1 /*-------------------------------------------------------------------------
2  *
3  * ragetypes_typanalyze.c
4  *	  Functions for gathering statistics from range columns
5  *
6  * For a range type column, histograms of lower and upper bounds, and
7  * the fraction of NULL and empty ranges are collected.
8  *
9  * Both histograms have the same length, and they are combined into a
10  * single array of ranges. This has the same shape as the histogram that
11  * std_typanalyze would collect, but the values are different. Each range
12  * in the array is a valid range, even though the lower and upper bounds
13  * come from different tuples. In theory, the standard scalar selectivity
14  * functions could be used with the combined histogram.
15  *
16  * Portions Copyright (c) 1996-2018, PostgreSQL Global Development Group
17  * Portions Copyright (c) 1994, Regents of the University of California
18  *
19  *
20  * IDENTIFICATION
21  *	  src/backend/utils/adt/rangetypes_typanalyze.c
22  *
23  *-------------------------------------------------------------------------
24  */
25 #include "postgres.h"
26 
27 #include "catalog/pg_operator.h"
28 #include "commands/vacuum.h"
29 #include "utils/builtins.h"
30 #include "utils/lsyscache.h"
31 #include "utils/rangetypes.h"
32 
33 static int	float8_qsort_cmp(const void *a1, const void *a2);
34 static int	range_bound_qsort_cmp(const void *a1, const void *a2, void *arg);
35 static void compute_range_stats(VacAttrStats *stats,
36 					AnalyzeAttrFetchFunc fetchfunc, int samplerows, double totalrows);
37 
38 /*
39  * range_typanalyze -- typanalyze function for range columns
40  */
41 Datum
range_typanalyze(PG_FUNCTION_ARGS)42 range_typanalyze(PG_FUNCTION_ARGS)
43 {
44 	VacAttrStats *stats = (VacAttrStats *) PG_GETARG_POINTER(0);
45 	TypeCacheEntry *typcache;
46 	Form_pg_attribute attr = stats->attr;
47 
48 	/* Get information about range type; note column might be a domain */
49 	typcache = range_get_typcache(fcinfo, getBaseType(stats->attrtypid));
50 
51 	if (attr->attstattarget < 0)
52 		attr->attstattarget = default_statistics_target;
53 
54 	stats->compute_stats = compute_range_stats;
55 	stats->extra_data = typcache;
56 	/* same as in std_typanalyze */
57 	stats->minrows = 300 * attr->attstattarget;
58 
59 	PG_RETURN_BOOL(true);
60 }
61 
62 /*
63  * Comparison function for sorting float8s, used for range lengths.
64  */
65 static int
float8_qsort_cmp(const void * a1,const void * a2)66 float8_qsort_cmp(const void *a1, const void *a2)
67 {
68 	const float8 *f1 = (const float8 *) a1;
69 	const float8 *f2 = (const float8 *) a2;
70 
71 	if (*f1 < *f2)
72 		return -1;
73 	else if (*f1 == *f2)
74 		return 0;
75 	else
76 		return 1;
77 }
78 
79 /*
80  * Comparison function for sorting RangeBounds.
81  */
82 static int
range_bound_qsort_cmp(const void * a1,const void * a2,void * arg)83 range_bound_qsort_cmp(const void *a1, const void *a2, void *arg)
84 {
85 	RangeBound *b1 = (RangeBound *) a1;
86 	RangeBound *b2 = (RangeBound *) a2;
87 	TypeCacheEntry *typcache = (TypeCacheEntry *) arg;
88 
89 	return range_cmp_bounds(typcache, b1, b2);
90 }
91 
92 /*
93  * compute_range_stats() -- compute statistics for a range column
94  */
95 static void
compute_range_stats(VacAttrStats * stats,AnalyzeAttrFetchFunc fetchfunc,int samplerows,double totalrows)96 compute_range_stats(VacAttrStats *stats, AnalyzeAttrFetchFunc fetchfunc,
97 					int samplerows, double totalrows)
98 {
99 	TypeCacheEntry *typcache = (TypeCacheEntry *) stats->extra_data;
100 	bool		has_subdiff = OidIsValid(typcache->rng_subdiff_finfo.fn_oid);
101 	int			null_cnt = 0;
102 	int			non_null_cnt = 0;
103 	int			non_empty_cnt = 0;
104 	int			empty_cnt = 0;
105 	int			range_no;
106 	int			slot_idx;
107 	int			num_bins = stats->attr->attstattarget;
108 	int			num_hist;
109 	float8	   *lengths;
110 	RangeBound *lowers,
111 			   *uppers;
112 	double		total_width = 0;
113 
114 	/* Allocate memory to hold range bounds and lengths of the sample ranges. */
115 	lowers = (RangeBound *) palloc(sizeof(RangeBound) * samplerows);
116 	uppers = (RangeBound *) palloc(sizeof(RangeBound) * samplerows);
117 	lengths = (float8 *) palloc(sizeof(float8) * samplerows);
118 
119 	/* Loop over the sample ranges. */
120 	for (range_no = 0; range_no < samplerows; range_no++)
121 	{
122 		Datum		value;
123 		bool		isnull,
124 					empty;
125 		RangeType  *range;
126 		RangeBound	lower,
127 					upper;
128 		float8		length;
129 
130 		vacuum_delay_point();
131 
132 		value = fetchfunc(stats, range_no, &isnull);
133 		if (isnull)
134 		{
135 			/* range is null, just count that */
136 			null_cnt++;
137 			continue;
138 		}
139 
140 		/*
141 		 * XXX: should we ignore wide values, like std_typanalyze does, to
142 		 * avoid bloating the statistics table?
143 		 */
144 		total_width += VARSIZE_ANY(DatumGetPointer(value));
145 
146 		/* Get range and deserialize it for further analysis. */
147 		range = DatumGetRangeTypeP(value);
148 		range_deserialize(typcache, range, &lower, &upper, &empty);
149 
150 		if (!empty)
151 		{
152 			/* Remember bounds and length for further usage in histograms */
153 			lowers[non_empty_cnt] = lower;
154 			uppers[non_empty_cnt] = upper;
155 
156 			if (lower.infinite || upper.infinite)
157 			{
158 				/* Length of any kind of an infinite range is infinite */
159 				length = get_float8_infinity();
160 			}
161 			else if (has_subdiff)
162 			{
163 				/*
164 				 * For an ordinary range, use subdiff function between upper
165 				 * and lower bound values.
166 				 */
167 				length = DatumGetFloat8(FunctionCall2Coll(
168 														  &typcache->rng_subdiff_finfo,
169 														  typcache->rng_collation,
170 														  upper.val, lower.val));
171 			}
172 			else
173 			{
174 				/* Use default value of 1.0 if no subdiff is available. */
175 				length = 1.0;
176 			}
177 			lengths[non_empty_cnt] = length;
178 
179 			non_empty_cnt++;
180 		}
181 		else
182 			empty_cnt++;
183 
184 		non_null_cnt++;
185 	}
186 
187 	slot_idx = 0;
188 
189 	/* We can only compute real stats if we found some non-null values. */
190 	if (non_null_cnt > 0)
191 	{
192 		Datum	   *bound_hist_values;
193 		Datum	   *length_hist_values;
194 		int			pos,
195 					posfrac,
196 					delta,
197 					deltafrac,
198 					i;
199 		MemoryContext old_cxt;
200 		float4	   *emptyfrac;
201 
202 		stats->stats_valid = true;
203 		/* Do the simple null-frac and width stats */
204 		stats->stanullfrac = (double) null_cnt / (double) samplerows;
205 		stats->stawidth = total_width / (double) non_null_cnt;
206 
207 		/* Estimate that non-null values are unique */
208 		stats->stadistinct = -1.0 * (1.0 - stats->stanullfrac);
209 
210 		/* Must copy the target values into anl_context */
211 		old_cxt = MemoryContextSwitchTo(stats->anl_context);
212 
213 		/*
214 		 * Generate a bounds histogram slot entry if there are at least two
215 		 * values.
216 		 */
217 		if (non_empty_cnt >= 2)
218 		{
219 			/* Sort bound values */
220 			qsort_arg(lowers, non_empty_cnt, sizeof(RangeBound),
221 					  range_bound_qsort_cmp, typcache);
222 			qsort_arg(uppers, non_empty_cnt, sizeof(RangeBound),
223 					  range_bound_qsort_cmp, typcache);
224 
225 			num_hist = non_empty_cnt;
226 			if (num_hist > num_bins)
227 				num_hist = num_bins + 1;
228 
229 			bound_hist_values = (Datum *) palloc(num_hist * sizeof(Datum));
230 
231 			/*
232 			 * The object of this loop is to construct ranges from first and
233 			 * last entries in lowers[] and uppers[] along with evenly-spaced
234 			 * values in between. So the i'th value is a range of lowers[(i *
235 			 * (nvals - 1)) / (num_hist - 1)] and uppers[(i * (nvals - 1)) /
236 			 * (num_hist - 1)]. But computing that subscript directly risks
237 			 * integer overflow when the stats target is more than a couple
238 			 * thousand.  Instead we add (nvals - 1) / (num_hist - 1) to pos
239 			 * at each step, tracking the integral and fractional parts of the
240 			 * sum separately.
241 			 */
242 			delta = (non_empty_cnt - 1) / (num_hist - 1);
243 			deltafrac = (non_empty_cnt - 1) % (num_hist - 1);
244 			pos = posfrac = 0;
245 
246 			for (i = 0; i < num_hist; i++)
247 			{
248 				bound_hist_values[i] = PointerGetDatum(range_serialize(
249 																	   typcache, &lowers[pos], &uppers[pos], false));
250 				pos += delta;
251 				posfrac += deltafrac;
252 				if (posfrac >= (num_hist - 1))
253 				{
254 					/* fractional part exceeds 1, carry to integer part */
255 					pos++;
256 					posfrac -= (num_hist - 1);
257 				}
258 			}
259 
260 			stats->stakind[slot_idx] = STATISTIC_KIND_BOUNDS_HISTOGRAM;
261 			stats->stavalues[slot_idx] = bound_hist_values;
262 			stats->numvalues[slot_idx] = num_hist;
263 			slot_idx++;
264 		}
265 
266 		/*
267 		 * Generate a length histogram slot entry if there are at least two
268 		 * values.
269 		 */
270 		if (non_empty_cnt >= 2)
271 		{
272 			/*
273 			 * Ascending sort of range lengths for further filling of
274 			 * histogram
275 			 */
276 			qsort(lengths, non_empty_cnt, sizeof(float8), float8_qsort_cmp);
277 
278 			num_hist = non_empty_cnt;
279 			if (num_hist > num_bins)
280 				num_hist = num_bins + 1;
281 
282 			length_hist_values = (Datum *) palloc(num_hist * sizeof(Datum));
283 
284 			/*
285 			 * The object of this loop is to copy the first and last lengths[]
286 			 * entries along with evenly-spaced values in between. So the i'th
287 			 * value is lengths[(i * (nvals - 1)) / (num_hist - 1)]. But
288 			 * computing that subscript directly risks integer overflow when
289 			 * the stats target is more than a couple thousand.  Instead we
290 			 * add (nvals - 1) / (num_hist - 1) to pos at each step, tracking
291 			 * the integral and fractional parts of the sum separately.
292 			 */
293 			delta = (non_empty_cnt - 1) / (num_hist - 1);
294 			deltafrac = (non_empty_cnt - 1) % (num_hist - 1);
295 			pos = posfrac = 0;
296 
297 			for (i = 0; i < num_hist; i++)
298 			{
299 				length_hist_values[i] = Float8GetDatum(lengths[pos]);
300 				pos += delta;
301 				posfrac += deltafrac;
302 				if (posfrac >= (num_hist - 1))
303 				{
304 					/* fractional part exceeds 1, carry to integer part */
305 					pos++;
306 					posfrac -= (num_hist - 1);
307 				}
308 			}
309 		}
310 		else
311 		{
312 			/*
313 			 * Even when we don't create the histogram, store an empty array
314 			 * to mean "no histogram". We can't just leave stavalues NULL,
315 			 * because get_attstatsslot() errors if you ask for stavalues, and
316 			 * it's NULL. We'll still store the empty fraction in stanumbers.
317 			 */
318 			length_hist_values = palloc(0);
319 			num_hist = 0;
320 		}
321 		stats->staop[slot_idx] = Float8LessOperator;
322 		stats->stavalues[slot_idx] = length_hist_values;
323 		stats->numvalues[slot_idx] = num_hist;
324 		stats->statypid[slot_idx] = FLOAT8OID;
325 		stats->statyplen[slot_idx] = sizeof(float8);
326 #ifdef USE_FLOAT8_BYVAL
327 		stats->statypbyval[slot_idx] = true;
328 #else
329 		stats->statypbyval[slot_idx] = false;
330 #endif
331 		stats->statypalign[slot_idx] = 'd';
332 
333 		/* Store the fraction of empty ranges */
334 		emptyfrac = (float4 *) palloc(sizeof(float4));
335 		*emptyfrac = ((double) empty_cnt) / ((double) non_null_cnt);
336 		stats->stanumbers[slot_idx] = emptyfrac;
337 		stats->numnumbers[slot_idx] = 1;
338 
339 		stats->stakind[slot_idx] = STATISTIC_KIND_RANGE_LENGTH_HISTOGRAM;
340 		slot_idx++;
341 
342 		MemoryContextSwitchTo(old_cxt);
343 	}
344 	else if (null_cnt > 0)
345 	{
346 		/* We found only nulls; assume the column is entirely null */
347 		stats->stats_valid = true;
348 		stats->stanullfrac = 1.0;
349 		stats->stawidth = 0;	/* "unknown" */
350 		stats->stadistinct = 0.0;	/* "unknown" */
351 	}
352 
353 	/*
354 	 * We don't need to bother cleaning up any of our temporary palloc's. The
355 	 * hashtable should also go away, as it used a child memory context.
356 	 */
357 }
358