22:
690:
466:
relation is scanned. It loads large chunks of relation R into main memory. For each chunk, it scans S and evaluates the join condition on all tuple pairs, currently in memory. This reduces the number of times S is scanned to once per chunk.
624:
333:
393:
363:
464:
433:
413:
180:
160:
731:
475:
If the inner relation has an index on the attributes used in the join, then the naive nest loop join can be replaced with an index join.
105:
39:
755:
86:
58:
43:
531:
65:
724:
72:
32:
750:
54:
442:
join algorithm is a generalization of the simple nested loops algorithm that takes advantage of additional
717:
672:
659:
443:
286:
439:
79:
701:
697:
127:
639:
368:
338:
449:
418:
398:
165:
145:
744:
21:
435:
respectively and can easily be generalized to join any number of relations ...
634:
123:
689:
131:
673:
http://www.databaselecture.com/slides/9_Operator_Implementations.pdf
15:
276:
are number of blocks in relations R and S respectively, and n
705:
534:
528:
The time complexity for this variation improves from
452:
421:
401:
371:
341:
289:
168:
148:
619:{\displaystyle O(|R||S|){\text{ to }}O(|R|\log |S|)}
46:. Unsourced material may be challenged and removed.
618:
458:
427:
407:
387:
357:
327:
174:
154:
725:
126:that joins two relations by using two nested
8:
732:
718:
608:
600:
589:
581:
570:
562:
554:
549:
541:
533:
451:
420:
400:
380:
372:
370:
350:
342:
340:
317:
309:
304:
296:
288:
167:
147:
106:Learn how and when to remove this message
651:
446:to reduce the number of times that the
280:is the number of tuples in relation R.
395:is the number of tuples contained in
7:
686:
684:
130:. Join operations are important for
44:adding citations to reliable sources
704:. You can help Knowledge (XXG) by
660:"Understanding Nested Loops Joins"
14:
688:
20:
31:needs additional citations for
613:
609:
601:
590:
582:
578:
567:
563:
555:
550:
542:
538:
381:
373:
351:
343:
322:
318:
310:
305:
297:
293:
248:This algorithm will involve n
1:
230:satisfy the join condition
772:
683:
328:{\displaystyle O(|R||S|)}
182:are joined as follows:
756:Computer science stubs
620:
460:
429:
409:
389:
359:
329:
283:The algorithm runs in
176:
156:
621:
461:
430:
410:
390:
360:
330:
260:block transfers and n
177:
157:
532:
510:in the index lookup
471:Index join variation
450:
419:
399:
369:
339:
287:
166:
146:
40:improve this article
388:{\displaystyle |S|}
358:{\displaystyle |R|}
616:
456:
425:
405:
385:
355:
325:
172:
152:
55:"Nested loop join"
713:
712:
662:. 4 October 2012.
573:
459:{\displaystyle S}
440:block nested loop
428:{\displaystyle S}
408:{\displaystyle R}
188:nested_loop_join
175:{\displaystyle S}
155:{\displaystyle R}
116:
115:
108:
90:
763:
734:
727:
720:
698:computer science
692:
685:
675:
670:
664:
663:
656:
625:
623:
622:
617:
612:
604:
593:
585:
574:
571:
566:
558:
553:
545:
465:
463:
462:
457:
434:
432:
431:
426:
414:
412:
411:
406:
394:
392:
391:
386:
384:
376:
364:
362:
361:
356:
354:
346:
334:
332:
331:
326:
321:
313:
308:
300:
181:
179:
178:
173:
161:
159:
158:
153:
120:nested loop join
111:
104:
100:
97:
91:
89:
48:
24:
16:
771:
770:
766:
765:
764:
762:
761:
760:
751:Join algorithms
741:
740:
739:
738:
681:
679:
678:
671:
667:
658:
657:
653:
648:
640:Sort-merge join
631:
530:
529:
526:
473:
448:
447:
417:
416:
397:
396:
367:
366:
337:
336:
285:
284:
279:
275:
271:
267:
263:
259:
255:
251:
246:
164:
163:
144:
143:
140:
112:
101:
95:
92:
49:
47:
37:
25:
12:
11:
5:
769:
767:
759:
758:
753:
743:
742:
737:
736:
729:
722:
714:
711:
710:
693:
677:
676:
665:
650:
649:
647:
644:
643:
642:
637:
630:
627:
615:
611:
607:
603:
599:
596:
592:
588:
584:
580:
577:
572: to
569:
565:
561:
557:
552:
548:
544:
540:
537:
477:
472:
469:
455:
424:
404:
383:
379:
375:
353:
349:
345:
324:
320:
316:
312:
307:
303:
299:
295:
292:
277:
273:
269:
268:seeks, where b
265:
261:
257:
253:
249:
184:
171:
151:
142:Two relations
139:
136:
114:
113:
28:
26:
19:
13:
10:
9:
6:
4:
3:
2:
768:
757:
754:
752:
749:
748:
746:
735:
730:
728:
723:
721:
716:
715:
709:
707:
703:
700:article is a
699:
694:
691:
687:
682:
674:
669:
666:
661:
655:
652:
645:
641:
638:
636:
633:
632:
628:
626:
605:
597:
594:
586:
575:
559:
546:
535:
524:
520:
516:
513:
509:
505:
501:
498:
495:
491:
487:
484:
480:
476:
470:
468:
453:
445:
441:
436:
422:
402:
377:
347:
314:
301:
290:
281:
244:
240:
236:
233:
229:
225:
222:
219:
216:
212:
208:
205:
202:
198:
194:
191:
187:
183:
169:
149:
137:
135:
133:
129:
125:
121:
110:
107:
99:
88:
85:
81:
78:
74:
71:
67:
64:
60:
57: –
56:
52:
51:Find sources:
45:
41:
35:
34:
29:This article
27:
23:
18:
17:
706:expanding it
695:
680:
668:
654:
527:
522:
518:
514:
511:
507:
503:
499:
496:
493:
489:
485:
482:
478:
474:
437:
335:I/Os, where
282:
247:
242:
238:
234:
231:
227:
223:
220:
217:
214:
210:
206:
203:
200:
196:
192:
189:
185:
141:
134:management.
119:
117:
102:
96:January 2021
93:
83:
76:
69:
62:
50:
38:Please help
33:verification
30:
481:index_join
122:is a naive
745:Categories
646:References
517:tuple <
237:tuple <
66:newspapers
635:Hash join
598:
479:algorithm
186:algorithm
138:Algorithm
124:algorithm
629:See also
500:for each
486:for each
207:for each
193:for each
132:database
80:scholar
502:tuple
488:tuple
444:memory
209:tuple
195:tuple
82:
75:
68:
61:
53:
696:This
525:>
515:yield
272:and b
245:>
235:yield
128:loops
87:JSTOR
73:books
702:stub
438:The
415:and
365:and
232:then
226:and
162:and
59:news
595:log
506:in
492:in
256:+ b
213:in
199:in
42:by
747::
512:do
497:do
483:is
264:+b
252:*b
221:if
218:do
204:do
190:is
118:A
733:e
726:t
719:v
708:.
614:)
610:|
606:S
602:|
591:|
587:R
583:|
579:(
576:O
568:)
564:|
560:S
556:|
551:|
547:R
543:|
539:(
536:O
523:s
521:,
519:r
508:S
504:s
494:R
490:r
454:S
423:S
403:R
382:|
378:S
374:|
352:|
348:R
344:|
323:)
319:|
315:S
311:|
306:|
302:R
298:|
294:(
291:O
278:r
274:s
270:r
266:r
262:r
258:r
254:s
250:r
243:s
241:,
239:r
228:s
224:r
215:S
211:s
201:R
197:r
170:S
150:R
109:)
103:(
98:)
94:(
84:·
77:·
70:·
63:·
36:.
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.
