-C Add\stests\sto\sensure\s"PRAGMA\sincremental_vacuum"\sand\s"PRAGMA\sauto_vacuum\s=\sincremental"\shandle\scorrupt\sdatabases\scorrectly.
-D 2015-03-13T15:44:36.085
+C When\sestimating\sthe\snumber\sof\srows\svisited\sby\sa\srange\sscan\sfor\swhich\sthe\skeys\sconsist\sof\smore\sthan\sone\sfield,\sconsider\sprefixes\sof\sstat4\ssamples\sas\swell\sas\sthe\sfull\ssamples.
+D 2015-03-14T18:59:58.801
F Makefile.arm-wince-mingw32ce-gcc d6df77f1f48d690bd73162294bbba7f59507c72f
F Makefile.in 88a3e6261286db378fdffa1124cad11b3c05f5bb
F Makefile.linux-gcc 91d710bdc4998cb015f39edf3cb314ec4f4d7e23
F src/wal.c 39303f2c9db02a4e422cd8eb2c8760420c6a51fe
F src/wal.h df01efe09c5cb8c8e391ff1715cca294f89668a4
F src/walker.c c253b95b4ee44b21c406e2a1052636c31ea27804
-F src/where.c eb141b075776e9864d38f279333e2472a8653202
+F src/where.c 5a4e4ab378dbddeca59ad283c61aa67c6e56a913
F src/whereInt.h cbe4aa57326998d89e7698ca65bb7c28541d483c
F test/8_3_names.test ebbb5cd36741350040fd28b432ceadf495be25b2
F test/aggerror.test a867e273ef9e3d7919f03ef4f0e8c0d2767944f2
F test/analyze6.test f1c552ce39cca4ec922a7e4e0e5d0203d6b3281f
F test/analyze7.test bb1409afc9e8629e414387ef048b8e0e3e0bdc4f
F test/analyze8.test c05a461d0a6b05991106467d0c47480f2e709c82
-F test/analyze9.test 72795c8113604b5dcd47a1498a61d6d7fb5d041a
+F test/analyze9.test 2f6cfeae1fcc61cc531bd19f68e1e28fb6edafbf
F test/analyzeA.test 3335697f6700c7052295cfd0067fc5b2aacddf9a
F test/analyzeB.test 8bf35ee0a548aea831bf56762cb8e7fdb1db083d
F test/analyzeC.test 555a6cc388b9818b6eda6df816f01ce0a75d3a93
F tool/warnings-clang.sh f6aa929dc20ef1f856af04a730772f59283631d4
F tool/warnings.sh 0abfd78ceb09b7f7c27c688c8e3fe93268a13b32
F tool/win/sqlite.vsix deb315d026cc8400325c5863eef847784a219a2f
-P 5aa522dcb9bfa18d49683f7cc889516984e2bcd2
-R a79445283a8ae7c7f85ae571d23bc239
+P 1c2166cb2a387a0856f41b399c3648bf8c5fce73
+R f0473fc546184f7826d3d60610130f49
+T *branch * stat4-change
+T *sym-stat4-change *
+T -sym-trunk *
U dan
-Z d6c136b9ed1be16533c60706d0427e82
+Z e2a2579617ea31b6dadba1e9a71ba744
** Estimate the location of a particular key among all keys in an
** index. Store the results in aStat as follows:
**
-** aStat[0] Est. number of rows less than pVal
-** aStat[1] Est. number of rows equal to pVal
+** aStat[0] Est. number of rows less than pRec
+** aStat[1] Est. number of rows equal to pRec
**
** Return the index of the sample that is the smallest sample that
-** is greater than or equal to pRec.
+** is greater than or equal to pRec. Note that this index is not an index
+** into the aSample[] array - it is an index into a virtual set of samples
+** based on the contents of aSample[] and the number of fields in record
+** pRec.
*/
static int whereKeyStats(
Parse *pParse, /* Database connection */
){
IndexSample *aSample = pIdx->aSample;
int iCol; /* Index of required stats in anEq[] etc. */
+ int i; /* Index of first sample >= pRec */
+ int iSample; /* Smallest sample larger than or equal to pRec */
int iMin = 0; /* Smallest sample not yet tested */
- int i = pIdx->nSample; /* Smallest sample larger than or equal to pRec */
int iTest; /* Next sample to test */
int res; /* Result of comparison operation */
+ int nField; /* Number of fields in pRec */
+ tRowcnt iLower = 0; /* anLt[] + anEq[] of largest sample pRec is > */
#ifndef SQLITE_DEBUG
UNUSED_PARAMETER( pParse );
#endif
assert( pRec!=0 );
- iCol = pRec->nField - 1;
assert( pIdx->nSample>0 );
- assert( pRec->nField>0 && iCol<pIdx->nSampleCol );
+ assert( pRec->nField>0 && pRec->nField<=pIdx->nSampleCol );
+
+ /* Do a binary search to find the first sample greater than or equal
+ ** to pRec. If pRec contains a single field, the set of samples to search
+ ** is simply the aSample[] array. If the samples in aSample[] contain more
+ ** than one fields, all fields following the first are ignored.
+ **
+ ** If pRec contains N fields, where N is more than one, then as well as the
+ ** samples in aSample[] (truncated to N fields), the search also has to
+ ** consider prefixes of those samples. For example, if the set of samples
+ ** in aSample is:
+ **
+ ** aSample[0] = (a, 5)
+ ** aSample[1] = (a, 10)
+ ** aSample[2] = (b, 5)
+ ** aSample[3] = (c, 100)
+ ** aSample[4] = (c, 105)
+ **
+ ** Then the search space should ideally be the samples above and the
+ ** unique prefixes [a], [b] and [c]. But since that is hard to organize,
+ ** the code actually searches this set:
+ **
+ ** 0: (a)
+ ** 1: (a, 5)
+ ** 2: (a, 10)
+ ** 3: (a, 10)
+ ** 4: (b)
+ ** 5: (b, 5)
+ ** 6: (c)
+ ** 7: (c, 100)
+ ** 8: (c, 105)
+ ** 9: (c, 105)
+ **
+ ** For each sample in the aSample[] array, N samples are present in the
+ ** effective sample array. In the above, samples 0 and 1 are based on
+ ** sample aSample[0]. Samples 2 and 3 on aSample[1] etc.
+ **
+ ** Often, sample i of each block of N effective samples has (i+1) fields.
+ ** Except, each sample may be extended to ensure that it is greater than or
+ ** equal to the previous sample in the array. For example, in the above,
+ ** sample 2 is the first sample of a block of N samples, so at first it
+ ** appears that it should be 1 field in size. However, that would make it
+ ** smaller than sample 1, so the binary search would not work. As a result,
+ ** it is extended to two fields. The duplicates that this creates do not
+ ** cause any problems.
+ */
+ nField = pRec->nField;
+ iCol = 0;
+ iSample = pIdx->nSample * nField;
do{
- iTest = (iMin+i)/2;
- res = sqlite3VdbeRecordCompare(aSample[iTest].n, aSample[iTest].p, pRec);
+ int iSamp; /* Index in aSample[] of test sample */
+ int n; /* Number of fields in test sample */
+
+ iTest = (iMin+iSample)/2;
+ iSamp = iTest / nField;
+ if( iSamp>0 ){
+ /* The proposed effective sample is a prefix of sample aSample[iSamp].
+ ** Specifically, the shortest prefix of at least (1 + iTest%nField)
+ ** fields that is greater than the previous effective sample. */
+ for(n=(iTest % nField) + 1; n<nField; n++){
+ if( aSample[iSamp-1].anLt[n-1]!=aSample[iSamp].anLt[n-1] ) break;
+ }
+ }else{
+ n = iTest + 1;
+ }
+
+ pRec->nField = n;
+ res = sqlite3VdbeRecordCompare(aSample[iSamp].n, aSample[iSamp].p, pRec);
if( res<0 ){
+ iLower = aSample[iSamp].anLt[n-1] + aSample[iSamp].anEq[n-1];
+ iMin = iTest+1;
+ }else if( res==0 && n<nField ){
+ iLower = aSample[iSamp].anLt[n-1];
iMin = iTest+1;
+ res = -1;
}else{
- i = iTest;
+ iSample = iTest;
+ iCol = n-1;
}
- }while( res && iMin<i );
+ }while( res && iMin<iSample );
+ i = iSample / nField;
#ifdef SQLITE_DEBUG
/* The following assert statements check that the binary search code
** above found the right answer. This block serves no purpose other
** than to invoke the asserts. */
- if( res==0 ){
- /* If (res==0) is true, then sample $i must be equal to pRec */
- assert( i<pIdx->nSample );
- assert( 0==sqlite3VdbeRecordCompare(aSample[i].n, aSample[i].p, pRec)
- || pParse->db->mallocFailed );
- }else{
- /* Otherwise, pRec must be smaller than sample $i and larger than
- ** sample ($i-1). */
- assert( i==pIdx->nSample
- || sqlite3VdbeRecordCompare(aSample[i].n, aSample[i].p, pRec)>0
- || pParse->db->mallocFailed );
- assert( i==0
- || sqlite3VdbeRecordCompare(aSample[i-1].n, aSample[i-1].p, pRec)<0
- || pParse->db->mallocFailed );
+ if( pParse->db->mallocFailed==0 ){
+ if( res==0 ){
+ /* If (res==0) is true, then pRec must be equal to sample i. */
+ assert( i<pIdx->nSample );
+ assert( iCol==nField-1 );
+ pRec->nField = nField;
+ assert( 0==sqlite3VdbeRecordCompare(aSample[i].n, aSample[i].p, pRec)
+ || pParse->db->mallocFailed
+ );
+ }else{
+ /* Unless i==pIdx->nSample, indicating that pRec is larger than
+ ** all samples in the aSample[] array, pRec must be smaller than the
+ ** (iCol+1) field prefix of sample i. */
+ assert( i<=pIdx->nSample && i>=0 );
+ pRec->nField = iCol+1;
+ assert( i==pIdx->nSample
+ || sqlite3VdbeRecordCompare(aSample[i].n, aSample[i].p, pRec)>0
+ || pParse->db->mallocFailed );
+
+ /* if i==0 and iCol==0, then record pRec is smaller than all samples
+ ** in the aSample[] array. Otherwise, if (iCol>0) then pRec must
+ ** be greater than or equal to the (iCol) field prefix of sample i.
+ ** If (i>0), then pRec must also be greater than sample (i-1). */
+ if( iCol>0 ){
+ pRec->nField = iCol;
+ assert( sqlite3VdbeRecordCompare(aSample[i].n, aSample[i].p, pRec)<=0
+ || pParse->db->mallocFailed );
+ }
+ if( i>0 ){
+ pRec->nField = nField;
+ assert( sqlite3VdbeRecordCompare(aSample[i-1].n, aSample[i-1].p, pRec)<0
+ || pParse->db->mallocFailed );
+ }
+ }
}
#endif /* ifdef SQLITE_DEBUG */
- /* At this point, aSample[i] is the first sample that is greater than
- ** or equal to pVal. Or if i==pIdx->nSample, then all samples are less
- ** than pVal. If aSample[i]==pVal, then res==0.
- */
if( res==0 ){
+ /* Record pRec is equal to sample i */
+ assert( iCol==nField-1 );
aStat[0] = aSample[i].anLt[iCol];
aStat[1] = aSample[i].anEq[iCol];
}else{
- tRowcnt iLower, iUpper, iGap;
- if( i==0 ){
- iLower = 0;
- iUpper = aSample[0].anLt[iCol];
+ /* At this point, the (iCol+1) field prefix of aSample[i] is the first
+ ** sample that is greater than pRec. Or, if i==pIdx->nSample then pRec
+ ** is larger than all samples in the array. */
+ tRowcnt iUpper, iGap;
+ if( i>=pIdx->nSample ){
+ iUpper = sqlite3LogEstToInt(pIdx->aiRowLogEst[0]);
}else{
- i64 nRow0 = sqlite3LogEstToInt(pIdx->aiRowLogEst[0]);
- iUpper = i>=pIdx->nSample ? nRow0 : aSample[i].anLt[iCol];
- iLower = aSample[i-1].anEq[iCol] + aSample[i-1].anLt[iCol];
+ iUpper = aSample[i].anLt[iCol];
}
- aStat[1] = pIdx->aAvgEq[iCol];
+
if( iLower>=iUpper ){
iGap = 0;
}else{
iGap = iGap/3;
}
aStat[0] = iLower + iGap;
+ aStat[1] = pIdx->aAvgEq[iCol];
}
+
+ /* Restore the pRec->nField value before returning. */
+ pRec->nField = nField;
return i;
}
#endif /* SQLITE_ENABLE_STAT3_OR_STAT4 */
}
}
+#-------------------------------------------------------------------------
+# Check that a problem in they way stat4 data is used has been
+# resolved (see below).
+#
+reset_db
+do_test 26.1 {
+ db transaction {
+ execsql {
+ CREATE TABLE t1(x, y, z);
+ CREATE INDEX t1xy ON t1(x, y);
+ CREATE INDEX t1z ON t1(z);
+ }
+ for {set i 0} {$i < 10000} {incr i} {
+ execsql { INSERT INTO t1(x, y) VALUES($i, $i) }
+ }
+ for {set i 0} {$i < 10} {incr i} {
+ execsql {
+ WITH cnt(x) AS (SELECT 1 UNION ALL SELECT x+1 FROM cnt WHERE x<100)
+ INSERT INTO t1(x, y) SELECT 10000+$i, x FROM cnt;
+ INSERT INTO t1(x, y) SELECT 10000+$i, 100;
+ }
+ }
+ execsql {
+ UPDATE t1 SET z = rowid / 20;
+ ANALYZE;
+ }
+ }
+} {}
+
+do_execsql_test 26.2 {
+ SELECT count(*) FROM t1 WHERE x = 10000 AND y < 50;
+} {49}
+do_execsql_test 26.3 {
+ SELECT count(*) FROM t1 WHERE z = 444;
+} {20}
+
+# The analyzer knows that any (z=?) expression matches 20 rows. So it
+# will use index "t1z" if the estimate of hits for (x=10000 AND y<50)
+# is greater than 20 rows.
+#
+# And it should be. The analyzer has a stat4 sample as follows:
+#
+# sample=(x=10000, y=100) nLt=(10000 10099)
+#
+# There should be no other samples that start with (x=10000). So it knows
+# that (x=10000 AND y<50) must match somewhere between 0 and 99 rows, but
+# know more than that. Guessing less than 20 is therefore unreasonable.
+#
+# At one point though, due to a problem in whereKeyStats(), the planner was
+# estimating that (x=10000 AND y<50) would match only 2 rows.
+#
+do_eqp_test 26.4 {
+ SELECT * FROM t1 WHERE x = 10000 AND y < 50 AND z = 444;
+} {
+ 0 0 0 {SEARCH TABLE t1 USING INDEX t1z (z=?)}
+}
+
+
+
+
finish_test
+
+
+
projects / thirdparty / sqlite.git / commitdiff
