19[A-Z]"
152 typedef struct ds_def_t {
153 char ds_nam[DS_NAM_SIZE]; /* Name of the data source (null terminated)*/
154 char dst[DST_SIZE]; /* Type of data source (null terminated)*/
155 unival par[10]; /* index of this array see ds_param_en */
158 /****************************************************************************
159 * POS 3: rra_def_t ( * rra_cnt) one for each store to be maintained
160 ****************************************************************************/
161 enum cf_en { CF_AVERAGE=0, /* data consolidation functions */
166 /* An array of predictions using the seasonal
167 * Holt-Winters algorithm. Requires an RRA of type
168 * CF_SEASONAL for this data source. */
170 /* An array of seasonal effects. Requires an RRA of
171 * type CF_HWPREDICT for this data source. */
173 /* An array of deviation predictions based upon
174 * smoothed seasonal deviations. Requires an RRA of
175 * type CF_DEVSEASONAL for this data source. */
177 /* An array of smoothed seasonal deviations. Requires
178 * an RRA of type CF_HWPREDICT for this data source.
181 /* A binary array of failure indicators: 1 indicates
182 * that the number of violations in the prescribed
183 * window exceeded the prescribed threshold. */
185 #define MAX_RRA_PAR_EN 10
186 enum rra_par_en { RRA_cdp_xff_val=0, /* what part of the consolidated
187 * datapoint must be known, to produce a
188 * valid entry in the rra */
190 /* exponential smoothing parameter for the intercept in
191 * the Holt-Winters prediction algorithm. */
193 /* exponential smoothing parameter for the slope in
194 * the Holt-Winters prediction algorithm. */
195 RRA_dependent_rra_idx,
196 /* For CF_HWPREDICT: index of the RRA with the seasonal
197 * effects of the Holt-Winters algorithm (of type
199 * For CF_DEVPREDICT: index of the RRA with the seasonal
200 * deviation predictions (of type CF_DEVSEASONAL).
201 * For CF_SEASONAL: index of the RRA with the Holt-Winters
202 * intercept and slope coefficient (of type CF_HWPREDICT).
203 * For CF_DEVSEASONAL: index of the RRA with the
204 * Holt-Winters prediction (of type CF_HWPREDICT).
205 * For CF_FAILURES: index of the CF_DEVSEASONAL array.
207 RRA_seasonal_smooth_idx,
208 /* For CF_SEASONAL and CF_DEVSEASONAL:
209 * an integer between 0 and row_count - 1 which
210 * is index in the seasonal cycle for applying
211 * the period smoother. */
212 RRA_failure_threshold,
213 /* For CF_FAILURES, number of violations within the last
214 * window required to mark a failure. */
215 RRA_seasonal_gamma = RRA_hw_alpha,
216 /* exponential smoothing parameter for seasonal effects.
218 RRA_delta_pos = RRA_hw_alpha,
219 RRA_delta_neg = RRA_hw_beta,
220 /* confidence bound scaling parameters for the
221 * the FAILURES RRA. */
222 RRA_window_len = RRA_seasonal_smooth_idx};
223 /* For CF_FAILURES, the length of the window for measuring
226 #define CF_NAM_FMT "%19[A-Z]"
227 #define CF_NAM_SIZE 20
229 typedef struct rra_def_t {
230 char cf_nam[CF_NAM_SIZE];/* consolidation function (null term) */
231 unsigned long row_cnt; /* number of entries in the store */
232 unsigned long pdp_cnt; /* how many primary data points are
233 * required for a consolidated data
235 unival par[MAX_RRA_PAR_EN]; /* index see rra_param_en */
240 /****************************************************************************
241 ****************************************************************************
242 ****************************************************************************
243 * LIVE PART OF THE HEADER. THIS WILL BE WRITTEN ON EVERY UPDATE *
244 ****************************************************************************
245 ****************************************************************************
246 ****************************************************************************/
247 /****************************************************************************
249 ****************************************************************************/
251 typedef struct live_head_t {
252 time_t last_up; /* when was rrd last updated */
253 long last_up_usec; /* micro seconds part of the
254 update timestamp. Always >= 0 */
258 /****************************************************************************
259 * POS 5: pdp_prep_t (* ds_cnt) here we prepare the pdps
260 ****************************************************************************/
261 #define LAST_DS_LEN 30 /* DO NOT CHANGE THIS ... */
263 enum pdp_par_en { PDP_unkn_sec_cnt=0, /* how many seconds of the current
264 * pdp value is unknown data? */
266 PDP_val}; /* current value of the pdp.
267 this depends on dst */
269 typedef struct pdp_prep_t{
270 char last_ds[LAST_DS_LEN]; /* the last reading from the data
271 * source. this is stored in ASCII
272 * to cater for very large counters
273 * we might encounter in connection
275 unival scratch[10]; /* contents according to pdp_par_en */
278 /* data is passed from pdp to cdp when seconds since epoch modulo pdp_step == 0
279 obviously the updates do not occur at these times only. Especially does the
280 format allow for updates to occur at different times for each data source.
281 The rules which makes this work is as follows:
283 * DS updates may only occur at ever increasing points in time
284 * When any DS update arrives after a cdp update time, the *previous*
285 update cycle gets executed. All pdps are transfered to cdps and the
286 cdps feed the rras where necessary. Only then the new DS value
287 is loaded into the PDP. */
290 /****************************************************************************
291 * POS 6: cdp_prep_t (* rra_cnt * ds_cnt ) data prep area for cdp values
292 ****************************************************************************/
293 #define MAX_CDP_PAR_EN 10
294 #define MAX_CDP_FAILURES_IDX 8
295 /* max CDP scratch entries avail to record violations for a FAILURES RRA */
296 #define MAX_FAILURES_WINDOW_LEN 28
297 enum cdp_par_en { CDP_val=0,
298 /* the base_interval is always an
301 /* how many unknown pdp were
302 * integrated. This and the cdp_xff
303 * will decide if this is going to
304 * be a UNKNOWN or a valid value */
306 /* Current intercept coefficient for the Holt-Winters
307 * prediction algorithm. */
308 CDP_hw_last_intercept,
309 /* Last iteration intercept coefficient for the Holt-Winters
310 * prediction algorihtm. */
312 /* Current slope coefficient for the Holt-Winters
313 * prediction algorithm. */
315 /* Last iteration slope coeffient. */
317 /* Number of sequential Unknown (DNAN) values + 1 preceding
318 * the current prediction.
321 /* Last iteration count of Unknown (DNAN) values. */
323 /* optimization for bulk updates: the value of the first CDP
324 * value to be written in the bulk update. */
325 CDP_secondary_val = 9,
326 /* optimization for bulk updates: the value of subsequent
327 * CDP values to be written in the bulk update. */
328 CDP_hw_seasonal = CDP_hw_intercept,
329 /* Current seasonal coefficient for the Holt-Winters
330 * prediction algorithm. This is stored in CDP prep to avoid
331 * redundant seek operations. */
332 CDP_hw_last_seasonal = CDP_hw_last_intercept,
333 /* Last iteration seasonal coeffient. */
334 CDP_seasonal_deviation = CDP_hw_intercept,
335 CDP_last_seasonal_deviation = CDP_hw_last_intercept,
336 CDP_init_seasonal = CDP_null_count};
337 /* init_seasonal is a flag which when > 0, forces smoothing updates
338 * to occur when rra_ptr.cur_row == 0 */
340 typedef struct cdp_prep_t{
341 unival scratch[MAX_CDP_PAR_EN];
342 /* contents according to cdp_par_en *
343 * init state should be NAN */
347 /****************************************************************************
348 * POS 7: rra_ptr_t (* rra_cnt) pointers to the current row in each rra
349 ****************************************************************************/
351 typedef struct rra_ptr_t {
352 unsigned long cur_row; /* current row in the rra*/
356 /****************************************************************************
357 ****************************************************************************
358 * One single struct to hold all the others. For convenience.
359 ****************************************************************************
360 ****************************************************************************/
361 typedef struct rrd_t {
362 stat_head_t *stat_head; /* the static header */
363 ds_def_t *ds_def; /* list of data source definitions */
364 rra_def_t *rra_def; /* list of round robin archive def */
365 live_head_t *live_head;
366 pdp_prep_t *pdp_prep; /* pdp data prep area */
367 cdp_prep_t *cdp_prep; /* cdp prep area */
368 rra_ptr_t *rra_ptr; /* list of rra pointers */
369 rrd_value_t *rrd_value; /* list of rrd values */
372 /****************************************************************************
373 ****************************************************************************
374 * AFTER the header section we have the DATA STORAGE AREA it is made up from
375 * Consolidated Data Points organized in Round Robin Archives.
376 ****************************************************************************
377 ****************************************************************************
380 (0,0) .................... ( ds_cnt -1 , 0)
384 (0, row_cnt -1) ... (ds_cnt -1, row_cnt -1)
391 ****************************************************************************/