Many hyperlinks are disabled.
Use anonymous login
to enable hyperlinks.
Changes In Branch stat2-enhancement Excluding Merge-Ins
This is equivalent to a diff from 9660a0a2 to a2a9f640
2011-02-04
| ||
06:36 | Merge the stat2 query planner enhancements into the trunk. (check-in: 499edcbc user: drh tags: trunk) | |
2011-01-28
| ||
03:13 | Reactivate the analyze5.test script. (Closed-Leaf check-in: a2a9f640 user: drh tags: stat2-enhancement) | |
01:57 | Change the weighting of binary searches on tables to 1/10th the cost of a search on an index. Change the assumed reduction in search space from a indexed range constraint from 1/3rd to 1/4th. Do not let the estimated number of rows drop below 1. (check-in: 4847c6cb user: drh tags: stat2-enhancement) | |
2011-01-21
| ||
15:52 | Add options to test command [do_faultsim_test] to support testing VFS implementations. (check-in: 503ad889 user: dan tags: trunk) | |
2011-01-20
| ||
02:56 | The first of a planned series of enhancements to the query planner that enable it to make better use of sqlite_stat2 histograms when the table has many repeated values. (check-in: 2cd374cd user: drh tags: stat2-enhancement) | |
2011-01-19
| ||
21:58 | Comment improvements in pcache1.c. No changes to code. (check-in: 9660a0a2 user: drh tags: trunk) | |
2011-01-18
| ||
17:03 | Do not use mutexes in the pcache implementation unless SQLITE_ENABLE_MEMORY_MANAGMENT is defined. This is a performance enhancement. A side effect is that pcaches will not steal pages from one another unless ENABLE_MEMORY_MANAGEMENT is set, or unless SQLITE_THREADSAFE=0. (check-in: e5ca59e6 user: drh tags: trunk) | |
Changes to src/vdbemem.c.
︙ | ︙ | |||
1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 | if( SQLITE_OK==sqlite3ValueFromExpr(db,pExpr->pLeft,enc,affinity,&pVal) ){ sqlite3VdbeMemNumerify(pVal); pVal->u.i = -1 * pVal->u.i; /* (double)-1 In case of SQLITE_OMIT_FLOATING_POINT... */ pVal->r = (double)-1 * pVal->r; sqlite3ValueApplyAffinity(pVal, affinity, enc); } } #ifndef SQLITE_OMIT_BLOB_LITERAL else if( op==TK_BLOB ){ int nVal; assert( pExpr->u.zToken[0]=='x' || pExpr->u.zToken[0]=='X' ); assert( pExpr->u.zToken[1]=='\'' ); pVal = sqlite3ValueNew(db); | > > | 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 | if( SQLITE_OK==sqlite3ValueFromExpr(db,pExpr->pLeft,enc,affinity,&pVal) ){ sqlite3VdbeMemNumerify(pVal); pVal->u.i = -1 * pVal->u.i; /* (double)-1 In case of SQLITE_OMIT_FLOATING_POINT... */ pVal->r = (double)-1 * pVal->r; sqlite3ValueApplyAffinity(pVal, affinity, enc); } }else if( op==TK_NULL ){ pVal = sqlite3ValueNew(db); } #ifndef SQLITE_OMIT_BLOB_LITERAL else if( op==TK_BLOB ){ int nVal; assert( pExpr->u.zToken[0]=='x' || pExpr->u.zToken[0]=='X' ); assert( pExpr->u.zToken[1]=='\'' ); pVal = sqlite3ValueNew(db); |
︙ | ︙ |
Changes to src/where.c.
︙ | ︙ | |||
113 114 115 116 117 118 119 120 121 122 123 124 125 126 | #define TERM_DYNAMIC 0x01 /* Need to call sqlite3ExprDelete(db, pExpr) */ #define TERM_VIRTUAL 0x02 /* Added by the optimizer. Do not code */ #define TERM_CODED 0x04 /* This term is already coded */ #define TERM_COPIED 0x08 /* Has a child */ #define TERM_ORINFO 0x10 /* Need to free the WhereTerm.u.pOrInfo object */ #define TERM_ANDINFO 0x20 /* Need to free the WhereTerm.u.pAndInfo obj */ #define TERM_OR_OK 0x40 /* Used during OR-clause processing */ /* ** An instance of the following structure holds all information about a ** WHERE clause. Mostly this is a container for one or more WhereTerms. */ struct WhereClause { Parse *pParse; /* The parser context */ | > | 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 | #define TERM_DYNAMIC 0x01 /* Need to call sqlite3ExprDelete(db, pExpr) */ #define TERM_VIRTUAL 0x02 /* Added by the optimizer. Do not code */ #define TERM_CODED 0x04 /* This term is already coded */ #define TERM_COPIED 0x08 /* Has a child */ #define TERM_ORINFO 0x10 /* Need to free the WhereTerm.u.pOrInfo object */ #define TERM_ANDINFO 0x20 /* Need to free the WhereTerm.u.pAndInfo obj */ #define TERM_OR_OK 0x40 /* Used during OR-clause processing */ #define TERM_VNULL 0x80 /* Manufactured x>NULL or x<=NULL term */ /* ** An instance of the following structure holds all information about a ** WHERE clause. Mostly this is a container for one or more WhereTerms. */ struct WhereClause { Parse *pParse; /* The parser context */ |
︙ | ︙ | |||
206 207 208 209 210 211 212 213 214 215 216 217 218 219 | #define WO_LE (WO_EQ<<(TK_LE-TK_EQ)) #define WO_GT (WO_EQ<<(TK_GT-TK_EQ)) #define WO_GE (WO_EQ<<(TK_GE-TK_EQ)) #define WO_MATCH 0x040 #define WO_ISNULL 0x080 #define WO_OR 0x100 /* Two or more OR-connected terms */ #define WO_AND 0x200 /* Two or more AND-connected terms */ #define WO_ALL 0xfff /* Mask of all possible WO_* values */ #define WO_SINGLE 0x0ff /* Mask of all non-compound WO_* values */ /* ** Value for wsFlags returned by bestIndex() and stored in ** WhereLevel.wsFlags. These flags determine which search | > | 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 | #define WO_LE (WO_EQ<<(TK_LE-TK_EQ)) #define WO_GT (WO_EQ<<(TK_GT-TK_EQ)) #define WO_GE (WO_EQ<<(TK_GE-TK_EQ)) #define WO_MATCH 0x040 #define WO_ISNULL 0x080 #define WO_OR 0x100 /* Two or more OR-connected terms */ #define WO_AND 0x200 /* Two or more AND-connected terms */ #define WO_NOOP 0x800 /* This term does not restrict search space */ #define WO_ALL 0xfff /* Mask of all possible WO_* values */ #define WO_SINGLE 0x0ff /* Mask of all non-compound WO_* values */ /* ** Value for wsFlags returned by bestIndex() and stored in ** WhereLevel.wsFlags. These flags determine which search |
︙ | ︙ | |||
1056 1057 1058 1059 1060 1061 1062 | exprAnalyze(pSrc, pWC, idxNew); pTerm = &pWC->a[idxTerm]; pWC->a[idxNew].iParent = idxTerm; pTerm->nChild = 1; }else{ sqlite3ExprListDelete(db, pList); } | | | 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 | exprAnalyze(pSrc, pWC, idxNew); pTerm = &pWC->a[idxTerm]; pWC->a[idxNew].iParent = idxTerm; pTerm->nChild = 1; }else{ sqlite3ExprListDelete(db, pList); } pTerm->eOperator = WO_NOOP; /* case 1 trumps case 2 */ } } } #endif /* !SQLITE_OMIT_OR_OPTIMIZATION && !SQLITE_OMIT_SUBQUERY */ /* |
︙ | ︙ | |||
1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 | pTerm->nChild = 1; pTerm->wtFlags |= TERM_COPIED; pNewTerm->prereqAll = pTerm->prereqAll; } } #endif /* SQLITE_OMIT_VIRTUALTABLE */ /* Prevent ON clause terms of a LEFT JOIN from being used to drive ** an index for tables to the left of the join. */ pTerm->prereqRight |= extraRight; } /* | > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > | 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 | pTerm->nChild = 1; pTerm->wtFlags |= TERM_COPIED; pNewTerm->prereqAll = pTerm->prereqAll; } } #endif /* SQLITE_OMIT_VIRTUALTABLE */ #ifdef SQLITE_ENABLE_STAT2 /* When sqlite_stat2 histogram data is available an operator of the ** form "x IS NOT NULL" can sometimes be evaluated more efficiently ** as "x>NULL" if x is not an INTEGER PRIMARY KEY. So construct a ** virtual term of that form. ** ** Note that the virtual term must be tagged with TERM_VNULL. This ** TERM_VNULL tag will suppress the not-null check at the beginning ** of the loop. Without the TERM_VNULL flag, the not-null check at ** the start of the loop will prevent any results from being returned. */ if( pExpr->op==TK_NOTNULL && pExpr->pLeft->iColumn>=0 ){ Expr *pNewExpr; Expr *pLeft = pExpr->pLeft; int idxNew; WhereTerm *pNewTerm; pNewExpr = sqlite3PExpr(pParse, TK_GT, sqlite3ExprDup(db, pLeft, 0), sqlite3PExpr(pParse, TK_NULL, 0, 0, 0), 0); idxNew = whereClauseInsert(pWC, pNewExpr, TERM_VIRTUAL|TERM_DYNAMIC|TERM_VNULL); testcase( idxNew==0 ); pNewTerm = &pWC->a[idxNew]; pNewTerm->leftCursor = pLeft->iTable; pNewTerm->u.leftColumn = pLeft->iColumn; pNewTerm->eOperator = WO_GT; pNewTerm->iParent = idxTerm; pTerm = &pWC->a[idxTerm]; pTerm->nChild = 1; pTerm->wtFlags |= TERM_COPIED; pNewTerm->prereqAll = pTerm->prereqAll; } #endif /* SQLITE_ENABLE_STAT2 */ /* Prevent ON clause terms of a LEFT JOIN from being used to drive ** an index for tables to the left of the join. */ pTerm->prereqRight |= extraRight; } /* |
︙ | ︙ | |||
2197 2198 2199 2200 2201 2202 2203 | bestOrClauseIndex(pParse, pWC, pSrc, notReady, notValid, pOrderBy, pCost); } #endif /* SQLITE_OMIT_VIRTUALTABLE */ /* ** Argument pIdx is a pointer to an index structure that has an array of ** SQLITE_INDEX_SAMPLES evenly spaced samples of the first indexed column | | | | > > | > | > > > > > > | > > > > > > > > > > | 2235 2236 2237 2238 2239 2240 2241 2242 2243 2244 2245 2246 2247 2248 2249 2250 2251 2252 2253 2254 2255 2256 2257 2258 2259 2260 2261 2262 2263 2264 2265 2266 2267 2268 2269 2270 2271 2272 2273 2274 2275 2276 2277 2278 2279 2280 2281 2282 2283 2284 2285 2286 2287 2288 2289 2290 2291 2292 2293 2294 2295 2296 | bestOrClauseIndex(pParse, pWC, pSrc, notReady, notValid, pOrderBy, pCost); } #endif /* SQLITE_OMIT_VIRTUALTABLE */ /* ** Argument pIdx is a pointer to an index structure that has an array of ** SQLITE_INDEX_SAMPLES evenly spaced samples of the first indexed column ** stored in Index.aSample. These samples divide the domain of values stored ** the index into (SQLITE_INDEX_SAMPLES+1) regions. ** Region 0 contains all values less than the first sample value. Region ** 1 contains values between the first and second samples. Region 2 contains ** values between samples 2 and 3. And so on. Region SQLITE_INDEX_SAMPLES ** contains values larger than the last sample. ** ** If the index contains many duplicates of a single value, then it is ** possible that two or more adjacent samples can hold the same value. ** When that is the case, the smallest possible region code is returned ** when roundUp is false and the largest possible region code is returned ** when roundUp is true. ** ** If successful, this function determines which of the regions value ** pVal lies in, sets *piRegion to the region index (a value between 0 ** and SQLITE_INDEX_SAMPLES+1, inclusive) and returns SQLITE_OK. ** Or, if an OOM occurs while converting text values between encodings, ** SQLITE_NOMEM is returned and *piRegion is undefined. */ #ifdef SQLITE_ENABLE_STAT2 static int whereRangeRegion( Parse *pParse, /* Database connection */ Index *pIdx, /* Index to consider domain of */ sqlite3_value *pVal, /* Value to consider */ int roundUp, /* Return largest valid region if true */ int *piRegion /* OUT: Region of domain in which value lies */ ){ assert( roundUp==0 || roundUp==1 ); if( ALWAYS(pVal) ){ IndexSample *aSample = pIdx->aSample; int i = 0; int eType = sqlite3_value_type(pVal); if( eType==SQLITE_INTEGER || eType==SQLITE_FLOAT ){ double r = sqlite3_value_double(pVal); for(i=0; i<SQLITE_INDEX_SAMPLES; i++){ if( aSample[i].eType==SQLITE_NULL ) continue; if( aSample[i].eType>=SQLITE_TEXT ) break; if( roundUp ){ if( aSample[i].u.r>r ) break; }else{ if( aSample[i].u.r>=r ) break; } } }else if( eType==SQLITE_NULL ){ i = 0; if( roundUp ){ while( i<SQLITE_INDEX_SAMPLES && aSample[i].eType==SQLITE_NULL ) i++; } }else{ sqlite3 *db = pParse->db; CollSeq *pColl; const u8 *z; int n; |
︙ | ︙ | |||
2256 2257 2258 2259 2260 2261 2262 | return SQLITE_NOMEM; } assert( z && pColl && pColl->xCmp ); } n = sqlite3ValueBytes(pVal, pColl->enc); for(i=0; i<SQLITE_INDEX_SAMPLES; i++){ | | | | | | 2313 2314 2315 2316 2317 2318 2319 2320 2321 2322 2323 2324 2325 2326 2327 2328 2329 2330 2331 2332 2333 2334 2335 2336 2337 2338 2339 2340 2341 2342 2343 2344 2345 2346 2347 2348 | return SQLITE_NOMEM; } assert( z && pColl && pColl->xCmp ); } n = sqlite3ValueBytes(pVal, pColl->enc); for(i=0; i<SQLITE_INDEX_SAMPLES; i++){ int c; int eSampletype = aSample[i].eType; if( eSampletype==SQLITE_NULL || eSampletype<eType ) continue; if( (eSampletype!=eType) ) break; #ifndef SQLITE_OMIT_UTF16 if( pColl->enc!=SQLITE_UTF8 ){ int nSample; char *zSample = sqlite3Utf8to16( db, pColl->enc, aSample[i].u.z, aSample[i].nByte, &nSample ); if( !zSample ){ assert( db->mallocFailed ); return SQLITE_NOMEM; } c = pColl->xCmp(pColl->pUser, nSample, zSample, n, z); sqlite3DbFree(db, zSample); }else #endif { c = pColl->xCmp(pColl->pUser, aSample[i].nByte, aSample[i].u.z, n, z); } if( c-roundUp>=0 ) break; } } assert( i>=0 && i<=SQLITE_INDEX_SAMPLES ); *piRegion = i; } return SQLITE_OK; |
︙ | ︙ | |||
2360 2361 2362 2363 2364 2365 2366 | ** value of 1 indicates that the proposed range scan is expected to visit ** approximately 1/100th (1%) of the rows selected by the nEq equality ** constraints (if any). A return value of 100 indicates that it is expected ** that the range scan will visit every row (100%) selected by the equality ** constraints. ** ** In the absence of sqlite_stat2 ANALYZE data, each range inequality | | | | > > > > > > | | | | > | | > | < > | | > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > | > > > | > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > | | | | 2417 2418 2419 2420 2421 2422 2423 2424 2425 2426 2427 2428 2429 2430 2431 2432 2433 2434 2435 2436 2437 2438 2439 2440 2441 2442 2443 2444 2445 2446 2447 2448 2449 2450 2451 2452 2453 2454 2455 2456 2457 2458 2459 2460 2461 2462 2463 2464 2465 2466 2467 2468 2469 2470 2471 2472 2473 2474 2475 2476 2477 2478 2479 2480 2481 2482 2483 2484 2485 2486 2487 2488 2489 2490 2491 2492 2493 2494 2495 2496 2497 2498 2499 2500 2501 2502 2503 2504 2505 2506 2507 2508 2509 2510 2511 2512 2513 2514 2515 2516 2517 2518 2519 2520 2521 2522 2523 2524 2525 2526 2527 2528 2529 2530 2531 2532 2533 2534 2535 2536 2537 2538 2539 2540 2541 2542 2543 2544 2545 2546 2547 2548 2549 2550 2551 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 2562 2563 2564 2565 2566 2567 2568 2569 2570 2571 2572 2573 2574 2575 2576 2577 2578 2579 2580 2581 2582 2583 2584 2585 2586 2587 2588 2589 2590 2591 2592 2593 2594 2595 2596 2597 2598 2599 2600 2601 2602 2603 2604 2605 2606 2607 2608 2609 2610 2611 2612 2613 2614 2615 2616 2617 2618 2619 2620 2621 2622 2623 2624 2625 2626 2627 2628 2629 2630 2631 2632 2633 2634 2635 2636 2637 2638 2639 2640 2641 2642 2643 2644 2645 2646 2647 2648 2649 2650 2651 2652 2653 2654 2655 2656 2657 2658 2659 2660 2661 2662 2663 2664 2665 2666 2667 2668 2669 2670 | ** value of 1 indicates that the proposed range scan is expected to visit ** approximately 1/100th (1%) of the rows selected by the nEq equality ** constraints (if any). A return value of 100 indicates that it is expected ** that the range scan will visit every row (100%) selected by the equality ** constraints. ** ** In the absence of sqlite_stat2 ANALYZE data, each range inequality ** reduces the search space by 3/4ths. Hence a single constraint (x>?) ** results in a return of 25 and a range constraint (x>? AND x<?) results ** in a return of 6. */ static int whereRangeScanEst( Parse *pParse, /* Parsing & code generating context */ Index *p, /* The index containing the range-compared column; "x" */ int nEq, /* index into p->aCol[] of the range-compared column */ WhereTerm *pLower, /* Lower bound on the range. ex: "x>123" Might be NULL */ WhereTerm *pUpper, /* Upper bound on the range. ex: "x<455" Might be NULL */ int *piEst /* OUT: Return value */ ){ int rc = SQLITE_OK; #ifdef SQLITE_ENABLE_STAT2 if( nEq==0 && p->aSample ){ sqlite3_value *pLowerVal = 0; sqlite3_value *pUpperVal = 0; int iEst; int iLower = 0; int iUpper = SQLITE_INDEX_SAMPLES; int roundUpUpper; int roundUpLower; u8 aff = p->pTable->aCol[p->aiColumn[0]].affinity; if( pLower ){ Expr *pExpr = pLower->pExpr->pRight; rc = valueFromExpr(pParse, pExpr, aff, &pLowerVal); assert( pLower->eOperator==WO_GT || pLower->eOperator==WO_GE ); roundUpLower = (pLower->eOperator==WO_GT) ?1:0; } if( rc==SQLITE_OK && pUpper ){ Expr *pExpr = pUpper->pExpr->pRight; rc = valueFromExpr(pParse, pExpr, aff, &pUpperVal); assert( pUpper->eOperator==WO_LT || pUpper->eOperator==WO_LE ); roundUpUpper = (pUpper->eOperator==WO_LE) ?1:0; } if( rc!=SQLITE_OK || (pLowerVal==0 && pUpperVal==0) ){ sqlite3ValueFree(pLowerVal); sqlite3ValueFree(pUpperVal); goto range_est_fallback; }else if( pLowerVal==0 ){ rc = whereRangeRegion(pParse, p, pUpperVal, roundUpUpper, &iUpper); if( pLower ) iLower = iUpper/2; }else if( pUpperVal==0 ){ rc = whereRangeRegion(pParse, p, pLowerVal, roundUpLower, &iLower); if( pUpper ) iUpper = (iLower + SQLITE_INDEX_SAMPLES + 1)/2; }else{ rc = whereRangeRegion(pParse, p, pUpperVal, roundUpUpper, &iUpper); if( rc==SQLITE_OK ){ rc = whereRangeRegion(pParse, p, pLowerVal, roundUpLower, &iLower); } } WHERETRACE(("range scan regions: %d..%d\n", iLower, iUpper)); iEst = iUpper - iLower; testcase( iEst==SQLITE_INDEX_SAMPLES ); assert( iEst<=SQLITE_INDEX_SAMPLES ); if( iEst<1 ){ *piEst = 50/SQLITE_INDEX_SAMPLES; }else{ *piEst = (iEst*100)/SQLITE_INDEX_SAMPLES; } sqlite3ValueFree(pLowerVal); sqlite3ValueFree(pUpperVal); return rc; } range_est_fallback: #else UNUSED_PARAMETER(pParse); UNUSED_PARAMETER(p); UNUSED_PARAMETER(nEq); #endif assert( pLower || pUpper ); *piEst = 100; if( pLower && (pLower->wtFlags & TERM_VNULL)==0 ) *piEst /= 4; if( pUpper ) *piEst /= 4; return rc; } #ifdef SQLITE_ENABLE_STAT2 /* ** Estimate the number of rows that will be returned based on ** an equality constraint x=VALUE and where that VALUE occurs in ** the histogram data. This only works when x is the left-most ** column of an index and sqlite_stat2 histogram data is available ** for that index. ** ** Write the estimated row count into *pnRow and return SQLITE_OK. ** If unable to make an estimate, leave *pnRow unchanged and return ** non-zero. ** ** This routine can fail if it is unable to load a collating sequence ** required for string comparison, or if unable to allocate memory ** for a UTF conversion required for comparison. The error is stored ** in the pParse structure. */ int whereEqualScanEst( Parse *pParse, /* Parsing & code generating context */ Index *p, /* The index whose left-most column is pTerm */ Expr *pExpr, /* Expression for VALUE in the x=VALUE constraint */ double *pnRow /* Write the revised row estimate here */ ){ sqlite3_value *pRhs = 0; /* VALUE on right-hand side of pTerm */ int iLower, iUpper; /* Range of histogram regions containing pRhs */ u8 aff; /* Column affinity */ int rc; /* Subfunction return code */ double nRowEst; /* New estimate of the number of rows */ assert( p->aSample!=0 ); aff = p->pTable->aCol[p->aiColumn[0]].affinity; rc = valueFromExpr(pParse, pExpr, aff, &pRhs); if( rc ) goto whereEqualScanEst_cancel; if( pRhs==0 ) return SQLITE_NOTFOUND; rc = whereRangeRegion(pParse, p, pRhs, 0, &iLower); if( rc ) goto whereEqualScanEst_cancel; rc = whereRangeRegion(pParse, p, pRhs, 1, &iUpper); if( rc ) goto whereEqualScanEst_cancel; WHERETRACE(("equality scan regions: %d..%d\n", iLower, iUpper)); if( iLower>=iUpper ){ nRowEst = p->aiRowEst[0]/(SQLITE_INDEX_SAMPLES*2); if( nRowEst<*pnRow ) *pnRow = nRowEst; }else{ nRowEst = (iUpper-iLower)*p->aiRowEst[0]/SQLITE_INDEX_SAMPLES; *pnRow = nRowEst; } whereEqualScanEst_cancel: sqlite3ValueFree(pRhs); return rc; } #endif /* defined(SQLITE_ENABLE_STAT2) */ #ifdef SQLITE_ENABLE_STAT2 /* ** Estimate the number of rows that will be returned based on ** an IN constraint where the right-hand side of the IN operator ** is a list of values. Example: ** ** WHERE x IN (1,2,3,4) ** ** Write the estimated row count into *pnRow and return SQLITE_OK. ** If unable to make an estimate, leave *pnRow unchanged and return ** non-zero. ** ** This routine can fail if it is unable to load a collating sequence ** required for string comparison, or if unable to allocate memory ** for a UTF conversion required for comparison. The error is stored ** in the pParse structure. */ int whereInScanEst( Parse *pParse, /* Parsing & code generating context */ Index *p, /* The index whose left-most column is pTerm */ ExprList *pList, /* The value list on the RHS of "x IN (v1,v2,v3,...)" */ double *pnRow /* Write the revised row estimate here */ ){ sqlite3_value *pVal = 0; /* One value from list */ int iLower, iUpper; /* Range of histogram regions containing pRhs */ u8 aff; /* Column affinity */ int rc = SQLITE_OK; /* Subfunction return code */ double nRowEst; /* New estimate of the number of rows */ int nSpan = 0; /* Number of histogram regions spanned */ int nSingle = 0; /* Histogram regions hit by a single value */ int nNotFound = 0; /* Count of values that are not constants */ int i; /* Loop counter */ u8 aSpan[SQLITE_INDEX_SAMPLES+1]; /* Histogram regions that are spanned */ u8 aSingle[SQLITE_INDEX_SAMPLES+1]; /* Histogram regions hit once */ assert( p->aSample!=0 ); aff = p->pTable->aCol[p->aiColumn[0]].affinity; memset(aSpan, 0, sizeof(aSpan)); memset(aSingle, 0, sizeof(aSingle)); for(i=0; i<pList->nExpr; i++){ sqlite3ValueFree(pVal); rc = valueFromExpr(pParse, pList->a[i].pExpr, aff, &pVal); if( rc ) break; if( pVal==0 || sqlite3_value_type(pVal)==SQLITE_NULL ){ nNotFound++; continue; } rc = whereRangeRegion(pParse, p, pVal, 0, &iLower); if( rc ) break; rc = whereRangeRegion(pParse, p, pVal, 1, &iUpper); if( rc ) break; if( iLower>=iUpper ){ aSingle[iLower] = 1; }else{ assert( iLower>=0 && iUpper<=SQLITE_INDEX_SAMPLES ); while( iLower<iUpper ) aSpan[iLower++] = 1; } } if( rc==SQLITE_OK ){ for(i=nSpan=0; i<=SQLITE_INDEX_SAMPLES; i++){ if( aSpan[i] ){ nSpan++; }else if( aSingle[i] ){ nSingle++; } } nRowEst = (nSpan*2+nSingle)*p->aiRowEst[0]/(2*SQLITE_INDEX_SAMPLES) + nNotFound*p->aiRowEst[1]; if( nRowEst > p->aiRowEst[0] ) nRowEst = p->aiRowEst[0]; *pnRow = nRowEst; WHERETRACE(("IN row estimate: nSpan=%d, nSingle=%d, nNotFound=%d, est=%g\n", nSpan, nSingle, nNotFound, nRowEst)); } sqlite3ValueFree(pVal); return rc; } #endif /* defined(SQLITE_ENABLE_STAT2) */ /* ** Find the best query plan for accessing a particular table. Write the ** best query plan and its cost into the WhereCost object supplied as the ** last parameter. ** ** The lowest cost plan wins. The cost is an estimate of the amount of ** CPU and disk I/O needed to process the requested result. ** Factors that influence cost include: ** ** * The estimated number of rows that will be retrieved. (The ** fewer the better.) ** ** * Whether or not sorting must occur. ** ** * Whether or not there must be separate lookups in the ** index and in the main table. ** ** If there was an INDEXED BY clause (pSrc->pIndex) attached to the table in ** the SQL statement, then this function only considers plans using the ** named index. If no such plan is found, then the returned cost is ** SQLITE_BIG_DBL. If a plan is found that uses the named index, ** then the cost is calculated in the usual way. ** ** If a NOT INDEXED clause (pSrc->notIndexed!=0) was attached to the table ** in the SELECT statement, then no indexes are considered. However, the ** selected plan may still take advantage of the built-in rowid primary key ** index. */ static void bestBtreeIndex( Parse *pParse, /* The parsing context */ WhereClause *pWC, /* The WHERE clause */ struct SrcList_item *pSrc, /* The FROM clause term to search */ Bitmask notReady, /* Mask of cursors not available for indexing */ |
︙ | ︙ | |||
2506 2507 2508 2509 2510 2511 2512 | if( pSrc->pIndex ){ /* An INDEXED BY clause specifies a particular index to use */ pIdx = pProbe = pSrc->pIndex; wsFlagMask = ~(WHERE_ROWID_EQ|WHERE_ROWID_RANGE); eqTermMask = idxEqTermMask; }else{ | | | > > | > > > | > > | 2699 2700 2701 2702 2703 2704 2705 2706 2707 2708 2709 2710 2711 2712 2713 2714 2715 2716 2717 2718 2719 2720 2721 2722 2723 2724 2725 2726 2727 2728 2729 2730 2731 2732 2733 2734 2735 2736 2737 2738 2739 2740 2741 2742 2743 2744 2745 2746 2747 2748 2749 2750 2751 2752 2753 2754 2755 2756 2757 2758 | if( pSrc->pIndex ){ /* An INDEXED BY clause specifies a particular index to use */ pIdx = pProbe = pSrc->pIndex; wsFlagMask = ~(WHERE_ROWID_EQ|WHERE_ROWID_RANGE); eqTermMask = idxEqTermMask; }else{ /* There is no INDEXED BY clause. Create a fake Index object in local ** variable sPk to represent the rowid primary key index. Make this ** fake index the first in a chain of Index objects with all of the real ** indices to follow */ Index *pFirst; /* First of real indices on the table */ memset(&sPk, 0, sizeof(Index)); sPk.nColumn = 1; sPk.aiColumn = &aiColumnPk; sPk.aiRowEst = aiRowEstPk; sPk.onError = OE_Replace; sPk.pTable = pSrc->pTab; aiRowEstPk[0] = pSrc->pTab->nRowEst; aiRowEstPk[1] = 1; pFirst = pSrc->pTab->pIndex; if( pSrc->notIndexed==0 ){ /* The real indices of the table are only considered if the ** NOT INDEXED qualifier is omitted from the FROM clause */ sPk.pNext = pFirst; } pProbe = &sPk; wsFlagMask = ~( WHERE_COLUMN_IN|WHERE_COLUMN_EQ|WHERE_COLUMN_NULL|WHERE_COLUMN_RANGE ); eqTermMask = WO_EQ|WO_IN; pIdx = 0; } /* Loop over all indices looking for the best one to use */ for(; pProbe; pIdx=pProbe=pProbe->pNext){ const unsigned int * const aiRowEst = pProbe->aiRowEst; double cost; /* Cost of using pProbe */ double nRow; /* Estimated number of rows in result set */ int rev; /* True to scan in reverse order */ double nSearch; /* Estimated number of binary searches */ int wsFlags = 0; Bitmask used = 0; /* The following variables are populated based on the properties of ** index being evaluated. They are then used to determine the expected ** cost and number of rows returned. ** ** nEq: ** Number of equality terms that can be implemented using the index. ** In other words, the number of initial fields in the index that ** are used in == or IN or NOT NULL constraints of the WHERE clause. ** ** nInMul: ** The "in-multiplier". This is an estimate of how many seek operations ** SQLite must perform on the index in question. For example, if the ** WHERE clause is: ** ** WHERE a IN (1, 2, 3) AND b IN (4, 5, 6) |
︙ | ︙ | |||
2568 2569 2570 2571 2572 2573 2574 | ** ** If there exists a WHERE term of the form "x IN (SELECT ...)", then ** the sub-select is assumed to return 25 rows for the purposes of ** determining nInMul. ** ** bInEst: ** Set to true if there was at least one "x IN (SELECT ...)" term used | | > > | | | > | | | | | > > | | | | | | | | > > > > | > | > > > | 2768 2769 2770 2771 2772 2773 2774 2775 2776 2777 2778 2779 2780 2781 2782 2783 2784 2785 2786 2787 2788 2789 2790 2791 2792 2793 2794 2795 2796 2797 2798 2799 2800 2801 2802 2803 2804 2805 2806 2807 2808 2809 2810 2811 2812 2813 2814 2815 2816 2817 2818 2819 2820 2821 2822 2823 2824 2825 2826 2827 2828 2829 2830 2831 2832 2833 2834 2835 2836 2837 2838 2839 2840 2841 2842 2843 2844 2845 2846 2847 2848 2849 | ** ** If there exists a WHERE term of the form "x IN (SELECT ...)", then ** the sub-select is assumed to return 25 rows for the purposes of ** determining nInMul. ** ** bInEst: ** Set to true if there was at least one "x IN (SELECT ...)" term used ** in determining the value of nInMul. Note that the RHS of the ** IN operator must be a SELECT, not a value list, for this variable ** to be true. ** ** estBound: ** An estimate on the amount of the table that must be searched. A ** value of 100 means the entire table is searched. Range constraints ** might reduce this to a value less than 100 to indicate that only ** a fraction of the table needs searching. In the absence of ** sqlite_stat2 ANALYZE data, a single inequality reduces the search ** space to 1/4rd its original size. So an x>? constraint reduces ** estBound to 25. Two constraints (x>? AND x<?) reduce estBound to 6. ** ** bSort: ** Boolean. True if there is an ORDER BY clause that will require an ** external sort (i.e. scanning the index being evaluated will not ** correctly order records). ** ** bLookup: ** Boolean. True if a table lookup is required for each index entry ** visited. In other words, true if this is not a covering index. ** This is always false for the rowid primary key index of a table. ** For other indexes, it is true unless all the columns of the table ** used by the SELECT statement are present in the index (such an ** index is sometimes described as a covering index). ** For example, given the index on (a, b), the second of the following ** two queries requires table b-tree lookups in order to find the value ** of column c, but the first does not because columns a and b are ** both available in the index. ** ** SELECT a, b FROM tbl WHERE a = 1; ** SELECT a, b, c FROM tbl WHERE a = 1; */ int nEq; /* Number of == or IN terms matching index */ int bInEst = 0; /* True if "x IN (SELECT...)" seen */ int nInMul = 1; /* Number of distinct equalities to lookup */ int estBound = 100; /* Estimated reduction in search space */ int nBound = 0; /* Number of range constraints seen */ int bSort = 0; /* True if external sort required */ int bLookup = 0; /* True if not a covering index */ WhereTerm *pTerm; /* A single term of the WHERE clause */ #ifdef SQLITE_ENABLE_STAT2 WhereTerm *pFirstTerm = 0; /* First term matching the index */ #endif /* Determine the values of nEq and nInMul */ for(nEq=0; nEq<pProbe->nColumn; nEq++){ int j = pProbe->aiColumn[nEq]; pTerm = findTerm(pWC, iCur, j, notReady, eqTermMask, pIdx); if( pTerm==0 ) break; wsFlags |= (WHERE_COLUMN_EQ|WHERE_ROWID_EQ); if( pTerm->eOperator & WO_IN ){ Expr *pExpr = pTerm->pExpr; wsFlags |= WHERE_COLUMN_IN; if( ExprHasProperty(pExpr, EP_xIsSelect) ){ /* "x IN (SELECT ...)": Assume the SELECT returns 25 rows */ nInMul *= 25; bInEst = 1; }else if( ALWAYS(pExpr->x.pList && pExpr->x.pList->nExpr) ){ /* "x IN (value, value, ...)" */ nInMul *= pExpr->x.pList->nExpr; } }else if( pTerm->eOperator & WO_ISNULL ){ wsFlags |= WHERE_COLUMN_NULL; } #ifdef SQLITE_ENABLE_STAT2 if( nEq==0 && pProbe->aSample ) pFirstTerm = pTerm; #endif used |= pTerm->prereqRight; } /* Determine the value of estBound. */ if( nEq<pProbe->nColumn ){ int j = pProbe->aiColumn[nEq]; if( findTerm(pWC, iCur, j, notReady, WO_LT|WO_LE|WO_GT|WO_GE, pIdx) ){ |
︙ | ︙ | |||
2690 2691 2692 2693 2694 2695 2696 | wsFlags |= WHERE_IDX_ONLY; }else{ bLookup = 1; } } /* | | | > | > | < > | > > > > > > > | > > > > > > > > | > | > > > > > > > > > > > | | > > > > > > | > | | < > > | | > | 2903 2904 2905 2906 2907 2908 2909 2910 2911 2912 2913 2914 2915 2916 2917 2918 2919 2920 2921 2922 2923 2924 2925 2926 2927 2928 2929 2930 2931 2932 2933 2934 2935 2936 2937 2938 2939 2940 2941 2942 2943 2944 2945 2946 2947 2948 2949 2950 2951 2952 2953 2954 2955 2956 2957 2958 2959 2960 2961 2962 2963 2964 2965 2966 2967 2968 2969 2970 2971 2972 2973 2974 2975 2976 2977 2978 2979 2980 2981 2982 2983 2984 2985 2986 2987 2988 | wsFlags |= WHERE_IDX_ONLY; }else{ bLookup = 1; } } /* ** Estimate the number of rows of output. For an "x IN (SELECT...)" ** constraint, do not let the estimate exceed half the rows in the table. */ nRow = (double)(aiRowEst[nEq] * nInMul); if( bInEst && nRow*2>aiRowEst[0] ){ nRow = aiRowEst[0]/2; nInMul = (int)(nRow / aiRowEst[nEq]); } #ifdef SQLITE_ENABLE_STAT2 /* If the constraint is of the form x=VALUE and histogram ** data is available for column x, then it might be possible ** to get a better estimate on the number of rows based on ** VALUE and how common that value is according to the histogram. */ if( nRow>(double)1 && nEq==1 && pFirstTerm!=0 ){ if( pFirstTerm->eOperator==WO_EQ ){ whereEqualScanEst(pParse, pProbe, pFirstTerm->pExpr->pRight, &nRow); }else if( pFirstTerm->eOperator==WO_IN && bInEst==0 ){ whereInScanEst(pParse, pProbe, pFirstTerm->pExpr->x.pList, &nRow); } } #endif /* SQLITE_ENABLE_STAT2 */ /* Adjust the number of rows and the cost downward to reflect rows ** that are excluded by range constraints. */ nRow = (nRow * (double)estBound) / (double)100; if( nRow<1 ) nRow = 1; /* Assume constant cost to advance from one row to the next and ** logarithmic cost to do a binary search. Hence, the initial cost ** is the number of output rows plus log2(table-size) times the ** number of binary searches. ** ** Because fan-out on tables is so much higher than the fan-out on ** indices (because table btrees contain only integer keys in non-leaf ** nodes) we weight the cost of a table binary search as 1/10th the ** cost of an index binary search. */ if( pIdx ){ if( bLookup ){ /* For an index lookup followed by a table lookup: ** nInMul index searches to find the start of each index range ** + nRow steps through the index ** + nRow table searches to lookup the table entry using the rowid */ nSearch = nInMul + nRow/10; }else{ /* For a covering index: ** nInMul binary searches to find the initial entry ** + nRow steps through the index */ nSearch = nInMul; } }else{ /* For a rowid primary key lookup: ** nInMult binary searches to find the initial entry scaled by 1/10th ** + nRow steps through the table */ nSearch = nInMul/10; } cost = nRow + nSearch*estLog(aiRowEst[0]); /* Add in the estimated cost of sorting the result. This cost is expanded ** by a fudge factor of 3.0 to account for the fact that a sorting step ** involves a write and is thus more expensive than a lookup step. */ if( bSort ){ cost += nRow*estLog(nRow)*(double)3; } /**** Cost of using this index has now been computed ****/ /* If there are additional constraints on this table that cannot ** be used with the current index, but which might lower the number ** of output rows, adjust the nRow value accordingly. This only ** matters if the current index is the least costly, so do not bother ** with this step if we already know this index will not be chosen. |
︙ | ︙ | |||
2764 2765 2766 2767 2768 2769 2770 | }else{ /* Assume each additional equality match reduces the result ** set size by a factor of 10 */ nRow /= 10; } }else if( pTerm->eOperator & (WO_LT|WO_LE|WO_GT|WO_GE) ){ if( nSkipRange ){ | | | > > > > | | 3015 3016 3017 3018 3019 3020 3021 3022 3023 3024 3025 3026 3027 3028 3029 3030 3031 3032 3033 3034 3035 3036 3037 3038 3039 3040 3041 | }else{ /* Assume each additional equality match reduces the result ** set size by a factor of 10 */ nRow /= 10; } }else if( pTerm->eOperator & (WO_LT|WO_LE|WO_GT|WO_GE) ){ if( nSkipRange ){ /* Ignore the first nSkipRange range constraints since the index ** has already accounted for these */ nSkipRange--; }else{ /* Assume each additional range constraint reduces the result ** set size by a factor of 3. Indexed range constraints reduce ** the search space by a larger factor: 4. We make indexed range ** more selective intentionally because of the subjective ** observation that indexed range constraints really are more ** selective in practice, on average. */ nRow /= 3; } }else if( pTerm->eOperator!=WO_NOOP ){ /* Any other expression lowers the output row count by half */ nRow /= 2; } } if( nRow<2 ) nRow = 2; } |
︙ | ︙ | |||
3610 3611 3612 3613 3614 3615 3616 | start_constraints = pRangeStart || nEq>0; /* Seek the index cursor to the start of the range. */ nConstraint = nEq; if( pRangeStart ){ Expr *pRight = pRangeStart->pExpr->pRight; sqlite3ExprCode(pParse, pRight, regBase+nEq); | > | > | 3865 3866 3867 3868 3869 3870 3871 3872 3873 3874 3875 3876 3877 3878 3879 3880 3881 | start_constraints = pRangeStart || nEq>0; /* Seek the index cursor to the start of the range. */ nConstraint = nEq; if( pRangeStart ){ Expr *pRight = pRangeStart->pExpr->pRight; sqlite3ExprCode(pParse, pRight, regBase+nEq); if( (pRangeStart->wtFlags & TERM_VNULL)==0 ){ sqlite3ExprCodeIsNullJump(v, pRight, regBase+nEq, addrNxt); } if( zStartAff ){ if( sqlite3CompareAffinity(pRight, zStartAff[nEq])==SQLITE_AFF_NONE){ /* Since the comparison is to be performed with no conversions ** applied to the operands, set the affinity to apply to pRight to ** SQLITE_AFF_NONE. */ zStartAff[nEq] = SQLITE_AFF_NONE; } |
︙ | ︙ | |||
3649 3650 3651 3652 3653 3654 3655 | ** range (if any). */ nConstraint = nEq; if( pRangeEnd ){ Expr *pRight = pRangeEnd->pExpr->pRight; sqlite3ExprCacheRemove(pParse, regBase+nEq, 1); sqlite3ExprCode(pParse, pRight, regBase+nEq); | > | > | 3906 3907 3908 3909 3910 3911 3912 3913 3914 3915 3916 3917 3918 3919 3920 3921 3922 | ** range (if any). */ nConstraint = nEq; if( pRangeEnd ){ Expr *pRight = pRangeEnd->pExpr->pRight; sqlite3ExprCacheRemove(pParse, regBase+nEq, 1); sqlite3ExprCode(pParse, pRight, regBase+nEq); if( (pRangeEnd->wtFlags & TERM_VNULL)==0 ){ sqlite3ExprCodeIsNullJump(v, pRight, regBase+nEq, addrNxt); } if( zEndAff ){ if( sqlite3CompareAffinity(pRight, zEndAff[nEq])==SQLITE_AFF_NONE){ /* Since the comparison is to be performed with no conversions ** applied to the operands, set the affinity to apply to pRight to ** SQLITE_AFF_NONE. */ zEndAff[nEq] = SQLITE_AFF_NONE; } |
︙ | ︙ |
Changes to test/analyze2.test.
︙ | ︙ | |||
150 151 152 153 154 155 156 | SELECT * FROM t1 WHERE x BETWEEN 100 AND 500 AND y BETWEEN 400 AND 700 } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_y (y>? AND y<?) (~75 rows)} } do_eqp_test 2.7 { SELECT * FROM t1 WHERE x BETWEEN -400 AND -300 AND y BETWEEN 100 AND 300 } { | | | | | | 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 | SELECT * FROM t1 WHERE x BETWEEN 100 AND 500 AND y BETWEEN 400 AND 700 } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_y (y>? AND y<?) (~75 rows)} } do_eqp_test 2.7 { SELECT * FROM t1 WHERE x BETWEEN -400 AND -300 AND y BETWEEN 100 AND 300 } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_x (x>? AND x<?) (~12 rows)} } do_eqp_test 2.8 { SELECT * FROM t1 WHERE x BETWEEN 100 AND 300 AND y BETWEEN -400 AND -300 } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_y (y>? AND y<?) (~12 rows)} } do_eqp_test 2.9 { SELECT * FROM t1 WHERE x BETWEEN 500 AND 100 AND y BETWEEN 100 AND 300 } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_x (x>? AND x<?) (~12 rows)} } do_eqp_test 2.10 { SELECT * FROM t1 WHERE x BETWEEN 100 AND 300 AND y BETWEEN 500 AND 100 } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_y (y>? AND y<?) (~12 rows)} } do_test analyze2-3.1 { set alphabet [list a b c d e f g h i j] execsql BEGIN for {set i 0} {$i < 1000} {incr i} { set str [lindex $alphabet [expr ($i/100)%10]] |
︙ | ︙ | |||
203 204 205 206 207 208 209 | SELECT * FROM t1 WHERE x BETWEEN 100 AND 500 AND y BETWEEN 'a' AND 'b' } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_y (y>? AND y<?) (~50 rows)} } do_eqp_test 3.4 { SELECT * FROM t1 WHERE x BETWEEN 100 AND 400 AND y BETWEEN 'a' AND 'h' } { | | | 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 | SELECT * FROM t1 WHERE x BETWEEN 100 AND 500 AND y BETWEEN 'a' AND 'b' } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_y (y>? AND y<?) (~50 rows)} } do_eqp_test 3.4 { SELECT * FROM t1 WHERE x BETWEEN 100 AND 400 AND y BETWEEN 'a' AND 'h' } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_x (x>? AND x<?) (~100 rows)} } do_eqp_test 3.5 { SELECT * FROM t1 WHERE x<'a' AND y>'h' } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1_y (y>?) (~66 rows)} } do_eqp_test 3.6 { |
︙ | ︙ | |||
238 239 240 241 242 243 244 245 246 247 | execsql { INSERT INTO t3 VALUES($str, $str) } } execsql COMMIT execsql ANALYZE } {} do_test analyze2-4.2 { execsql { SELECT tbl,idx,group_concat(sample,' ') FROM sqlite_stat2 WHERE idx = 't3a' | > | > | 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 | execsql { INSERT INTO t3 VALUES($str, $str) } } execsql COMMIT execsql ANALYZE } {} do_test analyze2-4.2 { execsql { PRAGMA automatic_index=OFF; SELECT tbl,idx,group_concat(sample,' ') FROM sqlite_stat2 WHERE idx = 't3a' GROUP BY tbl,idx; PRAGMA automatic_index=ON; } } {t3 t3a {AfA bEj CEj dEj EEj fEj GEj hEj IEj jEj}} do_test analyze2-4.3 { execsql { SELECT tbl,idx,group_concat(sample,' ') FROM sqlite_stat2 WHERE idx = 't3b' |
︙ | ︙ | |||
404 405 406 407 408 409 410 | DELETE FROM sqlite_stat2; } sqlite3 db test.db eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } | | | | | | | | 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 | DELETE FROM sqlite_stat2; } sqlite3 db test.db eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } } {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~60000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-6.2.2 { db cache flush execsql ANALYZE eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } } {0 0 1 {SEARCH TABLE t6 USING COVERING INDEX t6i (a>?) (~1 rows)} 0 1 0 {SEARCH TABLE t5 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-6.2.3 { sqlite3 db test.db eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } } {0 0 1 {SEARCH TABLE t6 USING COVERING INDEX t6i (a>?) (~1 rows)} 0 1 0 {SEARCH TABLE t5 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-6.2.4 { execsql { PRAGMA writable_schema = 1; DELETE FROM sqlite_master WHERE tbl_name = 'sqlite_stat1'; } sqlite3 db test.db eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } } {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~60000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-6.2.5 { execsql { PRAGMA writable_schema = 1; DELETE FROM sqlite_master WHERE tbl_name = 'sqlite_stat2'; } sqlite3 db test.db eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } } {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~60000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-6.2.6 { execsql { PRAGMA writable_schema = 1; INSERT INTO sqlite_master SELECT * FROM master; } sqlite3 db test.db execsql ANALYZE eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } } {0 0 1 {SEARCH TABLE t6 USING COVERING INDEX t6i (a>?) (~1 rows)} 0 1 0 {SEARCH TABLE t5 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} #-------------------------------------------------------------------- # These tests, analyze2-7.*, test that the sqlite_stat2 functionality # works in shared-cache mode. Note that these tests reuse the database # created for the analyze2-6.* tests. # ifcapable shared_cache { |
︙ | ︙ | |||
497 498 499 500 501 502 503 | } {20} do_test analyze2-7.5 { eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } db1 | | | | | | | | 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 | } {20} do_test analyze2-7.5 { eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } db1 } {0 0 1 {SEARCH TABLE t6 USING COVERING INDEX t6i (a>?) (~1 rows)} 0 1 0 {SEARCH TABLE t5 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-7.6 { incr_schema_cookie test.db execsql { SELECT * FROM sqlite_master } db2 eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } db2 } {0 0 1 {SEARCH TABLE t6 USING COVERING INDEX t6i (a>?) (~1 rows)} 0 1 0 {SEARCH TABLE t5 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-7.7 { incr_schema_cookie test.db execsql { SELECT * FROM sqlite_master } db1 eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } db1 } {0 0 1 {SEARCH TABLE t6 USING COVERING INDEX t6i (a>?) (~1 rows)} 0 1 0 {SEARCH TABLE t5 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-7.8 { execsql { DELETE FROM sqlite_stat2 } db2 execsql { SELECT * FROM sqlite_master } db1 eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } db1 } {0 0 1 {SEARCH TABLE t6 USING COVERING INDEX t6i (a>?) (~1 rows)} 0 1 0 {SEARCH TABLE t5 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-7.9 { execsql { SELECT * FROM sqlite_master } db2 eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } db2 } {0 0 1 {SEARCH TABLE t6 USING COVERING INDEX t6i (a>?) (~1 rows)} 0 1 0 {SEARCH TABLE t5 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} do_test analyze2-7.10 { incr_schema_cookie test.db execsql { SELECT * FROM sqlite_master } db1 eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND t5.a>1 AND t5.a<15 AND t6.a>1 } db1 } {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~1 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}} db1 close db2 close sqlite3_enable_shared_cache $::enable_shared_cache } finish_test |
Changes to test/analyze3.test.
︙ | ︙ | |||
244 245 246 247 248 249 250 | append t [lindex {a b c d e f g h i j} [expr ($i%10)]] execsql { INSERT INTO t1 VALUES($i, $t) } } execsql COMMIT } {} do_eqp_test analyze3-2.2 { SELECT count(a) FROM t1 WHERE b LIKE 'a%' | | | 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 | append t [lindex {a b c d e f g h i j} [expr ($i%10)]] execsql { INSERT INTO t1 VALUES($i, $t) } } execsql COMMIT } {} do_eqp_test analyze3-2.2 { SELECT count(a) FROM t1 WHERE b LIKE 'a%' } {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (b>? AND b<?) (~30000 rows)}} do_eqp_test analyze3-2.3 { SELECT count(a) FROM t1 WHERE b LIKE '%a' } {0 0 0 {SCAN TABLE t1 (~500000 rows)}} do_test analyze3-2.4 { sf_execsql { SELECT count(*) FROM t1 WHERE b LIKE 'a%' } } {101 0 100} |
︙ | ︙ |
Added test/analyze5.test.
> > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 | # 2011 January 19 # # The author disclaims copyright to this source code. In place of # a legal notice, here is a blessing: # # May you do good and not evil. # May you find forgiveness for yourself and forgive others. # May you share freely, never taking more than you give. # #*********************************************************************** # # This file implements tests for SQLite library. The focus of the tests # in this file is the use of the sqlite_stat2 histogram data on tables # with many repeated values and only a few distinct values. # set testdir [file dirname $argv0] source $testdir/tester.tcl ifcapable !stat2 { finish_test return } set testprefix analyze5 proc eqp {sql {db db}} { uplevel execsql [list "EXPLAIN QUERY PLAN $sql"] $db } unset -nocomplain i t u v w x y z do_test analyze5-1.0 { db eval {CREATE TABLE t1(t,u,v TEXT COLLATE nocase,w,x,y,z)} for {set i 0} {$i < 1000} {incr i} { set y [expr {$i>=25 && $i<=50}] set z [expr {($i>=400) + ($i>=700) + ($i>=875)}] set x $z set w $z set t [expr {$z+0.5}] switch $z { 0 {set u "alpha"; unset x} 1 {set u "bravo"} 2 {set u "charlie"} 3 {set u "delta"; unset w} } if {$i%2} {set v $u} {set v [string toupper $u]} db eval {INSERT INTO t1 VALUES($t,$u,$v,$w,$x,$y,$z)} } db eval { CREATE INDEX t1t ON t1(t); -- 0.5, 1.5, 2.5, and 3.5 CREATE INDEX t1u ON t1(u); -- text CREATE INDEX t1v ON t1(v); -- mixed case text CREATE INDEX t1w ON t1(w); -- integers 0, 1, 2 and a few NULLs CREATE INDEX t1x ON t1(x); -- integers 1, 2, 3 and many NULLs CREATE INDEX t1y ON t1(y); -- integers 0 and very few 1s CREATE INDEX t1z ON t1(z); -- integers 0, 1, 2, and 3 ANALYZE; SELECT sample FROM sqlite_stat2 WHERE idx='t1u' ORDER BY sampleno; } } {alpha alpha alpha alpha bravo bravo bravo charlie charlie delta} do_test analyze5-1.1 { string tolower \ [db eval {SELECT sample from sqlite_stat2 WHERE idx='t1v' ORDER BY sampleno}] } {alpha alpha alpha alpha bravo bravo bravo charlie charlie delta} do_test analyze5-1.2 { db eval {SELECT sample from sqlite_stat2 WHERE idx='t1w' ORDER BY sampleno} } {{} 0 0 0 0 1 1 1 2 2} do_test analyze5-1.3 { db eval {SELECT sample from sqlite_stat2 WHERE idx='t1x' ORDER BY sampleno} } {{} {} {} {} 1 1 1 2 2 3} do_test analyze5-1.4 { db eval {SELECT sample from sqlite_stat2 WHERE idx='t1y' ORDER BY sampleno} } {0 0 0 0 0 0 0 0 0 0} do_test analyze5-1.5 { db eval {SELECT sample from sqlite_stat2 WHERE idx='t1z' ORDER BY sampleno} } {0 0 0 0 1 1 1 2 2 3} do_test analyze5-1.6 { db eval {SELECT sample from sqlite_stat2 WHERE idx='t1t' ORDER BY sampleno} } {0.5 0.5 0.5 0.5 1.5 1.5 1.5 2.5 2.5 3.5} # Verify that range queries generate the correct row count estimates # foreach {testid where index rows} { 1 {z>=0 AND z<=0} t1z 400 2 {z>=1 AND z<=1} t1z 300 3 {z>=2 AND z<=2} t1z 200 4 {z>=3 AND z<=3} t1z 100 5 {z>=4 AND z<=4} t1z 50 6 {z>=-1 AND z<=-1} t1z 50 7 {z>1 AND z<3} t1z 200 8 {z>0 AND z<100} t1z 600 9 {z>=1 AND z<100} t1z 600 10 {z>1 AND z<100} t1z 300 11 {z>=2 AND z<100} t1z 300 12 {z>2 AND z<100} t1z 100 13 {z>=3 AND z<100} t1z 100 14 {z>3 AND z<100} t1z 50 15 {z>=4 AND z<100} t1z 50 16 {z>=-100 AND z<=-1} t1z 50 17 {z>=-100 AND z<=0} t1z 400 18 {z>=-100 AND z<0} t1z 50 19 {z>=-100 AND z<=1} t1z 700 20 {z>=-100 AND z<2} t1z 700 21 {z>=-100 AND z<=2} {} 111 22 {z>=-100 AND z<3} {} 111 31 {z>=0.0 AND z<=0.0} t1z 400 32 {z>=1.0 AND z<=1.0} t1z 300 33 {z>=2.0 AND z<=2.0} t1z 200 34 {z>=3.0 AND z<=3.0} t1z 100 35 {z>=4.0 AND z<=4.0} t1z 50 36 {z>=-1.0 AND z<=-1.0} t1z 50 37 {z>1.5 AND z<3.0} t1z 200 38 {z>0.5 AND z<100} t1z 600 39 {z>=1.0 AND z<100} t1z 600 40 {z>1.5 AND z<100} t1z 300 41 {z>=2.0 AND z<100} t1z 300 42 {z>2.1 AND z<100} t1z 100 43 {z>=3.0 AND z<100} t1z 100 44 {z>3.2 AND z<100} t1z 50 45 {z>=4.0 AND z<100} t1z 50 46 {z>=-100 AND z<=-1.0} t1z 50 47 {z>=-100 AND z<=0.0} t1z 400 48 {z>=-100 AND z<0.0} t1z 50 49 {z>=-100 AND z<=1.0} t1z 700 50 {z>=-100 AND z<2.0} t1z 700 51 {z>=-100 AND z<=2.0} {} 111 52 {z>=-100 AND z<3.0} {} 111 101 {z=-1} t1z 50 102 {z=0} t1z 400 103 {z=1} t1z 300 104 {z=2} t1z 200 105 {z=3} t1z 100 106 {z=4} t1z 50 107 {z=-10.0} t1z 50 108 {z=0.0} t1z 400 109 {z=1.0} t1z 300 110 {z=2.0} t1z 200 111 {z=3.0} t1z 100 112 {z=4.0} t1z 50 113 {z=1.5} t1z 50 114 {z=2.5} t1z 50 201 {z IN (-1)} t1z 50 202 {z IN (0)} t1z 400 203 {z IN (1)} t1z 300 204 {z IN (2)} t1z 200 205 {z IN (3)} t1z 100 206 {z IN (4)} t1z 50 207 {z IN (0.5)} t1z 50 208 {z IN (0,1)} t1z 700 209 {z IN (0,1,2)} {} 100 210 {z IN (0,1,2,3)} {} 100 211 {z IN (0,1,2,3,4,5)} {} 100 212 {z IN (1,2)} t1z 500 213 {z IN (2,3)} t1z 300 214 {z=3 OR z=2} t1z 300 215 {z IN (-1,3)} t1z 150 216 {z=-1 OR z=3} t1z 150 300 {y=0} {} 100 301 {y=1} t1y 50 302 {y=0.1} t1y 50 } { # Verify that the expected index is used with the expected row count do_test analyze5-1.${testid}a { set x [lindex [eqp "SELECT * FROM t1 WHERE $where"] 3] set idx {} regexp {INDEX (t1.) } $x all idx regexp {~([0-9]+) rows} $x all nrow list $idx $nrow } [list $index $rows] # Verify that the same result is achieved regardless of whether or not # the index is used do_test analyze5-1.${testid}b { set w2 [string map {y +y z +z} $where] set a1 [db eval "SELECT rowid FROM t1 NOT INDEXED WHERE $w2\ ORDER BY +rowid"] set a2 [db eval "SELECT rowid FROM t1 WHERE $where ORDER BY +rowid"] if {$a1==$a2} { set res ok } else { set res "a1=\[$a1\] a2=\[$a2\]" } set res } {ok} } finish_test |
Changes to test/e_createtable.test.
︙ | ︙ | |||
1375 1376 1377 1378 1379 1380 1381 | 1 "EXPLAIN QUERY PLAN SELECT * FROM t1 WHERE b = 5" {0 0 0 {SEARCH TABLE t1 USING INDEX sqlite_autoindex_t1_1 (b=?) (~1 rows)}} 2 "EXPLAIN QUERY PLAN SELECT * FROM t2 ORDER BY b, c" {0 0 0 {SCAN TABLE t2 USING INDEX sqlite_autoindex_t2_1 (~1000000 rows)}} 3 "EXPLAIN QUERY PLAN SELECT * FROM t2 WHERE b=10 AND c>10" | | | 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 | 1 "EXPLAIN QUERY PLAN SELECT * FROM t1 WHERE b = 5" {0 0 0 {SEARCH TABLE t1 USING INDEX sqlite_autoindex_t1_1 (b=?) (~1 rows)}} 2 "EXPLAIN QUERY PLAN SELECT * FROM t2 ORDER BY b, c" {0 0 0 {SCAN TABLE t2 USING INDEX sqlite_autoindex_t2_1 (~1000000 rows)}} 3 "EXPLAIN QUERY PLAN SELECT * FROM t2 WHERE b=10 AND c>10" {0 0 0 {SEARCH TABLE t2 USING INDEX sqlite_autoindex_t2_1 (b=? AND c>?) (~2 rows)}} } # EVIDENCE-OF: R-45493-35653 A CHECK constraint may be attached to a # column definition or specified as a table constraint. In practice it # makes no difference. # # All the tests that deal with CHECK constraints below (4.11.* and |
︙ | ︙ |
Changes to test/eqp.test.
︙ | ︙ | |||
388 389 390 391 392 393 394 | # EVIDENCE-OF: R-22253-05302 sqlite> EXPLAIN QUERY PLAN SELECT t1.*, # t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2; 0|0|0|SEARCH TABLE t1 # USING COVERING INDEX i2 (a=? AND b>?) (~3 rows) 0|1|1|SCAN TABLE t2 # (~1000000 rows) do_execsql_test 5.4.0 {CREATE TABLE t2(c, d)} det 5.4.1 "SELECT t1.*, t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2" { | | | | 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 | # EVIDENCE-OF: R-22253-05302 sqlite> EXPLAIN QUERY PLAN SELECT t1.*, # t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2; 0|0|0|SEARCH TABLE t1 # USING COVERING INDEX i2 (a=? AND b>?) (~3 rows) 0|1|1|SCAN TABLE t2 # (~1000000 rows) do_execsql_test 5.4.0 {CREATE TABLE t2(c, d)} det 5.4.1 "SELECT t1.*, t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2" { 0 0 0 {SEARCH TABLE t1 USING COVERING INDEX i2 (a=? AND b>?) (~2 rows)} 0 1 1 {SCAN TABLE t2 (~1000000 rows)} } # EVIDENCE-OF: R-21040-07025 sqlite> EXPLAIN QUERY PLAN SELECT t1.*, # t2.* FROM t2, t1 WHERE t1.a=1 AND t1.b>2; 0|0|1|SEARCH TABLE t1 # USING COVERING INDEX i2 (a=? AND b>?) (~3 rows) 0|1|0|SCAN TABLE t2 # (~1000000 rows) det 5.5 "SELECT t1.*, t2.* FROM t2, t1 WHERE t1.a=1 AND t1.b>2" { 0 0 1 {SEARCH TABLE t1 USING COVERING INDEX i2 (a=? AND b>?) (~2 rows)} 0 1 0 {SCAN TABLE t2 (~1000000 rows)} } # EVIDENCE-OF: R-39007-61103 sqlite> CREATE INDEX i3 ON t1(b); # sqlite> EXPLAIN QUERY PLAN SELECT * FROM t1 WHERE a=1 OR b=2; # 0|0|0|SEARCH TABLE t1 USING COVERING INDEX i2 (a=?) (~10 rows) # 0|0|0|SEARCH TABLE t1 USING INDEX i3 (b=?) (~10 rows) |
︙ | ︙ |
Changes to test/indexedby.test.
︙ | ︙ | |||
150 151 152 153 154 155 156 | # Test embedding an INDEXED BY in a CREATE VIEW statement. This block # also tests that nothing bad happens if an index refered to by # a CREATE VIEW statement is dropped and recreated. # do_execsql_test indexedby-5.1 { CREATE VIEW v2 AS SELECT * FROM t1 INDEXED BY i1 WHERE a > 5; EXPLAIN QUERY PLAN SELECT * FROM v2 | | | | 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 | # Test embedding an INDEXED BY in a CREATE VIEW statement. This block # also tests that nothing bad happens if an index refered to by # a CREATE VIEW statement is dropped and recreated. # do_execsql_test indexedby-5.1 { CREATE VIEW v2 AS SELECT * FROM t1 INDEXED BY i1 WHERE a > 5; EXPLAIN QUERY PLAN SELECT * FROM v2 } {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a>?) (~250000 rows)}} do_execsql_test indexedby-5.2 { EXPLAIN QUERY PLAN SELECT * FROM v2 WHERE b = 10 } {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a>?) (~25000 rows)}} do_test indexedby-5.3 { execsql { DROP INDEX i1 } catchsql { SELECT * FROM v2 } } {1 {no such index: i1}} do_test indexedby-5.4 { # Recreate index i1 in such a way as it cannot be used by the view query. execsql { CREATE INDEX i1 ON t1(b) } |
︙ | ︙ |
Changes to test/like.test.
︙ | ︙ | |||
703 704 705 706 707 708 709 | INSERT INTO t10 VALUES(12,12,12,12,12,12); INSERT INTO t10 VALUES(123,123,123,123,123,123); INSERT INTO t10 VALUES(234,234,234,234,234,234); INSERT INTO t10 VALUES(345,345,345,345,345,345); INSERT INTO t10 VALUES(45,45,45,45,45,45); } count { | | | | | | | | | | | | | | 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 | INSERT INTO t10 VALUES(12,12,12,12,12,12); INSERT INTO t10 VALUES(123,123,123,123,123,123); INSERT INTO t10 VALUES(234,234,234,234,234,234); INSERT INTO t10 VALUES(345,345,345,345,345,345); INSERT INTO t10 VALUES(45,45,45,45,45,45); } count { SELECT a FROM t10 WHERE b LIKE '12%' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.2 { count { SELECT a FROM t10 WHERE c LIKE '12%' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.3 { count { SELECT a FROM t10 WHERE d LIKE '12%' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.4 { count { SELECT a FROM t10 WHERE e LIKE '12%' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.5 { count { SELECT a FROM t10 WHERE f LIKE '12%' ORDER BY +a; } } {12 123 scan 3 like 0} do_test like-10.6 { count { SELECT a FROM t10 WHERE a LIKE '12%' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.10 { execsql { CREATE TABLE t10b( a INTEGER PRIMARY KEY, b INTEGER UNIQUE, c NUMBER UNIQUE, d BLOB UNIQUE, e UNIQUE, f TEXT UNIQUE ); INSERT INTO t10b SELECT * FROM t10; } count { SELECT a FROM t10b WHERE b GLOB '12*' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.11 { count { SELECT a FROM t10b WHERE c GLOB '12*' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.12 { count { SELECT a FROM t10b WHERE d GLOB '12*' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.13 { count { SELECT a FROM t10b WHERE e GLOB '12*' ORDER BY +a; } } {12 123 scan 5 like 6} do_test like-10.14 { count { SELECT a FROM t10b WHERE f GLOB '12*' ORDER BY +a; } } {12 123 scan 3 like 0} do_test like-10.15 { count { SELECT a FROM t10b WHERE a GLOB '12*' ORDER BY +a; } } {12 123 scan 5 like 6} } # LIKE and GLOB where the default collating sequence is not appropriate # but an index with the appropriate collating sequence exists. # |
︙ | ︙ | |||
815 816 817 818 819 820 821 | SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a; } } {abc abcd nosort t11 *} do_test like-11.3 { queryplan { PRAGMA case_sensitive_like=OFF; CREATE INDEX t11b ON t11(b); | | | | | | | | | 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 | SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a; } } {abc abcd nosort t11 *} do_test like-11.3 { queryplan { PRAGMA case_sensitive_like=OFF; CREATE INDEX t11b ON t11(b); SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY +a; } } {abc abcd ABC ABCD sort {} t11b} do_test like-11.4 { queryplan { PRAGMA case_sensitive_like=ON; SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a; } } {abc abcd nosort t11 *} do_test like-11.5 { queryplan { PRAGMA case_sensitive_like=OFF; DROP INDEX t11b; CREATE INDEX t11bnc ON t11(b COLLATE nocase); SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY +a; } } {abc abcd ABC ABCD sort {} t11bnc} do_test like-11.6 { queryplan { CREATE INDEX t11bb ON t11(b COLLATE binary); SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY +a; } } {abc abcd ABC ABCD sort {} t11bnc} do_test like-11.7 { queryplan { PRAGMA case_sensitive_like=ON; SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY +a; } } {abc abcd sort {} t11bb} do_test like-11.8 { queryplan { PRAGMA case_sensitive_like=OFF; SELECT b FROM t11 WHERE b GLOB 'abc*' ORDER BY +a; } } {abc abcd sort {} t11bb} do_test like-11.9 { queryplan { CREATE INDEX t11cnc ON t11(c COLLATE nocase); CREATE INDEX t11cb ON t11(c COLLATE binary); SELECT c FROM t11 WHERE c LIKE 'abc%' ORDER BY +a; } } {abc abcd ABC ABCD sort {} t11cnc} do_test like-11.10 { queryplan { SELECT c FROM t11 WHERE c GLOB 'abc*' ORDER BY +a; } } {abc abcd sort {} t11cb} finish_test |
Changes to test/minmax3.test.
︙ | ︙ | |||
48 49 50 51 52 53 54 55 56 57 58 59 60 61 | INSERT INTO t1 VALUES('1', 'I', 'one'); INSERT INTO t1 VALUES('2', 'IV', 'four'); INSERT INTO t1 VALUES('2', NULL, 'three'); INSERT INTO t1 VALUES('2', 'II', 'two'); INSERT INTO t1 VALUES('2', 'V', 'five'); INSERT INTO t1 VALUES('3', 'VI', 'six'); COMMIT; } } {} do_test minmax3-1.1.1 { # Linear scan. count { SELECT max(y) FROM t1 WHERE x = '2'; } } {V 5} do_test minmax3-1.1.2 { | > | 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | INSERT INTO t1 VALUES('1', 'I', 'one'); INSERT INTO t1 VALUES('2', 'IV', 'four'); INSERT INTO t1 VALUES('2', NULL, 'three'); INSERT INTO t1 VALUES('2', 'II', 'two'); INSERT INTO t1 VALUES('2', 'V', 'five'); INSERT INTO t1 VALUES('3', 'VI', 'six'); COMMIT; PRAGMA automatic_index=OFF; } } {} do_test minmax3-1.1.1 { # Linear scan. count { SELECT max(y) FROM t1 WHERE x = '2'; } } {V 5} do_test minmax3-1.1.2 { |
︙ | ︙ |
Changes to test/where3.test.
︙ | ︙ | |||
221 222 223 224 225 226 227 | CREATE TABLE t301(a INTEGER PRIMARY KEY,b,c); CREATE INDEX t301c ON t301(c); INSERT INTO t301 VALUES(1,2,3); CREATE TABLE t302(x, y); ANALYZE; explain query plan SELECT * FROM t302, t301 WHERE t302.x=5 AND t301.a=t302.y; } { | | > | | 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 | CREATE TABLE t301(a INTEGER PRIMARY KEY,b,c); CREATE INDEX t301c ON t301(c); INSERT INTO t301 VALUES(1,2,3); CREATE TABLE t302(x, y); ANALYZE; explain query plan SELECT * FROM t302, t301 WHERE t302.x=5 AND t301.a=t302.y; } { 0 0 0 {SCAN TABLE t302 (~1 rows)} 0 1 1 {SEARCH TABLE t301 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)} } exit do_execsql_test where3-3.1 { explain query plan SELECT * FROM t301, t302 WHERE t302.x=5 AND t301.a=t302.y; } { 0 0 1 {SCAN TABLE t302 (~1 rows)} 0 1 0 {SEARCH TABLE t301 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)} } # Verify that when there are multiple tables in a join which must be # full table scans that the query planner attempts put the table with # the fewest number of output rows as the outer loop. # |
︙ | ︙ |
Changes to test/where9.test.
︙ | ︙ | |||
468 469 470 471 472 473 474 | # Likewise, inequalities in an AND are preferred over inequalities in # an OR. # do_execsql_test where9-5.3 { EXPLAIN QUERY PLAN SELECT a FROM t1 WHERE b>1000 AND (c>=31031 OR d IS NULL) } { | | | 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 | # Likewise, inequalities in an AND are preferred over inequalities in # an OR. # do_execsql_test where9-5.3 { EXPLAIN QUERY PLAN SELECT a FROM t1 WHERE b>1000 AND (c>=31031 OR d IS NULL) } { 0 0 0 {SEARCH TABLE t1 USING INDEX t1b (b>?) (~125000 rows)} } } ############################################################################ # Make sure OR-clauses work correctly on UPDATE and DELETE statements. do_test where9-6.2.1 { |
︙ | ︙ |