1 /*
2 * Copyright (c) 2001, 2014, Oracle and/or its affiliates. All rights reserved.
3 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
4 *
5 * This code is free software; you can redistribute it and/or modify it
6 * under the terms of the GNU General Public License version 2 only, as
7 * published by the Free Software Foundation.
8 *
9 * This code is distributed in the hope that it will be useful, but WITHOUT
10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
11 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
12 * version 2 for more details (a copy is included in the LICENSE file that
13 * accompanied this code).
14 *
15 * You should have received a copy of the GNU General Public License version
16 * 2 along with this work; if not, write to the Free Software Foundation,
17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
18 *
19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
20 * or visit www.oracle.com if you need additional information or have any
21 * questions.
22 *
23 */
24
25 #include "precompiled.hpp"
26 #include "memory/allocation.inline.hpp"
27 #include "utilities/debug.hpp"
28 #include "utilities/globalDefinitions.hpp"
29 #include "utilities/numberSeq.hpp"
30
31 AbsSeq::AbsSeq(double alpha) :
32 _num(0), _sum(0.0), _sum_of_squares(0.0),
33 _davg(0.0), _dvariance(0.0), _alpha(alpha) {
34 }
35
36 void AbsSeq::add(double val) {
37 if (_num == 0) {
38 // if the sequence is empty, the davg is the same as the value
39 _davg = val;
40 // and the variance is 0
41 _dvariance = 0.0;
42 } else {
43 // otherwise, calculate both
44 _davg = (1.0 - _alpha) * val + _alpha * _davg;
45 double diff = val - _davg;
46 _dvariance = (1.0 - _alpha) * diff * diff + _alpha * _dvariance;
47 }
48 }
49
50 double AbsSeq::avg() const {
51 if (_num == 0)
52 return 0.0;
53 else
54 return _sum / total();
55 }
56
57 double AbsSeq::variance() const {
58 if (_num <= 1)
59 return 0.0;
60
61 double x_bar = avg();
62 double result = _sum_of_squares / total() - x_bar * x_bar;
63 if (result < 0.0) {
64 // due to loss-of-precision errors, the variance might be negative
65 // by a small bit
66
67 // guarantee(-0.1 < result && result < 0.0,
68 // "if variance is negative, it should be very small");
69 result = 0.0;
70 }
71 return result;
72 }
73
74 double AbsSeq::sd() const {
75 double var = variance();
76 guarantee( var >= 0.0, "variance should not be negative" );
77 return sqrt(var);
78 }
79
80 double AbsSeq::davg() const {
81 return _davg;
82 }
83
84 double AbsSeq::dvariance() const {
85 if (_num <= 1)
86 return 0.0;
87
88 double result = _dvariance;
89 if (result < 0.0) {
90 // due to loss-of-precision errors, the variance might be negative
91 // by a small bit
92
93 guarantee(-0.1 < result && result < 0.0,
94 "if variance is negative, it should be very small");
95 result = 0.0;
96 }
97 return result;
98 }
99
100 double AbsSeq::dsd() const {
101 double var = dvariance();
102 guarantee( var >= 0.0, "variance should not be negative" );
103 return sqrt(var);
104 }
105
106 NumberSeq::NumberSeq(double alpha) :
107 AbsSeq(alpha), _maximum(0.0), _last(0.0) {
108 }
109
110 bool NumberSeq::check_nums(NumberSeq *total, int n, NumberSeq **parts) {
111 for (int i = 0; i < n; ++i) {
112 if (parts[i] != NULL && total->num() != parts[i]->num())
113 return false;
114 }
115 return true;
116 }
117
118 void NumberSeq::add(double val) {
119 AbsSeq::add(val);
120
121 _last = val;
122 if (_num == 0) {
123 _maximum = val;
124 } else {
125 if (val > _maximum)
126 _maximum = val;
127 }
128 _sum += val;
129 _sum_of_squares += val * val;
130 ++_num;
131 }
132
133
134 TruncatedSeq::TruncatedSeq(int length, double alpha):
135 AbsSeq(alpha), _length(length), _next(0) {
136 _sequence = NEW_C_HEAP_ARRAY(double, _length, mtInternal);
137 for (int i = 0; i < _length; ++i)
138 _sequence[i] = 0.0;
139 }
140
141 TruncatedSeq::~TruncatedSeq() {
142 FREE_C_HEAP_ARRAY(double, _sequence, mtGC);
143 }
144
145 void TruncatedSeq::add(double val) {
146 AbsSeq::add(val);
147
148 // get the oldest value in the sequence...
149 double old_val = _sequence[_next];
150 // ...remove it from the sum and sum of squares
151 _sum -= old_val;
152 _sum_of_squares -= old_val * old_val;
153
154 // ...and update them with the new value
155 _sum += val;
156 _sum_of_squares += val * val;
157
158 // now replace the old value with the new one
159 _sequence[_next] = val;
160 _next = (_next + 1) % _length;
161
162 // only increase it if the buffer is not full
163 if (_num < _length)
164 ++_num;
165
166 guarantee( variance() > -1.0, "variance should be >= 0" );
167 }
168
169 // can't easily keep track of this incrementally...
170 double TruncatedSeq::maximum() const {
171 if (_num == 0)
172 return 0.0;
173 double ret = _sequence[0];
174 for (int i = 1; i < _num; ++i) {
175 double val = _sequence[i];
176 if (val > ret)
177 ret = val;
178 }
179 return ret;
180 }
181
182 double TruncatedSeq::last() const {
183 if (_num == 0)
184 return 0.0;
185 unsigned last_index = (_next + _length - 1) % _length;
186 return _sequence[last_index];
187 }
188
189 double TruncatedSeq::oldest() const {
190 if (_num == 0)
191 return 0.0;
192 else if (_num < _length)
193 // index 0 always oldest value until the array is full
194 return _sequence[0];
195 else {
196 // since the array is full, _next is over the oldest value
197 return _sequence[_next];
198 }
199 }
200
201 double TruncatedSeq::predict_next() const {
202 if (_num == 0)
203 return 0.0;
204
205 double num = (double) _num;
206 double x_squared_sum = 0.0;
207 double x_sum = 0.0;
208 double y_sum = 0.0;
209 double xy_sum = 0.0;
210 double x_avg = 0.0;
211 double y_avg = 0.0;
212
213 int first = (_next + _length - _num) % _length;
214 for (int i = 0; i < _num; ++i) {
215 double x = (double) i;
216 double y = _sequence[(first + i) % _length];
217
218 x_squared_sum += x * x;
219 x_sum += x;
220 y_sum += y;
221 xy_sum += x * y;
222 }
223 x_avg = x_sum / num;
224 y_avg = y_sum / num;
225
226 double Sxx = x_squared_sum - x_sum * x_sum / num;
227 double Sxy = xy_sum - x_sum * y_sum / num;
228 double b1 = Sxy / Sxx;
229 double b0 = y_avg - b1 * x_avg;
230
231 return b0 + b1 * num;
232 }
233
234
235 // Printing/Debugging Support
236
237 void AbsSeq::dump() { dump_on(gclog_or_tty); }
238
239 void AbsSeq::dump_on(outputStream* s) {
240 s->print_cr("\t _num = %d, _sum = %7.3f, _sum_of_squares = %7.3f",
241 _num, _sum, _sum_of_squares);
242 s->print_cr("\t _davg = %7.3f, _dvariance = %7.3f, _alpha = %7.3f",
243 _davg, _dvariance, _alpha);
244 }
245
246 void NumberSeq::dump_on(outputStream* s) {
247 AbsSeq::dump_on(s);
248 s->print_cr("\t\t _last = %7.3f, _maximum = %7.3f", _last, _maximum);
249 }
250
251 void TruncatedSeq::dump_on(outputStream* s) {
252 AbsSeq::dump_on(s);
253 s->print_cr("\t\t _length = %d, _next = %d", _length, _next);
254 for (int i = 0; i < _length; i++) {
255 if (i%5 == 0) {
256 s->cr();
257 s->print("\t");
258 }
259 s->print("\t[%d]=%7.3f", i, _sequence[i]);
260 }
261 s->cr();
262 }
263
264 HdrSeq::HdrSeq() {
265 _hdr = NEW_C_HEAP_ARRAY(int*, MagBuckets, mtInternal);
266 for (int c = 0; c < MagBuckets; c++) {
267 _hdr[c] = NULL;
268 }
269 }
270
271 HdrSeq::~HdrSeq() {
272 for (int c = 0; c < MagBuckets; c++) {
273 int* sub = _hdr[c];
274 if (sub != NULL) {
275 FREE_C_HEAP_ARRAY(int, sub, mtInternal);
276 }
277 }
278 FREE_C_HEAP_ARRAY(int*, _hdr, mtInternal);
279 }
280
281 void HdrSeq::add(double val) {
282 if (val < 0) {
283 assert (false, err_msg("value (%8.2f) is not negative", val));
284 val = 0;
285 }
286
287 NumberSeq::add(val);
288
289 double v = val;
290 int mag;
291 if (v > 0) {
292 mag = 0;
293 while (v > 1) {
294 mag++;
295 v /= 10;
296 }
297 while (v < 0.1) {
298 mag--;
299 v *= 10;
300 }
301 } else {
302 mag = MagMinimum;
303 }
304
305 int bucket = -MagMinimum + mag;
306 int sub_bucket = (int) (v * ValBuckets);
307
308 // Defensively saturate for product bits:
309 if (bucket < 0) {
310 assert (false, err_msg("bucket index (%d) underflow for value (%8.2f)", bucket, val));
311 bucket = 0;
312 }
313
314 if (bucket >= MagBuckets) {
315 assert (false, err_msg("bucket index (%d) overflow for value (%8.2f)", bucket, val));
316 bucket = MagBuckets - 1;
317 }
318
319 if (sub_bucket < 0) {
320 assert (false, err_msg("sub-bucket index (%d) underflow for value (%8.2f)", sub_bucket, val));
321 sub_bucket = 0;
322 }
323
324 if (sub_bucket >= ValBuckets) {
325 assert (false, err_msg("sub-bucket index (%d) overflow for value (%8.2f)", sub_bucket, val));
326 sub_bucket = ValBuckets - 1;
327 }
328
329 int* b = _hdr[bucket];
330 if (b == NULL) {
331 b = NEW_C_HEAP_ARRAY(int, ValBuckets, mtInternal);
332 for (int c = 0; c < ValBuckets; c++) {
333 b[c] = 0;
334 }
335 _hdr[bucket] = b;
336 }
337 b[sub_bucket]++;
338 }
339
340 double HdrSeq::percentile(double level) const {
341 // target should be non-zero to find the first sample
342 int target = MAX2(1, (int) (level * num() / 100));
343 int cnt = 0;
344 for (int mag = 0; mag < MagBuckets; mag++) {
345 if (_hdr[mag] != NULL) {
346 for (int val = 0; val < ValBuckets; val++) {
347 cnt += _hdr[mag][val];
348 if (cnt >= target) {
349 return pow(10.0, MagMinimum + mag) * val / ValBuckets;
350 }
351 }
352 }
353 }
354 return maximum();
355 }
356
357 BinaryMagnitudeSeq::BinaryMagnitudeSeq() {
358 _mags = NEW_C_HEAP_ARRAY(jlong, BitsPerJavaLong, mtInternal);
359 for (int c = 0; c < BitsPerJavaLong; c++) {
360 _mags[c] = 0;
361 }
362 _sum = 0;
363 }
364
365 BinaryMagnitudeSeq::~BinaryMagnitudeSeq() {
366 FREE_C_HEAP_ARRAY(size_t, _mags, mtInternal);
367 }
368
369 void BinaryMagnitudeSeq::add(size_t val) {
370 Atomic::add(val, &_sum);
371
372 int mag = log2_intptr(val) + 1;
373
374 // Defensively saturate for product bits:
375 if (mag < 0) {
376 assert (false, err_msg("bucket index (%d) underflow for value (" SIZE_FORMAT ")", mag, val));
377 mag = 0;
378 }
379
380 if (mag >= BitsPerJavaLong) {
381 assert (false, err_msg("bucket index (%d) overflow for value (" SIZE_FORMAT ")", mag, val));
382 mag = BitsPerJavaLong - 1;
383 }
384
385 Atomic::add(1, &_mags[mag]);
386 }
387
388 size_t BinaryMagnitudeSeq::level(int level) const {
389 if (0 <= level && level < BitsPerJavaLong) {
390 return _mags[level];
391 } else {
392 return 0;
393 }
394 }
395
396 size_t BinaryMagnitudeSeq::num() const {
397 int r = 0;
398 for (int c = 0; c < BitsPerJavaLong; c++) {
399 r += _mags[c];
400 }
401 return r;
402 }
403
404 size_t BinaryMagnitudeSeq::sum() const {
405 return _sum;
406 }
407
408 int BinaryMagnitudeSeq::min_level() const {
409 for (int c = 0; c < BitsPerJavaLong; c++) {
410 if (_mags[c] != 0) {
411 return c;
412 }
413 }
414 return BitsPerJavaLong - 1;
415 }
416
417 int BinaryMagnitudeSeq::max_level() const {
418 for (int c = BitsPerJavaLong - 1; c > 0; c--) {
419 if (_mags[c] != 0) {
420 return c;
421 }
422 }
423 return 0;
424 }
425