if( sqlite3_libversion_number()>=3008002 )
#endif
{
- pIdxInfo->estimatedRows = nRow;
+ pIdxInfo->estimatedRows = MAX(1, nRow);
}
#endif
}
** a) If a MATCH operator is present, the cost depends on the other
** constraints also present. As follows:
**
-** * No other constraints: cost=1000.0
-** * One rowid range constraint: cost=750.0
-** * Both rowid range constraints: cost=500.0
-** * An == rowid constraint: cost=100.0
+** * No other constraints: cost=50000.0
+** * One rowid range constraint: cost=37500.0
+** * Both rowid range constraints: cost=30000.0
+** * An == rowid constraint: cost=25000.0
**
** b) Otherwise, if there is no MATCH:
**
-** * No other constraints: cost=1000000.0
-** * One rowid range constraint: cost=750000.0
-** * Both rowid range constraints: cost=250000.0
-** * An == rowid constraint: cost=10.0
+** * No other constraints: cost=3000000.0
+** * One rowid range constraints: cost=2250000.0
+** * Both rowid range constraint: cost=750000.0
+** * An == rowid constraint: cost=25.0
**
** Costs are not modified by the ORDER BY clause.
+**
+** The ratios used in case (a) are based on informal results obtained from
+** the tool/fts5cost.tcl script. The "MATCH and ==" combination has the
+** cost set quite high because the query may be a prefix query. Unless
+** there is a prefix index, prefix queries with rowid constraints are much
+** more expensive than non-prefix queries with rowid constraints.
+**
+** The estimated rows returned is set to the cost/40. For simple queries,
+** experimental results show that cost/4 might be about right. But for
+** more complex queries that use multiple terms the number of rows might
+** be far fewer than this. So we compromise and use cost/40.
*/
static int fts5BestIndexMethod(sqlite3_vtab *pVTab, sqlite3_index_info *pInfo){
Fts5Table *pTab = (Fts5Table*)pVTab;
/* Calculate the estimated cost based on the flags set in idxFlags. */
if( bSeenEq ){
- pInfo->estimatedCost = nSeenMatch ? 1000.0 : 25.0;
- fts5SetUniqueFlag(pInfo);
+ pInfo->estimatedCost = nSeenMatch ? 25000.0 : 25.0;
fts5SetEstimatedRows(pInfo, 1);
+ fts5SetUniqueFlag(pInfo);
}else{
- if( bSeenLt && bSeenGt ){
- pInfo->estimatedCost = nSeenMatch ? 5000.0 : 750000.0;
- }else if( bSeenLt || bSeenGt ){
- pInfo->estimatedCost = nSeenMatch ? 7500.0 : 2250000.0;
+ i64 nEstRows;
+ if( nSeenMatch ){
+ if( bSeenLt && bSeenGt ){
+ pInfo->estimatedCost = 50000.0;
+ }else if( bSeenLt || bSeenGt ){
+ pInfo->estimatedCost = 37500.0;
+ }else{
+ pInfo->estimatedCost = 50000.0;
+ }
+ nEstRows = (i64)(pInfo->estimatedCost / 40.0);
+ for(i=1; i<nSeenMatch; i++){
+ pInfo->estimatedCost *= 2.5;
+ nEstRows = nEstRows / 2;
+ }
}else{
- pInfo->estimatedCost = nSeenMatch ? 10000.0 : 3000000.0;
- }
- for(i=1; i<nSeenMatch; i++){
- pInfo->estimatedCost *= 0.4;
+ if( bSeenLt && bSeenGt ){
+ pInfo->estimatedCost = 750000.0;
+ }else if( bSeenLt || bSeenGt ){
+ pInfo->estimatedCost = 2250000.0;
+ }else{
+ pInfo->estimatedCost = 3000000.0;
+ }
+ nEstRows = (i64)(pInfo->estimatedCost / 4.0);
}
- fts5SetEstimatedRows(pInfo, (i64)(pInfo->estimatedCost / 4.0));
+ fts5SetEstimatedRows(pInfo, nEstRows);
}
pInfo->idxNum = idxFlags;
`--SCAN vt VIRTUAL TABLE INDEX 0:=
}
+do_eqp_test 1.5 {
+ SELECT * FROM vt, t1
+ WHERE vt.rowid = t1.rowid AND vt MATCH ? AND b = ?
+} {
+ QUERY PLAN
+ |--SCAN vt VIRTUAL TABLE INDEX 0:M1
+ `--SEARCH t1 USING INTEGER PRIMARY KEY (rowid=?)
+}
+
finish_test
--- /dev/null
+#
+# 2026 March 20
+#
+# 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 script extracts the documentation for the API used by fts5 auxiliary
+# functions from header file fts5.h. It outputs html text on stdout that
+# is included in the documentation on the web.
+#
+
+
+sqlite3 db fts5cost.db
+
+# Create an IPK table with 1,000,000 entries. Short records.
+#
+set res [list [catch { db eval {SELECT count(*) FROM t1} } msg] $msg]
+if {$res!="0 1000000"} {
+ db eval {
+ PRAGMA mmap_size = 1000000000; -- 1GB
+ DROP TABLE IF EXISTS t1;
+ CREATE TABLE t1(a INTEGER PRIMARY KEY, b TEXT);
+ WITH s(i) AS (
+ SELECT 1 UNION ALL SELECT i+1 FROM s WHERE i<1_000_000
+ )
+ INSERT INTO t1 SELECT i, hex(randomblob(8)) FROM s;
+ }
+}
+
+# Create an FTS5 table with 1,000,000 entries. Each row contains a single
+# column containing a document of 100 terms chosen pseudo-randomly from
+# a vocabularly of 2000.
+set res [list [catch { db eval {SELECT count(*) FROM f1} } msg] $msg]
+if {$res!="0 1000000"} {
+ set nVocab 2000
+ set nTerm 100
+ db eval {
+ BEGIN;
+ DROP TABLE IF EXISTS vocab1;
+ CREATE TABLE vocab1(w);
+ }
+ for {set ii 0} {$ii<$nVocab} {incr ii} {
+ set word [format %06x [expr {int(abs(rand()) * 0xFFFFFF)}]]
+ db eval { INSERT INTO vocab1 VALUES($word) }
+ lappend lVocab $word
+ }
+ db func doc doc
+ proc doc {} {
+ for {set ii 0} {$ii<$::nTerm} {incr ii} {
+ lappend ret [lindex $::lVocab [expr int(abs(rand())*$::nVocab)]]
+ }
+ set ret
+ }
+ db eval {
+ DROP TABLE IF EXISTS f1;
+ CREATE VIRTUAL TABLE f1 USING fts5(x);
+ WITH s(i) AS (
+ SELECT 1 UNION ALL SELECT i+1 FROM s WHERE i<1_000_000
+ )
+ INSERT INTO f1(rowid, x) SELECT i, doc() FROM s;
+ COMMIT;
+ }
+} else {
+ set lVocab [db eval { SELECT * FROM vocab1 }]
+ set nVocab [llength $lVocab]
+}
+
+proc rowid_query {n} {
+ set rowid 654
+ for {set ii 0} {$ii<$n} {incr ii} {
+ db eval { SELECT b FROM t1 WHERE a = $rowid }
+ set rowid [expr {($rowid + 7717) % 1000000}]
+ }
+}
+
+proc rowid_query_fts {n} {
+ set rowid 654
+ for {set ii 0} {$ii<$n} {incr ii} {
+ db eval { SELECT * FROM f1 WHERE rowid = $rowid }
+ set rowid [expr {($rowid + 7717) % 1000000}]
+ }
+}
+
+proc match_query_fts {n} {
+ set idx 654
+ for {set ii 0} {$ii<$n} {incr ii} {
+ set match [lrange $::lVocab $idx $idx+1]
+ db eval { SELECT * FROM f1($match) }
+ set idx [expr {($idx + 7717) % $::nVocab}]
+ }
+}
+
+proc prefix_query_fts {n} {
+ set idx 654
+ for {set ii 0} {$ii<$n} {incr ii} {
+ set match "[lindex $::lVocab $idx]*"
+ db eval { SELECT * FROM f1($match) }
+ set idx [expr {($idx + 7717) % $::nVocab}]
+ }
+}
+
+proc match_rowid_query_fts {n} {
+ set idx 654
+ for {set ii 0} {$ii<$n} {incr ii} {
+ set match "[lindex $::lVocab $idx]"
+ db eval { SELECT * FROM f1($match) WHERE rowid=500000 }
+ set idx [expr {($idx + 7717) % $::nVocab}]
+ }
+}
+
+proc prefix_rowid_query_fts {n} {
+ set idx 654
+ for {set ii 0} {$ii<$n} {incr ii} {
+ set match "[lindex $::lVocab $idx]*"
+ db eval { SELECT * FROM f1($match) WHERE rowid=500000 }
+ set idx [expr {($idx + 7717) % $::nVocab}]
+ }
+}
+
+
+proc mytime {cmd div} {
+ set tm [time $cmd]
+ expr {[lindex $tm 0] / $div}
+}
+
+#set us [mytime { match_rowid_query_fts 1000 } 1000]
+#puts "1000 match/rowid queries on fts5 table: ${us} per query"
+
+set us [mytime { prefix_rowid_query_fts 1000 } 1000]
+puts "1000 prefix/rowid queries on fts5 table: ${us} per query"
+
+set us [mytime { match_query_fts 10 } 10]
+puts "10 match queries on fts5 table: ${us} per query"
+
+set us [mytime { prefix_query_fts 10 } 10]
+puts "10 prefix queries on fts5 table: ${us} per query"
+
+set us [mytime { prefix_rowid_query_fts 1000 } 1000]
+puts "1000 prefix/rowid queries on fts5 table: ${us} per query"
+
+set us [mytime { rowid_query 10000 } 10000]
+puts "10000 by-rowid queries on normal table: ${us} per query"
+
+set us [mytime { rowid_query_fts 10000 } 10000]
+puts "10000 by-rowid queries on fts5 table: ${us} per query"
+
+
-C Restructure\ssome\sinternal\ssubroutine\ssignatures\sfor\simproved\nperformance\sof\saffinity\stype\sconversions.
-D 2026-03-19T17:08:08.454
+C Update\sfts5\sscan\scosts\sto\stake\sinto\saccount\sthat\sa\sprefix\squery\scombined\swith\sa\srowid\sequality\sconstraint\sis\sstill\squite\sexpensive.
+D 2026-03-19T17:56:10.586
F .fossil-settings/binary-glob 61195414528fb3ea9693577e1980230d78a1f8b0a54c78cf1b9b24d0a409ed6a x
F .fossil-settings/empty-dirs dbb81e8fc0401ac46a1491ab34a7f2c7c0452f2f06b54ebb845d024ca8283ef1
F .fossil-settings/ignore-glob 35175cdfcf539b2318cb04a9901442804be81cd677d8b889fcc9149c21f239ea
F ext/fts5/fts5_expr.c 71d48e8cf0358deace4949276647d317ff7665db6db09f40b81e2e7fe6664c7c
F ext/fts5/fts5_hash.c d5871df92ce3fa210a650cf419ee916b87c29977e86084d06612edf772bff6f5
F ext/fts5/fts5_index.c f8cfa37bb7397e5ede20242e4c9cb030bc8b4584ce3f23a5e2495038c0ae64bd
-F ext/fts5/fts5_main.c 6889f1373c469d515e792fb3d783c2218e63c560433ebd66edc0f740ab086c1b
+F ext/fts5/fts5_main.c b0fed47b3b4420ba6810373480a75bc28a9c0b7d16478d19a396436fb3ff17d7
F ext/fts5/fts5_storage.c 19bc7c4cbe1e6a2dd9849ef7d84b5ca1fcbf194cefc3e386b901e00e08bf05c2
F ext/fts5/fts5_tcl.c 2be6cc14f9448f720fd4418339cd202961a0801ea9424cb3d9de946f8f5a051c
F ext/fts5/fts5_test_mi.c 4308d5658cb1f5eee5998dcbaac7d5bdf7a2ef43c8192ca6e0c843f856ccee26
F ext/fts5/test/fts5integrity.test 613efcebe16b2d7a4096f03bcfb164f79a000b3354420ceda4a6f3e035090789
F ext/fts5/test/fts5integrity2.test 4c3636615c0201232c44a8105d5cb14fd5499fd0ee3014d7ffd7e83aac76ece8
F ext/fts5/test/fts5interrupt.test af7834ac6c2e71c05aea42d92f272eef3655e89b7a14a5620a2cd9de35e2e8ea
-F ext/fts5/test/fts5join.test 48b7ed36956948c5b8456c8bcaa5b087808d99000675918a43c4f51a925f1514
+F ext/fts5/test/fts5join.test 3791e30d034050281191cd8141d969849f6c060135f1e3938fea3eea955f9da9
F ext/fts5/test/fts5lastrowid.test f36298a1fb9f988bde060a274a7ce638faa9c38a31400f8d2d27ea9373e0c4a1
F ext/fts5/test/fts5leftjoin.test 1c14b51f4d1344a89e488160882f05a2246dd7e70c5cf077c8fb473e03c66338
F ext/fts5/test/fts5limits.test 8ab67cf5d311c124b6ceb0062d0297767176df4572d955fce79fa43004dff01c
F ext/fts5/test/fts5version.test 44ab35566267b7618c090443de2d9ad84f633df5d20bf72e9bad199ae5fced84
F ext/fts5/test/fts5vocab.test 2a2bdb60d0998fa3124d541b6d30b019504918dc43a6584645b63a24be72f992
F ext/fts5/test/fts5vocab2.test 4265137a3747b27deb1e2e2bde5654120c6de72bfed3238e67806d85af60fc4c
+F ext/fts5/tool/fts5cost.tcl 188a802e69422619c526698b92f0e5935f7d00b964e155bf4d5b4d4094989f60
F ext/fts5/tool/fts5speed.tcl b0056f91a55b2d1a3684ec05729de92b042e2f85
F ext/fts5/tool/fts5txt2db.tcl c0d43c8590656f8240e622b00957b3a0facc49482411a9fdc2870b45c0c82f9f
F ext/fts5/tool/loadfts5.tcl 95b03429ee6b138645703c6ca192c3ac96eaf093
F tool/warnings.sh a554d13f6e5cf3760f041b87939e3d616ec6961859c3245e8ef701d1eafc2ca2
F tool/win/sqlite.vsix deb315d026cc8400325c5863eef847784a219a2f
F tool/winmain.c 00c8fb88e365c9017db14c73d3c78af62194d9644feaf60e220ab0f411f3604c
-P 3c64f31392328f51e205fde52f19cf70c193e90897ccb7e93c685bad4f342cac
-R 72f078867d2671a9f24c867ea87f8152
-U drh
-Z b5c58da09518d5fa628ac92460368943
+P 2bc6ce87b39c6ae324c3641c5af60e000df7d7c6d5fd2dd1a318c94cbb4aef84
+R 6c35fdaa0bdeaaa060b11671c8849a23
+U dan
+Z f5066f6b4172e70d6c3c82bea527816b
# Remove this line to create a well-formed Fossil manifest.
-2bc6ce87b39c6ae324c3641c5af60e000df7d7c6d5fd2dd1a318c94cbb4aef84
+539769b63e4044018be2993894b1962df6a6ae58636682b7fb7a2dd5aaf4075c
projects / thirdparty / sqlite.git / commitdiff
