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Merge orderby-planning with this branch.

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FossilOrigin-Name: d9549de31741239ece060e448b592ce8fc5b8042
This commit is contained in:
dan 2014-05-02 18:05:38 +00:00
commit 2ae56f50ce
43 changed files with 2398 additions and 1096 deletions

1496
ext/rtree/rtree.c

File diff suppressed because it is too large Load Diff

19
ext/rtree/rtree1.test

@ -120,12 +120,13 @@ proc execsql_intout {sql} {
# Test that it is possible to open an existing database that contains
# r-tree tables.
#
do_test rtree-1.4.1 {
execsql {
CREATE VIRTUAL TABLE t1 USING rtree(ii, x1, x2);
INSERT INTO t1 VALUES(1, 5.0, 10.0);
INSERT INTO t1 VALUES(2, 15.0, 20.0);
}
do_execsql_test rtree-1.4.1a {
CREATE VIRTUAL TABLE t1 USING rtree(ii, x1, x2);
INSERT INTO t1 VALUES(1, 5.0, 10.0);
SELECT substr(hex(data),1,40) FROM t1_node;
} {00000001000000000000000140A0000041200000}
do_execsql_test rtree-1.4.1b {
INSERT INTO t1 VALUES(2, 15.0, 20.0);
} {}
do_test rtree-1.4.2 {
db close
@ -435,16 +436,18 @@ do_test rtree-11.2 {
# Test on-conflict clause handling.
#
db_delete_and_reopen
do_execsql_test 12.0 {
do_execsql_test 12.0.1 {
CREATE VIRTUAL TABLE t1 USING rtree_i32(idx, x1, x2, y1, y2);
INSERT INTO t1 VALUES(1, 1, 2, 3, 4);
SELECT substr(hex(data),1,56) FROM t1_node;
} {00000001000000000000000100000001000000020000000300000004}
do_execsql_test 12.0.2 {
INSERT INTO t1 VALUES(2, 2, 3, 4, 5);
INSERT INTO t1 VALUES(3, 3, 4, 5, 6);
CREATE TABLE source(idx, x1, x2, y1, y2);
INSERT INTO source VALUES(5, 8, 8, 8, 8);
INSERT INTO source VALUES(2, 7, 7, 7, 7);
}
db_save_and_close
foreach {tn sql_template testdata} {

18
ext/rtree/rtree6.test

@ -57,31 +57,31 @@ do_test rtree6-1.1 {
do_test rtree6-1.2 {
rtree_strategy {SELECT * FROM t1 WHERE x1>10}
} {Ea}
} {E0}
do_test rtree6-1.3 {
rtree_strategy {SELECT * FROM t1 WHERE x1<10}
} {Ca}
} {C0}
do_test rtree6-1.4 {
rtree_strategy {SELECT * FROM t1,t2 WHERE k=ii AND x1<10}
} {Ca}
} {C0}
do_test rtree6-1.5 {
rtree_strategy {SELECT * FROM t1,t2 WHERE k=+ii AND x1<10}
} {Ca}
} {C0}
do_eqp_test rtree6.2.1 {
SELECT * FROM t1,t2 WHERE k=+ii AND x1<10
} {
0 0 0 {SCAN TABLE t1 VIRTUAL TABLE INDEX 2:Ca}
0 0 0 {SCAN TABLE t1 VIRTUAL TABLE INDEX 2:C0}
0 1 1 {SEARCH TABLE t2 USING INTEGER PRIMARY KEY (rowid=?)}
}
do_eqp_test rtree6.2.2 {
SELECT * FROM t1,t2 WHERE k=ii AND x1<10
} {
0 0 0 {SCAN TABLE t1 VIRTUAL TABLE INDEX 2:Ca}
0 0 0 {SCAN TABLE t1 VIRTUAL TABLE INDEX 2:C0}
0 1 1 {SEARCH TABLE t2 USING INTEGER PRIMARY KEY (rowid=?)}
}
@ -95,7 +95,7 @@ do_eqp_test rtree6.2.3 {
do_eqp_test rtree6.2.4 {
SELECT * FROM t1,t2 WHERE v=10 and x1<10 and x2>10
} {
0 0 0 {SCAN TABLE t1 VIRTUAL TABLE INDEX 2:CaEb}
0 0 0 {SCAN TABLE t1 VIRTUAL TABLE INDEX 2:C0E1}
0 1 1 {SEARCH TABLE t2 USING AUTOMATIC COVERING INDEX (v=?)}
}
@ -126,7 +126,7 @@ do_test rtree6.3.2 {
x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND
x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5
}
} {EaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEa}
} {E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0}
do_test rtree6.3.3 {
rtree_strategy {
SELECT * FROM t3 WHERE
@ -137,7 +137,7 @@ do_test rtree6.3.3 {
x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND
x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5 AND x1>0.5
}
} {EaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEaEa}
} {E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0E0}
do_execsql_test rtree6-3.4 {
SELECT * FROM t3 WHERE x1>0.5 AND x1>0.8 AND x1>1.1

2
ext/rtree/rtreeB.test

@ -41,7 +41,7 @@ ifcapable rtree_int_only {
INSERT INTO t1 VALUES(9223372036854775807, 150, 150, 400, 400);
SELECT rtreenode(2, data) FROM t1_node;
}
} {{{1073741824 0.000000 0.000000 100.000000 100.000000} {2147483646 0.000000 0.000000 200.000000 200.000000} {4294967296 0.000000 0.000000 300.000000 300.000000} {8589934592 20.000000 20.000000 150.000000 150.000000} {9223372036854775807 150.000000 150.000000 400.000000 400.000000}}}
} {{{1073741824 0 0 100 100} {2147483646 0 0 200 200} {4294967296 0 0 300 300} {8589934592 20 20 150 150} {9223372036854775807 150 150 400 400}}}
}
finish_test

13
ext/rtree/rtreeC.test

@ -29,7 +29,7 @@ do_eqp_test 1.1 {
WHERE t.x>=min_x AND t.x<=max_x AND t.y>=min_y AND t.x<=max_y
} {
0 0 1 {SCAN TABLE t}
0 1 0 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:DdBcDbBa}
0 1 0 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:D3B2D1B0}
}
do_eqp_test 1.2 {
@ -37,7 +37,7 @@ do_eqp_test 1.2 {
WHERE t.x>=min_x AND t.x<=max_x AND t.y>=min_y AND t.x<=max_y
} {
0 0 0 {SCAN TABLE t}
0 1 1 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:DdBcDbBa}
0 1 1 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:D3B2D1B0}
}
do_eqp_test 1.3 {
@ -45,7 +45,7 @@ do_eqp_test 1.3 {
WHERE t.x>=min_x AND t.x<=max_x AND t.y>=min_y AND ?<=max_y
} {
0 0 0 {SCAN TABLE t}
0 1 1 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:DdBcDbBa}
0 1 1 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:D3B2D1B0}
}
do_eqp_test 1.5 {
@ -82,7 +82,7 @@ do_eqp_test 2.1 {
WHERE t.x>=min_x AND t.x<=max_x AND t.y>=min_y AND t.x<=max_y
} {
0 0 1 {SCAN TABLE t}
0 1 0 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:DdBcDbBa}
0 1 0 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:D3B2D1B0}
}
do_eqp_test 2.2 {
@ -90,7 +90,7 @@ do_eqp_test 2.2 {
WHERE t.x>=min_x AND t.x<=max_x AND t.y>=min_y AND t.x<=max_y
} {
0 0 0 {SCAN TABLE t}
0 1 1 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:DdBcDbBa}
0 1 1 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:D3B2D1B0}
}
do_eqp_test 2.3 {
@ -98,7 +98,7 @@ do_eqp_test 2.3 {
WHERE t.x>=min_x AND t.x<=max_x AND t.y>=min_y AND ?<=max_y
} {
0 0 0 {SCAN TABLE t}
0 1 1 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:DdBcDbBa}
0 1 1 {SCAN TABLE r_tree VIRTUAL TABLE INDEX 2:D3B2D1B0}
}
do_eqp_test 2.5 {
@ -271,4 +271,3 @@ ifcapable rtree {
finish_test

129
ext/rtree/rtreeE.test Normal file

@ -0,0 +1,129 @@
# 2010 August 28
#
# 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 contains tests for the r-tree module. Specifically, it tests
# that new-style custom r-tree queries (geometry callbacks) work.
#
if {![info exists testdir]} {
set testdir [file join [file dirname [info script]] .. .. test]
}
source $testdir/tester.tcl
ifcapable !rtree { finish_test ; return }
ifcapable rtree_int_only { finish_test; return }
#-------------------------------------------------------------------------
# Test the example 2d "circle" geometry callback.
#
register_circle_geom db
do_execsql_test rtreeE-1.1 {
PRAGMA page_size=512;
CREATE VIRTUAL TABLE rt1 USING rtree(id,x0,x1,y0,y1);
/* A tight pattern of small boxes near 0,0 */
WITH RECURSIVE
x(x) AS (VALUES(0) UNION ALL SELECT x+1 FROM x WHERE x<4),
y(y) AS (VALUES(0) UNION ALL SELECT y+1 FROM y WHERE y<4)
INSERT INTO rt1 SELECT x+5*y, x, x+2, y, y+2 FROM x, y;
/* A looser pattern of small boxes near 100, 0 */
WITH RECURSIVE
x(x) AS (VALUES(0) UNION ALL SELECT x+1 FROM x WHERE x<4),
y(y) AS (VALUES(0) UNION ALL SELECT y+1 FROM y WHERE y<4)
INSERT INTO rt1 SELECT 100+x+5*y, x*3+100, x*3+102, y*3, y*3+2 FROM x, y;
/* A looser pattern of larger boxes near 0, 200 */
WITH RECURSIVE
x(x) AS (VALUES(0) UNION ALL SELECT x+1 FROM x WHERE x<4),
y(y) AS (VALUES(0) UNION ALL SELECT y+1 FROM y WHERE y<4)
INSERT INTO rt1 SELECT 200+x+5*y, x*7, x*7+15, y*7+200, y*7+215 FROM x, y;
} {}
# Queries against each of the three clusters */
do_execsql_test rtreeE-1.1 {
SELECT id FROM rt1 WHERE id MATCH Qcircle(0.0, 0.0, 50.0, 3) ORDER BY id;
} {0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24}
do_execsql_test rtreeE-1.2 {
SELECT id FROM rt1 WHERE id MATCH Qcircle(100.0, 0.0, 50.0, 3) ORDER BY id;
} {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}
do_execsql_test rtreeE-1.3 {
SELECT id FROM rt1 WHERE id MATCH Qcircle(0.0, 200.0, 50.0, 3) ORDER BY id;
} {200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224}
# The Qcircle geometry function gives a lower score to larger leaf-nodes.
# This causes the 200s to sort before the 100s and the 0s to sort before
# last.
#
do_execsql_test rtreeE-1.4 {
SELECT id FROM rt1 WHERE id MATCH Qcircle(0,0,1000,3) AND id%100==0
} {200 100 0}
# Exclude odd rowids on a depth-first search
do_execsql_test rtreeE-1.5 {
SELECT id FROM rt1 WHERE id MATCH Qcircle(0,0,1000,4) ORDER BY +id
} {0 2 4 6 8 10 12 14 16 18 20 22 24 100 102 104 106 108 110 112 114 116 118 120 122 124 200 202 204 206 208 210 212 214 216 218 220 222 224}
# Exclude odd rowids on a breadth-first search.
do_execsql_test rtreeE-1.6 {
SELECT id FROM rt1 WHERE id MATCH Qcircle(0,0,1000,5) ORDER BY +id
} {0 2 4 6 8 10 12 14 16 18 20 22 24 100 102 104 106 108 110 112 114 116 118 120 122 124 200 202 204 206 208 210 212 214 216 218 220 222 224}
# Construct a large 2-D RTree with thousands of random entries.
#
do_test rtreeE-2.1 {
db eval {
CREATE TABLE t2(id,x0,x1,y0,y1);
CREATE VIRTUAL TABLE rt2 USING rtree(id,x0,x1,y0,y1);
BEGIN;
}
expr srand(0)
for {set i 1} {$i<=10000} {incr i} {
set dx [expr {int(rand()*40)+1}]
set dy [expr {int(rand()*40)+1}]
set x0 [expr {int(rand()*(10000 - $dx))}]
set x1 [expr {$x0+$dx}]
set y0 [expr {int(rand()*(10000 - $dy))}]
set y1 [expr {$y0+$dy}]
set id [expr {$i+10000}]
db eval {INSERT INTO t2 VALUES($id,$x0,$x1,$y0,$y1)}
}
db eval {
INSERT INTO rt2 SELECT * FROM t2;
COMMIT;
}
} {}
for {set i 1} {$i<=200} {incr i} {
set dx [expr {int(rand()*100)}]
set dy [expr {int(rand()*100)}]
set x0 [expr {int(rand()*(10000 - $dx))}]
set x1 [expr {$x0+$dx}]
set y0 [expr {int(rand()*(10000 - $dy))}]
set y1 [expr {$y0+$dy}]
set ans [db eval {SELECT id FROM t2 WHERE x1>=$x0 AND x0<=$x1 AND y1>=$y0 AND y0<=$y1 ORDER BY id}]
do_execsql_test rtreeE-2.2.$i {
SELECT id FROM rt2 WHERE id MATCH breadthfirstsearch($x0,$x1,$y0,$y1) ORDER BY id
} $ans
}
# Run query that have very deep priority queues
#
set ans [db eval {SELECT id FROM t2 WHERE x1>=0 AND x0<=5000 AND y1>=0 AND y0<=5000 ORDER BY id}]
do_execsql_test rtreeE-2.3 {
SELECT id FROM rt2 WHERE id MATCH breadthfirstsearch(0,5000,0,5000) ORDER BY id
} $ans
set ans [db eval {SELECT id FROM t2 WHERE x1>=0 AND x0<=10000 AND y1>=0 AND y0<=10000 ORDER BY id}]
do_execsql_test rtreeE-2.4 {
SELECT id FROM rt2 WHERE id MATCH breadthfirstsearch(0,10000,0,10000) ORDER BY id
} $ans
finish_test

67
ext/rtree/sqlite3rtree.h

@ -21,6 +21,16 @@ extern "C" {
#endif
typedef struct sqlite3_rtree_geometry sqlite3_rtree_geometry;
typedef struct sqlite3_rtree_query_info sqlite3_rtree_query_info;
/* The double-precision datatype used by RTree depends on the
** SQLITE_RTREE_INT_ONLY compile-time option.
*/
#ifdef SQLITE_RTREE_INT_ONLY
typedef sqlite3_int64 sqlite3_rtree_dbl;
#else
typedef double sqlite3_rtree_dbl;
#endif
/*
** Register a geometry callback named zGeom that can be used as part of an
@ -31,11 +41,7 @@ typedef struct sqlite3_rtree_geometry sqlite3_rtree_geometry;
int sqlite3_rtree_geometry_callback(
sqlite3 *db,
const char *zGeom,
#ifdef SQLITE_RTREE_INT_ONLY
int (*xGeom)(sqlite3_rtree_geometry*, int n, sqlite3_int64 *a, int *pRes),
#else
int (*xGeom)(sqlite3_rtree_geometry*, int n, double *a, int *pRes),
#endif
int (*xGeom)(sqlite3_rtree_geometry*, int, sqlite3_rtree_dbl*,int*),
void *pContext
);
@ -47,11 +53,60 @@ int sqlite3_rtree_geometry_callback(
struct sqlite3_rtree_geometry {
void *pContext; /* Copy of pContext passed to s_r_g_c() */
int nParam; /* Size of array aParam[] */
double *aParam; /* Parameters passed to SQL geom function */
sqlite3_rtree_dbl *aParam; /* Parameters passed to SQL geom function */
void *pUser; /* Callback implementation user data */
void (*xDelUser)(void *); /* Called by SQLite to clean up pUser */
};
/*
** Register a 2nd-generation geometry callback named zScore that can be
** used as part of an R-Tree geometry query as follows:
**
** SELECT ... FROM <rtree> WHERE <rtree col> MATCH $zQueryFunc(... params ...)
*/
int sqlite3_rtree_query_callback(
sqlite3 *db,
const char *zQueryFunc,
int (*xQueryFunc)(sqlite3_rtree_query_info*),
void *pContext,
void (*xDestructor)(void*)
);
/*
** A pointer to a structure of the following type is passed as the
** argument to scored geometry callback registered using
** sqlite3_rtree_query_callback().
**
** Note that the first 5 fields of this structure are identical to
** sqlite3_rtree_geometry. This structure is a subclass of
** sqlite3_rtree_geometry.
*/
struct sqlite3_rtree_query_info {
void *pContext; /* pContext from when function registered */
int nParam; /* Number of function parameters */
sqlite3_rtree_dbl *aParam; /* value of function parameters */
void *pUser; /* callback can use this, if desired */
void (*xDelUser)(void*); /* function to free pUser */
sqlite3_rtree_dbl *aCoord; /* Coordinates of node or entry to check */
unsigned int *anQueue; /* Number of pending entries in the queue */
int nCoord; /* Number of coordinates */
int iLevel; /* Level of current node or entry */
int mxLevel; /* The largest iLevel value in the tree */
sqlite3_int64 iRowid; /* Rowid for current entry */
sqlite3_rtree_dbl rParentScore; /* Score of parent node */
int eParentWithin; /* Visibility of parent node */
int eWithin; /* OUT: Visiblity */
sqlite3_rtree_dbl rScore; /* OUT: Write the score here */
};
/*
** Allowed values for sqlite3_rtree_query.eWithin and .eParentWithin.
*/
#define NOT_WITHIN 0 /* Object completely outside of query region */
#define PARTLY_WITHIN 1 /* Object partially overlaps query region */
#define FULLY_WITHIN 2 /* Object fully contained within query region */
#ifdef __cplusplus
} /* end of the 'extern "C"' block */

2
main.mk

@ -477,7 +477,7 @@ parse.c: $(TOP)/src/parse.y lemon $(TOP)/addopcodes.awk
mv parse.h parse.h.temp
$(NAWK) -f $(TOP)/addopcodes.awk parse.h.temp >parse.h
sqlite3.h: $(TOP)/src/sqlite.h.in $(TOP)/manifest.uuid $(TOP)/VERSION
sqlite3.h: $(TOP)/src/sqlite.h.in $(TOP)/manifest.uuid $(TOP)/VERSION $(TOP)/ext/rtree/sqlite3rtree.h
tclsh $(TOP)/tool/mksqlite3h.tcl $(TOP) >sqlite3.h
keywordhash.h: $(TOP)/tool/mkkeywordhash.c

87
manifest

@ -1,5 +1,5 @@
C Fix\ssome\sbroken\sasserts\sin\sbtree.c\sand\svdbeaux.c\sthat\smay\sfail\sfollowing\san\sOOM\serror.
D 2014-05-02T17:12:41.912
C Merge\sorderby-planning\swith\sthis\sbranch.
D 2014-05-02T18:05:38.568
F Makefile.arm-wince-mingw32ce-gcc d6df77f1f48d690bd73162294bbba7f59507c72f
F Makefile.in ad0921c4b2780d01868cf69b419a4f102308d125
F Makefile.linux-gcc 91d710bdc4998cb015f39edf3cb314ec4f4d7e23
@ -120,30 +120,31 @@ F ext/misc/vfslog.c fe40fab5c077a40477f7e5eba994309ecac6cc95
F ext/misc/vtshim.c babb0dc2bf116029e3e7c9a618b8a1377045303e
F ext/misc/wholenumber.c 784b12543d60702ebdd47da936e278aa03076212
F ext/rtree/README 6315c0d73ebf0ec40dedb5aa0e942bc8b54e3761
F ext/rtree/rtree.c 2d9f95da404d850474e628c720c5ce15d29b47de
F ext/rtree/rtree.c 6f70db93e0e42c369325c5cddcf2024c5a87ca43
F ext/rtree/rtree.h 834dbcb82dc85b2481cde6a07cdadfddc99e9b9e
F ext/rtree/rtree1.test cf679265ecafff494a768ac9c2f43a70915a6290
F ext/rtree/rtree1.test e2da4aaa426918d27122d1a1066c6ecf8409a514
F ext/rtree/rtree2.test acbb3a4ce0f4fbc2c304d2b4b784cfa161856bba
F ext/rtree/rtree3.test a494da55c30ee0bc9b01a91c80c81b387b22d2dc
F ext/rtree/rtree4.test c8fe384f60ebd49540a5fecc990041bf452eb6e0
F ext/rtree/rtree5.test 6a510494f12454bf57ef28f45bc7764ea279431e
F ext/rtree/rtree6.test fe0bd377a21c68ce2826129d14354c884cb1f354
F ext/rtree/rtree6.test 756585abc51727fec97c77852476445c10c0ee95
F ext/rtree/rtree7.test 1fa710b9e6bf997a0c1a537b81be7bb6fded1971
F ext/rtree/rtree8.test db79c812f9e4a11f9b1f3f9934007884610a713a
F ext/rtree/rtree9.test d86ebf08ff6328895613ed577dd8a2a37c472c34
F ext/rtree/rtreeA.test ace05e729a36e342d40cf94e9efc7b4723d9dcdf
F ext/rtree/rtreeB.test 983e567b49b5dca165940f66b87e161aa30e82b2
F ext/rtree/rtreeC.test 16d7aa86ecb6a876d2a38cf590a1471a41b3a46d
F ext/rtree/rtreeB.test c85f9ce78766c4e68b8b89fbf2979ee9cfa82b4e
F ext/rtree/rtreeC.test df158dcc81f1a43ce7eef361af03c48ec91f1e06
F ext/rtree/rtreeD.test 636630357638f5983701550b37f0f5867130d2ca
F ext/rtree/rtreeE.test 388c1c8602c3ce55c15f03b509e9cf545fb7c41f
F ext/rtree/rtree_perf.tcl 6c18c1f23cd48e0f948930c98dfdd37dfccb5195
F ext/rtree/rtree_util.tcl 06aab2ed5b826545bf215fff90ecb9255a8647ea
F ext/rtree/sqlite3rtree.h c34c1e41d1ab80bb8ad09aae402c9c956871a765
F ext/rtree/sqlite3rtree.h 83349d519fe5f518b3ea025d18dd1fe51b1684bd
F ext/rtree/tkt3363.test 142ab96eded44a3615ec79fba98c7bde7d0f96de
F ext/rtree/viewrtree.tcl eea6224b3553599ae665b239bd827e182b466024
F install-sh 9d4de14ab9fb0facae2f48780b874848cbf2f895 x
F ltmain.sh 3ff0879076df340d2e23ae905484d8c15d5fdea8
F magic.txt f439556c5ce01ced70987e5ee86549a45165d9ff
F main.mk 4b30dd2a6cb441db688972496b45a6c3abef8b20
F main.mk 97673939d94f210b7218a8236df6c8799d4a0da6
F mkopcodec.awk c2ff431854d702cdd2d779c9c0d1f58fa16fa4ea
F mkopcodeh.awk c6b3fa301db6ef7ac916b14c60868aeaec1337b5
F mkso.sh fd21c06b063bb16a5d25deea1752c2da6ac3ed83
@ -158,7 +159,7 @@ F sqlite.pc.in 42b7bf0d02e08b9e77734a47798d1a55a9e0716b
F sqlite3.1 3d8b83c91651f53472ca17599dae3457b8b89494
F sqlite3.pc.in 48fed132e7cb71ab676105d2a4dc77127d8c1f3a
F src/alter.c b00900877f766f116f9e16116f1ccacdc21d82f1
F src/analyze.c 663e0b291d27eb03c9fd6b421e2d61ba348a2389
F src/analyze.c 3596f863bb80126fe56ba217df5932749271efc8
F src/attach.c 3801129015ef59d76bf23c95ef9b0069d18a0c52
F src/auth.c 523da7fb4979469955d822ff9298352d6b31de34
F src/backup.c a729e63cf5cd1829507cb7b8e89f99b95141bb53
@ -167,7 +168,7 @@ F src/btmutex.c 976f45a12e37293e32cae0281b15a21d48a8aaa7
F src/btree.c e14daeed62b5b1499835a6523f9a47d660c297c8
F src/btree.h d79306df4ed9181b48916737fe8871a4392c4594
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F src/ctime.c 0231df905e2c4abba4483ee18ffc05adc321df2a
@ -181,7 +182,7 @@ F src/global.c deadd872189b92aca4ee2566332a86315839f811
F src/hash.c d139319967164f139c8d1bb8a11b14db9c4ba3cd
F src/hash.h 8890a25af81fb85a9ad7790d32eedab4b994da22
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@ -211,18 +212,18 @@ F src/parse.y 22d6a074e5f5a7258947a1dc55a9bf946b765dd0
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@ -260,7 +261,7 @@ F src/test_osinst.c 90a845c8183013d80eccb1f29e8805608516edba
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@ -270,20 +271,20 @@ F src/test_syscall.c 2e21ca7f7dc54a028f1967b63f1e76155c356f9b
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F test/whereH.test e4b07f7a3c2f5d31195cd33710054c78667573b2
F test/wherelimit.test 5e9fd41e79bb2b2d588ed999d641d9c965619b31
F test/wild001.test bca33f499866f04c24510d74baf1e578d4e44b1c
@ -1127,7 +1132,7 @@ F tool/genfkey.test 4196a8928b78f51d54ef58e99e99401ab2f0a7e5
F tool/getlock.c f4c39b651370156cae979501a7b156bdba50e7ce
F tool/lemon.c 07aba6270d5a5016ba8107b09e431eea4ecdc123
F tool/lempar.c 01ca97f87610d1dac6d8cd96ab109ab1130e76dc
F tool/logest.c 388c318c7ac8b52b7c08ca1e2de0f4ca9a8f7e81
F tool/logest.c eef612f8adf4d0993dafed0416064cf50d5d33c6
F tool/mkautoconfamal.sh f8d8dbf7d62f409ebed5134998bf5b51d7266383
F tool/mkkeywordhash.c c9e05e4a7bcab8fab9f583d5b321fb72f565ad97
F tool/mkopts.tcl 66ac10d240cc6e86abd37dc908d50382f84ff46e
@ -1165,7 +1170,7 @@ F tool/vdbe_profile.tcl 67746953071a9f8f2f668b73fe899074e2c6d8c1
F tool/warnings-clang.sh f6aa929dc20ef1f856af04a730772f59283631d4
F tool/warnings.sh d1a6de74685f360ab718efda6265994b99bbea01
F tool/win/sqlite.vsix 030f3eeaf2cb811a3692ab9c14d021a75ce41fff
P d95d68aa1d14b750888d50068380cc107f9070df
R 2642a9b7016b11d8b125fe44a5d1acd4
P e15f47064bef431c0afd8bf93eb4e160c23ad562 3300d62dcbe74842cf86ca436959fe4e77a89f84
R 6fa5ff1df255fa8dfad56d587950c625
U dan
Z 60595d854f9f1dca901aef6c64df6a77
Z 63362d13bfcb7640057f1ca0f3721e45

2
manifest.uuid

@ -1 +1 @@
e15f47064bef431c0afd8bf93eb4e160c23ad562
d9549de31741239ece060e448b592ce8fc5b8042

25
src/analyze.c

@ -1371,6 +1371,7 @@ static void decodeIntArray(
char *zIntArray, /* String containing int array to decode */
int nOut, /* Number of slots in aOut[] */
tRowcnt *aOut, /* Store integers here */
LogEst *aLog, /* Or, if aOut==0, here */
Index *pIndex /* Handle extra flags for this index, if not NULL */
){
char *z = zIntArray;
@ -1389,7 +1390,17 @@ static void decodeIntArray(
v = v*10 + c - '0';
z++;
}
aOut[i] = v;
#ifdef SQLITE_ENABLE_STAT3_OR_STAT4
if( aOut ){
aOut[i] = v;
}else
#else
assert( aOut==0 );
UNUSED_PARAMETER(aOut);
#endif
{
aLog[i] = sqlite3LogEst(v);
}
if( *z==' ' ) z++;
}
#ifndef SQLITE_ENABLE_STAT3_OR_STAT4
@ -1445,12 +1456,12 @@ static int analysisLoader(void *pData, int argc, char **argv, char **NotUsed){
z = argv[2];
if( pIndex ){
decodeIntArray((char*)z, pIndex->nKeyCol+1, pIndex->aiRowEst, pIndex);
if( pIndex->pPartIdxWhere==0 ) pTable->nRowEst = pIndex->aiRowEst[0];
decodeIntArray((char*)z, pIndex->nKeyCol+1, 0, pIndex->aiRowLogEst, pIndex);
if( pIndex->pPartIdxWhere==0 ) pTable->nRowLogEst = pIndex->aiRowLogEst[0];
}else{
Index fakeIdx;
fakeIdx.szIdxRow = pTable->szTabRow;
decodeIntArray((char*)z, 1, &pTable->nRowEst, &fakeIdx);
decodeIntArray((char*)z, 1, 0, &pTable->nRowLogEst, &fakeIdx);
pTable->szTabRow = fakeIdx.szIdxRow;
}
@ -1642,9 +1653,9 @@ static int loadStatTbl(
pPrevIdx = pIdx;
}
pSample = &pIdx->aSample[pIdx->nSample];
decodeIntArray((char*)sqlite3_column_text(pStmt,1), nCol, pSample->anEq, 0);
decodeIntArray((char*)sqlite3_column_text(pStmt,2), nCol, pSample->anLt, 0);
decodeIntArray((char*)sqlite3_column_text(pStmt,3), nCol, pSample->anDLt,0);
decodeIntArray((char*)sqlite3_column_text(pStmt,1),nCol,pSample->anEq,0,0);
decodeIntArray((char*)sqlite3_column_text(pStmt,2),nCol,pSample->anLt,0,0);
decodeIntArray((char*)sqlite3_column_text(pStmt,3),nCol,pSample->anDLt,0,0);
/* Take a copy of the sample. Add two 0x00 bytes the end of the buffer.
** This is in case the sample record is corrupted. In that case, the

45
src/build.c

@ -905,7 +905,7 @@ void sqlite3StartTable(
pTable->iPKey = -1;
pTable->pSchema = db->aDb[iDb].pSchema;
pTable->nRef = 1;
pTable->nRowEst = 1048576;
pTable->nRowLogEst = 200; assert( 200==sqlite3LogEst(1048576) );
assert( pParse->pNewTable==0 );
pParse->pNewTable = pTable;
@ -2730,15 +2730,15 @@ Index *sqlite3AllocateIndexObject(
nByte = ROUND8(sizeof(Index)) + /* Index structure */
ROUND8(sizeof(char*)*nCol) + /* Index.azColl */
ROUND8(sizeof(tRowcnt)*(nCol+1) + /* Index.aiRowEst */
ROUND8(sizeof(LogEst)*(nCol+1) + /* Index.aiRowLogEst */
sizeof(i16)*nCol + /* Index.aiColumn */
sizeof(u8)*nCol); /* Index.aSortOrder */
p = sqlite3DbMallocZero(db, nByte + nExtra);
if( p ){
char *pExtra = ((char*)p)+ROUND8(sizeof(Index));
p->azColl = (char**)pExtra; pExtra += ROUND8(sizeof(char*)*nCol);
p->aiRowEst = (tRowcnt*)pExtra; pExtra += sizeof(tRowcnt)*(nCol+1);
p->aiColumn = (i16*)pExtra; pExtra += sizeof(i16)*nCol;
p->azColl = (char**)pExtra; pExtra += ROUND8(sizeof(char*)*nCol);
p->aiRowLogEst = (LogEst*)pExtra; pExtra += sizeof(LogEst)*(nCol+1);
p->aiColumn = (i16*)pExtra; pExtra += sizeof(i16)*nCol;
p->aSortOrder = (u8*)pExtra;
p->nColumn = nCol;
p->nKeyCol = nCol - 1;
@ -2968,7 +2968,7 @@ Index *sqlite3CreateIndex(
if( db->mallocFailed ){
goto exit_create_index;
}
assert( EIGHT_BYTE_ALIGNMENT(pIndex->aiRowEst) );
assert( EIGHT_BYTE_ALIGNMENT(pIndex->aiRowLogEst) );
assert( EIGHT_BYTE_ALIGNMENT(pIndex->azColl) );
pIndex->zName = zExtra;
zExtra += nName + 1;
@ -3249,7 +3249,7 @@ exit_create_index:
** Since we do not know, guess 1 million. aiRowEst[1] is an estimate of the
** number of rows in the table that match any particular value of the
** first column of the index. aiRowEst[2] is an estimate of the number
** of rows that match any particular combiniation of the first 2 columns
** of rows that match any particular combination of the first 2 columns
** of the index. And so forth. It must always be the case that
*
** aiRowEst[N]<=aiRowEst[N-1]
@ -3260,20 +3260,27 @@ exit_create_index:
** are based on typical values found in actual indices.
*/
void sqlite3DefaultRowEst(Index *pIdx){
tRowcnt *a = pIdx->aiRowEst;
/* 10, 9, 8, 7, 6 */
LogEst aVal[] = { 33, 32, 30, 28, 26 };
LogEst *a = pIdx->aiRowLogEst;
int nCopy = MIN(ArraySize(aVal), pIdx->nKeyCol);
int i;
tRowcnt n;
assert( a!=0 );
a[0] = pIdx->pTable->nRowEst;
if( a[0]<10 ) a[0] = 10;
n = 10;
for(i=1; i<=pIdx->nKeyCol; i++){
a[i] = n;
if( n>5 ) n--;
}
if( pIdx->onError!=OE_None ){
a[pIdx->nKeyCol] = 1;
/* Set the first entry (number of rows in the index) to the estimated
** number of rows in the table. Or 10, if the estimated number of rows
** in the table is less than that. */
a[0] = pIdx->pTable->nRowLogEst;
if( a[0]<33 ) a[0] = 33; assert( 33==sqlite3LogEst(10) );
/* Estimate that a[1] is 10, a[2] is 9, a[3] is 8, a[4] is 7, a[5] is
** 6 and each subsequent value (if any) is 5. */
memcpy(&a[1], aVal, nCopy*sizeof(LogEst));
for(i=nCopy+1; i<=pIdx->nKeyCol; i++){
a[i] = 23; assert( 23==sqlite3LogEst(5) );
}
assert( 0==sqlite3LogEst(1) );
if( pIdx->onError!=OE_None ) a[pIdx->nKeyCol] = 0;
}
/*

15
src/insert.c

@ -1865,15 +1865,24 @@ static int xferOptimization(
return 0; /* Both tables must have the same INTEGER PRIMARY KEY */
}
for(i=0; i<pDest->nCol; i++){
if( pDest->aCol[i].affinity!=pSrc->aCol[i].affinity ){
Column *pDestCol = &pDest->aCol[i];
Column *pSrcCol = &pSrc->aCol[i];
if( pDestCol->affinity!=pSrcCol->affinity ){
return 0; /* Affinity must be the same on all columns */
}
if( !xferCompatibleCollation(pDest->aCol[i].zColl, pSrc->aCol[i].zColl) ){
if( !xferCompatibleCollation(pDestCol->zColl, pSrcCol->zColl) ){
return 0; /* Collating sequence must be the same on all columns */
}
if( pDest->aCol[i].notNull && !pSrc->aCol[i].notNull ){
if( pDestCol->notNull && !pSrcCol->notNull ){
return 0; /* tab2 must be NOT NULL if tab1 is */
}
/* Default values for second and subsequent columns need to match. */
if( i>0
&& ((pDestCol->zDflt==0)!=(pSrcCol->zDflt==0)
|| (pDestCol->zDflt && strcmp(pDestCol->zDflt, pSrcCol->zDflt)!=0))
){
return 0; /* Default values must be the same for all columns */
}
}
for(pDestIdx=pDest->pIndex; pDestIdx; pDestIdx=pDestIdx->pNext){
if( pDestIdx->onError!=OE_None ){

6
src/pragma.c

@ -1488,13 +1488,15 @@ void sqlite3Pragma(
sqlite3VdbeAddOp2(v, OP_Null, 0, 2);
sqlite3VdbeAddOp2(v, OP_Integer,
(int)sqlite3LogEstToInt(pTab->szTabRow), 3);
sqlite3VdbeAddOp2(v, OP_Integer, (int)pTab->nRowEst, 4);
sqlite3VdbeAddOp2(v, OP_Integer,
(int)sqlite3LogEstToInt(pTab->nRowLogEst), 4);
sqlite3VdbeAddOp2(v, OP_ResultRow, 1, 4);
for(pIdx=pTab->pIndex; pIdx; pIdx=pIdx->pNext){
sqlite3VdbeAddOp4(v, OP_String8, 0, 2, 0, pIdx->zName, 0);
sqlite3VdbeAddOp2(v, OP_Integer,
(int)sqlite3LogEstToInt(pIdx->szIdxRow), 3);
sqlite3VdbeAddOp2(v, OP_Integer, (int)pIdx->aiRowEst[0], 4);
sqlite3VdbeAddOp2(v, OP_Integer,
(int)sqlite3LogEstToInt(pIdx->aiRowLogEst[0]), 4);
sqlite3VdbeAddOp2(v, OP_ResultRow, 1, 4);
}
}

23
src/select.c

@ -471,7 +471,7 @@ static void pushOntoSorter(
int nExpr = pSort->pOrderBy->nExpr; /* No. of ORDER BY terms */
int nBase = nExpr + bSeq + nData; /* Fields in sorter record */
int regBase; /* Regs for sorter record */
int regRecord = sqlite3GetTempReg(pParse); /* Assembled sorter record */
int regRecord = ++pParse->nMem; /* Assembled sorter record */
int nOBSat = pSort->nOBSat; /* ORDER BY terms to skip */
int op; /* Opcode to add sorter record to sorter */
@ -480,7 +480,8 @@ static void pushOntoSorter(
assert( nPrefixReg==nExpr+bSeq );
regBase = regData - nExpr - bSeq;
}else{
regBase = sqlite3GetTempRange(pParse, nBase);
regBase = pParse->nMem + 1;
pParse->nMem += nBase;
}
sqlite3ExprCodeExprList(pParse, pSort->pOrderBy, regBase, SQLITE_ECEL_DUP);
if( bSeq ){
@ -511,7 +512,7 @@ static void pushOntoSorter(
sqlite3VdbeAddOp3(v, OP_Compare, regPrevKey, regBase, pSort->nOBSat);
pOp = sqlite3VdbeGetOp(v, pSort->addrSortIndex);
if( pParse->db->mallocFailed ) return;
pOp->p2 = nKey + 1;
pOp->p2 = nKey + nData;
pKI = pOp->p4.pKeyInfo;
memset(pKI->aSortOrder, 0, pKI->nField); /* Makes OP_Jump below testable */
sqlite3VdbeChangeP4(v, -1, (char*)pKI, P4_KEYINFO);
@ -532,12 +533,6 @@ static void pushOntoSorter(
op = OP_IdxInsert;
}
sqlite3VdbeAddOp2(v, op, pSort->iECursor, regRecord);
if( nOBSat==0 ){
sqlite3ReleaseTempReg(pParse, regRecord);
if( nPrefixReg==0 ){
sqlite3ReleaseTempRange(pParse, regBase, nBase);
}
}
if( pSelect->iLimit ){
int addr1, addr2;
int iLimit;
@ -1722,7 +1717,7 @@ Table *sqlite3ResultSetOfSelect(Parse *pParse, Select *pSelect){
assert( db->lookaside.bEnabled==0 );
pTab->nRef = 1;
pTab->zName = 0;
pTab->nRowEst = 1048576;
pTab->nRowLogEst = 200; assert( 200==sqlite3LogEst(1048576) );
selectColumnsFromExprList(pParse, pSelect->pEList, &pTab->nCol, &pTab->aCol);
selectAddColumnTypeAndCollation(pParse, pTab, pSelect);
pTab->iPKey = -1;
@ -3861,7 +3856,7 @@ static int withExpand(
pTab->nRef = 1;
pTab->zName = sqlite3DbStrDup(db, pCte->zName);
pTab->iPKey = -1;
pTab->nRowEst = 1048576;
pTab->nRowLogEst = 200; assert( 200==sqlite3LogEst(1048576) );
pTab->tabFlags |= TF_Ephemeral;
pFrom->pSelect = sqlite3SelectDup(db, pCte->pSelect, 0);
if( db->mallocFailed ) return SQLITE_NOMEM;
@ -4037,7 +4032,7 @@ static int selectExpander(Walker *pWalker, Select *p){
while( pSel->pPrior ){ pSel = pSel->pPrior; }
selectColumnsFromExprList(pParse, pSel->pEList, &pTab->nCol, &pTab->aCol);
pTab->iPKey = -1;
pTab->nRowEst = 1048576;
pTab->nRowLogEst = 200; assert( 200==sqlite3LogEst(1048576) );
pTab->tabFlags |= TF_Ephemeral;
#endif
}else{
@ -4687,7 +4682,7 @@ int sqlite3Select(
sqlite3SelectDestInit(&dest, SRT_Coroutine, pItem->regReturn);
explainSetInteger(pItem->iSelectId, (u8)pParse->iNextSelectId);
sqlite3Select(pParse, pSub, &dest);
pItem->pTab->nRowEst = (unsigned)pSub->nSelectRow;
pItem->pTab->nRowLogEst = sqlite3LogEst(pSub->nSelectRow);
pItem->viaCoroutine = 1;
pItem->regResult = dest.iSdst;
sqlite3VdbeAddOp1(v, OP_EndCoroutine, pItem->regReturn);
@ -4718,7 +4713,7 @@ int sqlite3Select(
sqlite3SelectDestInit(&dest, SRT_EphemTab, pItem->iCursor);
explainSetInteger(pItem->iSelectId, (u8)pParse->iNextSelectId);
sqlite3Select(pParse, pSub, &dest);
pItem->pTab->nRowEst = (unsigned)pSub->nSelectRow;
pItem->pTab->nRowLogEst = sqlite3LogEst(pSub->nSelectRow);
if( onceAddr ) sqlite3VdbeJumpHere(v, onceAddr);
retAddr = sqlite3VdbeAddOp1(v, OP_Return, pItem->regReturn);
VdbeComment((v, "end %s", pItem->pTab->zName));

8
src/sqliteInt.h

@ -538,10 +538,10 @@ typedef INT8_TYPE i8; /* 1-byte signed integer */
** gives a possible range of values of approximately 1.0e986 to 1e-986.
** But the allowed values are "grainy". Not every value is representable.
** For example, quantities 16 and 17 are both represented by a LogEst
** of 40. However, since LogEst quantatites are suppose to be estimates,
** of 40. However, since LogEst quantaties are suppose to be estimates,
** not exact values, this imprecision is not a problem.
**
** "LogEst" is short for "Logarithimic Estimate".
** "LogEst" is short for "Logarithmic Estimate".
**
** Examples:
** 1 -> 0 20 -> 43 10000 -> 132
@ -1486,7 +1486,7 @@ struct Table {
#ifndef SQLITE_OMIT_CHECK
ExprList *pCheck; /* All CHECK constraints */
#endif
tRowcnt nRowEst; /* Estimated rows in table - from sqlite_stat1 table */
LogEst nRowLogEst; /* Estimated rows in table - from sqlite_stat1 table */
int tnum; /* Root BTree node for this table (see note above) */
i16 iPKey; /* If not negative, use aCol[iPKey] as the primary key */
i16 nCol; /* Number of columns in this table */
@ -1695,7 +1695,7 @@ struct UnpackedRecord {
struct Index {
char *zName; /* Name of this index */
i16 *aiColumn; /* Which columns are used by this index. 1st is 0 */
tRowcnt *aiRowEst; /* From ANALYZE: Est. rows selected by each column */
LogEst *aiRowLogEst; /* From ANALYZE: Est. rows selected by each column */
Table *pTable; /* The SQL table being indexed */
char *zColAff; /* String defining the affinity of each column */
Index *pNext; /* The next index associated with the same table */

200
src/test_rtree.c

@ -35,6 +35,8 @@ struct Circle {
double centerx;
double centery;
double radius;
double mxArea;
int eScoreType;
};
/*
@ -50,11 +52,7 @@ static void circle_del(void *p){
static int circle_geom(
sqlite3_rtree_geometry *p,
int nCoord,
#ifdef SQLITE_RTREE_INT_ONLY
sqlite3_int64 *aCoord,
#else
double *aCoord,
#endif
sqlite3_rtree_dbl *aCoord,
int *pRes
){
int i; /* Iterator variable */
@ -62,7 +60,12 @@ static int circle_geom(
double xmin, xmax; /* X dimensions of box being tested */
double ymin, ymax; /* X dimensions of box being tested */
if( p->pUser==0 ){
xmin = aCoord[0];
xmax = aCoord[1];
ymin = aCoord[2];
ymax = aCoord[3];
pCircle = (Circle *)p->pUser;
if( pCircle==0 ){
/* If pUser is still 0, then the parameter values have not been tested
** for correctness or stored into a Circle structure yet. Do this now. */
@ -108,14 +111,9 @@ static int circle_geom(
pCircle->aBox[1].xmax = pCircle->centerx - pCircle->radius;
pCircle->aBox[1].ymin = pCircle->centery;
pCircle->aBox[1].ymax = pCircle->centery;
pCircle->mxArea = (xmax - xmin)*(ymax - ymin) + 1.0;
}
pCircle = (Circle *)p->pUser;
xmin = aCoord[0];
xmax = aCoord[1];
ymin = aCoord[2];
ymax = aCoord[3];
/* Check if any of the 4 corners of the bounding-box being tested lie
** inside the circular region. If they do, then the bounding-box does
** intersect the region of interest. Set the output variable to true and
@ -154,6 +152,170 @@ static int circle_geom(
return SQLITE_OK;
}
/*
** Implementation of "circle" r-tree geometry callback using the
** 2nd-generation interface that allows scoring.
*/
static int circle_query_func(sqlite3_rtree_query_info *p){
int i; /* Iterator variable */
Circle *pCircle; /* Structure defining circular region */
double xmin, xmax; /* X dimensions of box being tested */
double ymin, ymax; /* X dimensions of box being tested */
int nWithin = 0; /* Number of corners inside the circle */
xmin = p->aCoord[0];
xmax = p->aCoord[1];
ymin = p->aCoord[2];
ymax = p->aCoord[3];
pCircle = (Circle *)p->pUser;
if( pCircle==0 ){
/* If pUser is still 0, then the parameter values have not been tested
** for correctness or stored into a Circle structure yet. Do this now. */
/* This geometry callback is for use with a 2-dimensional r-tree table.
** Return an error if the table does not have exactly 2 dimensions. */
if( p->nCoord!=4 ) return SQLITE_ERROR;
/* Test that the correct number of parameters (4) have been supplied,
** and that the parameters are in range (that the radius of the circle
** radius is greater than zero). */
if( p->nParam!=4 || p->aParam[2]<0.0 ) return SQLITE_ERROR;
/* Allocate a structure to cache parameter data in. Return SQLITE_NOMEM
** if the allocation fails. */
pCircle = (Circle *)(p->pUser = sqlite3_malloc(sizeof(Circle)));
if( !pCircle ) return SQLITE_NOMEM;
p->xDelUser = circle_del;
/* Record the center and radius of the circular region. One way that
** tested bounding boxes that intersect the circular region are detected
** is by testing if each corner of the bounding box lies within radius
** units of the center of the circle. */
pCircle->centerx = p->aParam[0];
pCircle->centery = p->aParam[1];
pCircle->radius = p->aParam[2];
pCircle->eScoreType = (int)p->aParam[3];
/* Define two bounding box regions. The first, aBox[0], extends to
** infinity in the X dimension. It covers the same range of the Y dimension
** as the circular region. The second, aBox[1], extends to infinity in
** the Y dimension and is constrained to the range of the circle in the
** X dimension.
**
** Then imagine each box is split in half along its short axis by a line
** that intersects the center of the circular region. A bounding box
** being tested can be said to intersect the circular region if it contains
** points from each half of either of the two infinite bounding boxes.
*/
pCircle->aBox[0].xmin = pCircle->centerx;
pCircle->aBox[0].xmax = pCircle->centerx;
pCircle->aBox[0].ymin = pCircle->centery + pCircle->radius;
pCircle->aBox[0].ymax = pCircle->centery - pCircle->radius;
pCircle->aBox[1].xmin = pCircle->centerx + pCircle->radius;
pCircle->aBox[1].xmax = pCircle->centerx - pCircle->radius;
pCircle->aBox[1].ymin = pCircle->centery;
pCircle->aBox[1].ymax = pCircle->centery;
pCircle->mxArea = 200.0*200.0;
}
/* Check if any of the 4 corners of the bounding-box being tested lie
** inside the circular region. If they do, then the bounding-box does
** intersect the region of interest. Set the output variable to true and
** return SQLITE_OK in this case. */
for(i=0; i<4; i++){
double x = (i&0x01) ? xmax : xmin;
double y = (i&0x02) ? ymax : ymin;
double d2;
d2 = (x-pCircle->centerx)*(x-pCircle->centerx);
d2 += (y-pCircle->centery)*(y-pCircle->centery);
if( d2<(pCircle->radius*pCircle->radius) ) nWithin++;
}
/* Check if the bounding box covers any other part of the circular region.
** See comments above for a description of how this test works. If it does
** cover part of the circular region, set the output variable to true
** and return SQLITE_OK. */
if( nWithin==0 ){
for(i=0; i<2; i++){
if( xmin<=pCircle->aBox[i].xmin
&& xmax>=pCircle->aBox[i].xmax
&& ymin<=pCircle->aBox[i].ymin
&& ymax>=pCircle->aBox[i].ymax
){
nWithin = 1;
break;
}
}
}
if( pCircle->eScoreType==1 ){
/* Depth first search */
p->rScore = p->iLevel;
}else if( pCircle->eScoreType==2 ){
/* Breadth first search */
p->rScore = 100 - p->iLevel;
}else if( pCircle->eScoreType==3 ){
/* Depth-first search, except sort the leaf nodes by area with
** the largest area first */
if( p->iLevel==1 ){
p->rScore = 1.0 - (xmax-xmin)*(ymax-ymin)/pCircle->mxArea;
if( p->rScore<0.01 ) p->rScore = 0.01;
}else{
p->rScore = 0.0;
}
}else if( pCircle->eScoreType==4 ){
/* Depth-first search, except exclude odd rowids */
p->rScore = p->iLevel;
if( p->iRowid&1 ) nWithin = 0;
}else{
/* Breadth-first search, except exclude odd rowids */
p->rScore = 100 - p->iLevel;
if( p->iRowid&1 ) nWithin = 0;
}
if( nWithin==0 ){
p->eWithin = NOT_WITHIN;
}else if( nWithin>=4 ){
p->eWithin = FULLY_WITHIN;
}else{
p->eWithin = PARTLY_WITHIN;
}
return SQLITE_OK;
}
/*
** Implementation of "breadthfirstsearch" r-tree geometry callback using the
** 2nd-generation interface that allows scoring.
**
** ... WHERE id MATCH breadthfirstsearch($x0,$x1,$y0,$y1) ...
**
** It returns all entries whose bounding boxes overlap with $x0,$x1,$y0,$y1.
*/
static int bfs_query_func(sqlite3_rtree_query_info *p){
double x0,x1,y0,y1; /* Dimensions of box being tested */
double bx0,bx1,by0,by1; /* Boundary of the query function */
if( p->nParam!=4 ) return SQLITE_ERROR;
x0 = p->aCoord[0];
x1 = p->aCoord[1];
y0 = p->aCoord[2];
y1 = p->aCoord[3];
bx0 = p->aParam[0];
bx1 = p->aParam[1];
by0 = p->aParam[2];
by1 = p->aParam[3];
p->rScore = 100 - p->iLevel;
if( p->eParentWithin==FULLY_WITHIN ){
p->eWithin = FULLY_WITHIN;
}else if( x0>=bx0 && x1<=bx1 && y0>=by0 && y1<=by1 ){
p->eWithin = FULLY_WITHIN;
}else if( x1>=bx0 && x0<=bx1 && y1>=by0 && y0<=by1 ){
p->eWithin = PARTLY_WITHIN;
}else{
p->eWithin = NOT_WITHIN;
}
return SQLITE_OK;
}
/* END of implementation of "circle" geometry callback.
**************************************************************************
*************************************************************************/
@ -194,11 +356,7 @@ static int gHere = 42;
static int cube_geom(
sqlite3_rtree_geometry *p,
int nCoord,
#ifdef SQLITE_RTREE_INT_ONLY
sqlite3_int64 *aCoord,
#else
double *aCoord,
#endif
sqlite3_rtree_dbl *aCoord,
int *piRes
){
Cube *pCube = (Cube *)p->pUser;
@ -293,6 +451,14 @@ static int register_circle_geom(
}
if( getDbPointer(interp, Tcl_GetString(objv[1]), &db) ) return TCL_ERROR;
rc = sqlite3_rtree_geometry_callback(db, "circle", circle_geom, 0);
if( rc==SQLITE_OK ){
rc = sqlite3_rtree_query_callback(db, "Qcircle",
circle_query_func, 0, 0);
}
if( rc==SQLITE_OK ){
rc = sqlite3_rtree_query_callback(db, "breadthfirstsearch",
bfs_query_func, 0, 0);
}
Tcl_SetResult(interp, (char *)sqlite3ErrName(rc), TCL_STATIC);
#endif
return TCL_OK;

2
src/test_vfstrace.c

@ -678,7 +678,7 @@ static int vfstraceAccess(
vfstrace_info *pInfo = (vfstrace_info*)pVfs->pAppData;
sqlite3_vfs *pRoot = pInfo->pRootVfs;
int rc;
vfstrace_printf(pInfo, "%s.xDelete(\"%s\",%d)",
vfstrace_printf(pInfo, "%s.xAccess(\"%s\",%d)",
pInfo->zVfsName, zPath, flags);
rc = pRoot->xAccess(pRoot, zPath, flags, pResOut);
vfstrace_print_errcode(pInfo, " -> %s", rc);

4
src/util.c

@ -1246,8 +1246,8 @@ LogEst sqlite3LogEstAdd(LogEst a, LogEst b){
}
/*
** Convert an integer into a LogEst. In other words, compute a
** good approximatation for 10*log2(x).
** Convert an integer into a LogEst. In other words, compute an
** approximation for 10*log2(x).
*/
LogEst sqlite3LogEst(u64 x){
static LogEst a[] = { 0, 2, 3, 5, 6, 7, 8, 9 };

5
src/vdbe.c

@ -4255,6 +4255,7 @@ case OP_SorterData: {
pC = p->apCsr[pOp->p1];
assert( isSorter(pC) );
rc = sqlite3VdbeSorterRowkey(pC, pOut);
assert( rc!=SQLITE_OK || (pOut->flags & MEM_Blob) );
break;
}
@ -6346,8 +6347,8 @@ default: { /* This is really OP_Noop and OP_Explain */
#ifdef VDBE_PROFILE
{
u64 elapsed = sqlite3Hwtime() - start;
pOp->cycles += elapsed;
u64 endTime = sqlite3Hwtime();
if( endTime>start ) pOp->cycles += endTime - start;
pOp->cnt++;
}
#endif

43
src/vdbeaux.c

@ -3137,10 +3137,14 @@ void sqlite3VdbeRecordUnpack(
** sqlite3VdbeSerialGet() and sqlite3MemCompare() functions. It is used
** in assert() statements to ensure that the optimized code in
** sqlite3VdbeRecordCompare() returns results with these two primitives.
**
** Return true if the result of comparison is equivalent to desiredResult.
** Return false if there is a disagreement.
*/
static int vdbeRecordCompareDebug(
int nKey1, const void *pKey1, /* Left key */
const UnpackedRecord *pPKey2 /* Right key */
const UnpackedRecord *pPKey2, /* Right key */
int desiredResult /* Correct answer */
){
u32 d1; /* Offset into aKey[] of next data element */
u32 idx1; /* Offset into aKey[] of next header element */
@ -3202,7 +3206,7 @@ static int vdbeRecordCompareDebug(
if( pKeyInfo->aSortOrder[i] ){
rc = -rc; /* Invert the result for DESC sort order. */
}
return rc;
goto debugCompareEnd;
}
i++;
}while( idx1<szHdr1 && i<pPKey2->nField );
@ -3216,7 +3220,15 @@ static int vdbeRecordCompareDebug(
/* rc==0 here means that one of the keys ran out of fields and
** all the fields up to that point were equal. Return the the default_rc
** value. */
return pPKey2->default_rc;
rc = pPKey2->default_rc;
debugCompareEnd:
if( desiredResult==0 && rc==0 ) return 1;
if( desiredResult<0 && rc<0 ) return 1;
if( desiredResult>0 && rc>0 ) return 1;
if( CORRUPT_DB ) return 1;
if( pKeyInfo->db->mallocFailed ) return 1;
return 0;
}
#endif
@ -3570,11 +3582,7 @@ int sqlite3VdbeRecordCompare(
if( pKeyInfo->aSortOrder[i] ){
rc = -rc;
}
assert( CORRUPT_DB || pKeyInfo->db==0
|| (rc<0 && vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)<0)
|| (rc>0 && vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)>0)
|| pKeyInfo->db->mallocFailed
);
assert( vdbeRecordCompareDebug(nKey1, pKey1, pPKey2, rc) );
assert( mem1.zMalloc==0 ); /* See comment below */
return rc;
}
@ -3593,10 +3601,7 @@ int sqlite3VdbeRecordCompare(
/* rc==0 here means that one or both of the keys ran out of fields and
** all the fields up to that point were equal. Return the the default_rc
** value. */
assert( CORRUPT_DB || pKeyInfo->db==0
|| pPKey2->default_rc==vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)
|| pKeyInfo->db->mallocFailed
);
assert( vdbeRecordCompareDebug(nKey1, pKey1, pPKey2, pPKey2->default_rc) );
return pPKey2->default_rc;
}
@ -3693,12 +3698,7 @@ static int vdbeRecordCompareInt(
res = pPKey2->default_rc;
}
assert( pPKey2->pKeyInfo->db==0
|| (res==0 && vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)==0)
|| (res<0 && vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)<0)
|| (res>0 && vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)>0)
|| CORRUPT_DB || pPKey2->pKeyInfo->db->mallocFailed
);
assert( vdbeRecordCompareDebug(nKey1, pKey1, pPKey2, res) );
return res;
}
@ -3758,12 +3758,7 @@ static int vdbeRecordCompareString(
}
}
assert( pPKey2->pKeyInfo->db==0
|| (res==0 && vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)==0)
|| (res<0 && vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)<0)
|| (res>0 && vdbeRecordCompareDebug(nKey1, pKey1, pPKey2)>0)
|| CORRUPT_DB || pPKey2->pKeyInfo->db->mallocFailed
);
assert( vdbeRecordCompareDebug(nKey1, pKey1, pPKey2, res) );
return res;
}

410
src/where.c

@ -227,7 +227,7 @@ static int whereClauseInsert(WhereClause *pWC, Expr *p, u8 wtFlags){
if( p && ExprHasProperty(p, EP_Unlikely) ){
pTerm->truthProb = sqlite3LogEst(p->iTable) - 99;
}else{
pTerm->truthProb = -1;
pTerm->truthProb = 1;
}
pTerm->pExpr = sqlite3ExprSkipCollate(p);
pTerm->wtFlags = wtFlags;
@ -1956,7 +1956,8 @@ static void whereKeyStats(
iLower = 0;
iUpper = aSample[0].anLt[iCol];
}else{
iUpper = i>=pIdx->nSample ? pIdx->aiRowEst[0] : aSample[i].anLt[iCol];
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];
}
aStat[1] = (pIdx->nKeyCol>iCol ? pIdx->aAvgEq[iCol] : 1);
@ -1975,6 +1976,29 @@ static void whereKeyStats(
}
#endif /* SQLITE_ENABLE_STAT3_OR_STAT4 */
/*
** If it is not NULL, pTerm is a term that provides an upper or lower
** bound on a range scan. Without considering pTerm, it is estimated
** that the scan will visit nNew rows. This function returns the number
** estimated to be visited after taking pTerm into account.
**
** If the user explicitly specified a likelihood() value for this term,
** then the return value is the likelihood multiplied by the number of
** input rows. Otherwise, this function assumes that an "IS NOT NULL" term
** has a likelihood of 0.50, and any other term a likelihood of 0.25.
*/
static LogEst whereRangeAdjust(WhereTerm *pTerm, LogEst nNew){
LogEst nRet = nNew;
if( pTerm ){
if( pTerm->truthProb<=0 ){
nRet += pTerm->truthProb;
}else if( (pTerm->wtFlags & TERM_VNULL)==0 ){
nRet -= 20; assert( 20==sqlite3LogEst(4) );
}
}
return nRet;
}
/*
** This function is used to estimate the number of rows that will be visited
** by scanning an index for a range of values. The range may have an upper
@ -2067,7 +2091,7 @@ static int whereRangeScanEst(
/* Determine iLower and iUpper using ($P) only. */
if( nEq==0 ){
iLower = 0;
iUpper = p->aiRowEst[0];
iUpper = sqlite3LogEstToInt(p->aiRowLogEst[0]);
}else{
/* Note: this call could be optimized away - since the same values must
** have been requested when testing key $P in whereEqualScanEst(). */
@ -2127,17 +2151,18 @@ static int whereRangeScanEst(
UNUSED_PARAMETER(pBuilder);
#endif
assert( pLower || pUpper );
/* TUNING: Each inequality constraint reduces the search space 4-fold.
** A BETWEEN operator, therefore, reduces the search space 16-fold */
nNew = nOut;
if( pLower && (pLower->wtFlags & TERM_VNULL)==0 ){
nNew -= 20; assert( 20==sqlite3LogEst(4) );
nOut--;
}
if( pUpper ){
nNew -= 20; assert( 20==sqlite3LogEst(4) );
nOut--;
}
assert( pUpper==0 || (pUpper->wtFlags & TERM_VNULL)==0 );
nNew = whereRangeAdjust(pLower, nOut);
nNew = whereRangeAdjust(pUpper, nNew);
/* TUNING: If there is both an upper and lower limit, assume the range is
** reduced by an additional 75%. This means that, by default, an open-ended
** range query (e.g. col > ?) is assumed to match 1/4 of the rows in the
** index. While a closed range (e.g. col BETWEEN ? AND ?) is estimated to
** match 1/64 of the index. */
if( pLower && pUpper ) nNew -= 20;
nOut -= (pLower!=0) + (pUpper!=0);
if( nNew<10 ) nNew = 10;
if( nNew<nOut ) nOut = nNew;
pLoop->nOut = (LogEst)nOut;
@ -2234,6 +2259,7 @@ static int whereInScanEst(
tRowcnt *pnRow /* Write the revised row estimate here */
){
Index *p = pBuilder->pNew->u.btree.pIndex;
i64 nRow0 = sqlite3LogEstToInt(p->aiRowLogEst[0]);
int nRecValid = pBuilder->nRecValid;
int rc = SQLITE_OK; /* Subfunction return code */
tRowcnt nEst; /* Number of rows for a single term */
@ -2242,14 +2268,14 @@ static int whereInScanEst(
assert( p->aSample!=0 );
for(i=0; rc==SQLITE_OK && i<pList->nExpr; i++){
nEst = p->aiRowEst[0];
nEst = nRow0;
rc = whereEqualScanEst(pParse, pBuilder, pList->a[i].pExpr, &nEst);
nRowEst += nEst;
pBuilder->nRecValid = nRecValid;
}
if( rc==SQLITE_OK ){
if( nRowEst > p->aiRowEst[0] ) nRowEst = p->aiRowEst[0];
if( nRowEst > nRow0 ) nRowEst = nRow0;
*pnRow = nRowEst;
WHERETRACE(0x10,("IN row estimate: est=%g\n", nRowEst));
}
@ -3757,12 +3783,25 @@ static int whereLoopCheaperProperSubset(
** To say "WhereLoop X is a proper subset of Y" means that X uses fewer
** WHERE clause terms than Y and that every WHERE clause term used by X is
** also used by Y.
**
** This adjustment is omitted for SKIPSCAN loops. In a SKIPSCAN loop, the
** WhereLoop.nLTerm field is not an accurate measure of the number of WHERE
** clause terms covered, since some of the first nLTerm entries in aLTerm[]
** will be NULL (because they are skipped). That makes it more difficult
** to compare the loops. We could add extra code to do the comparison, and
** perhaps we will someday. But SKIPSCAN is sufficiently uncommon, and this
** adjustment is sufficient minor, that it is very difficult to construct
** a test case where the extra code would improve the query plan. Better
** to avoid the added complexity and just omit cost adjustments to SKIPSCAN
** loops.
*/
static void whereLoopAdjustCost(const WhereLoop *p, WhereLoop *pTemplate){
if( (pTemplate->wsFlags & WHERE_INDEXED)==0 ) return;
if( (pTemplate->wsFlags & WHERE_SKIPSCAN)!=0 ) return;
for(; p; p=p->pNextLoop){
if( p->iTab!=pTemplate->iTab ) continue;
if( (p->wsFlags & WHERE_INDEXED)==0 ) continue;
if( (p->wsFlags & WHERE_SKIPSCAN)!=0 ) continue;
if( whereLoopCheaperProperSubset(p, pTemplate) ){
/* Adjust pTemplate cost downward so that it is cheaper than its
** subset p */
@ -3987,13 +4026,20 @@ static void whereLoopOutputAdjust(WhereClause *pWC, WhereLoop *pLoop){
if( pX==pTerm ) break;
if( pX->iParent>=0 && (&pWC->a[pX->iParent])==pTerm ) break;
}
if( j<0 ) pLoop->nOut += pTerm->truthProb;
if( j<0 ){
pLoop->nOut += (pTerm->truthProb<=0 ? pTerm->truthProb : -1);
}
}
}
/*
** We have so far matched pBuilder->pNew->u.btree.nEq terms of the index pIndex.
** Try to match one more.
** We have so far matched pBuilder->pNew->u.btree.nEq terms of the
** index pIndex. Try to match one more.
**
** When this function is called, pBuilder->pNew->nOut contains the
** number of rows expected to be visited by filtering using the nEq
** terms only. If it is modified, this value is restored before this
** function returns.
**
** If pProbe->tnum==0, that means pIndex is a fake index used for the
** INTEGER PRIMARY KEY.
@ -4019,7 +4065,6 @@ static int whereLoopAddBtreeIndex(
LogEst saved_nOut; /* Original value of pNew->nOut */
int iCol; /* Index of the column in the table */
int rc = SQLITE_OK; /* Return code */
LogEst nRowEst; /* Estimated index selectivity */
LogEst rLogSize; /* Logarithm of table size */
WhereTerm *pTop = 0, *pBtm = 0; /* Top and bottom range constraints */
@ -4040,11 +4085,8 @@ static int whereLoopAddBtreeIndex(
assert( pNew->u.btree.nEq<=pProbe->nKeyCol );
if( pNew->u.btree.nEq < pProbe->nKeyCol ){
iCol = pProbe->aiColumn[pNew->u.btree.nEq];
nRowEst = sqlite3LogEst(pProbe->aiRowEst[pNew->u.btree.nEq+1]);
if( nRowEst==0 && pProbe->onError==OE_None ) nRowEst = 1;
}else{
iCol = -1;
nRowEst = 0;
}
pTerm = whereScanInit(&scan, pBuilder->pWC, pSrc->iCursor, iCol,
opMask, pProbe);
@ -4055,18 +4097,23 @@ static int whereLoopAddBtreeIndex(
saved_prereq = pNew->prereq;
saved_nOut = pNew->nOut;
pNew->rSetup = 0;
rLogSize = estLog(sqlite3LogEst(pProbe->aiRowEst[0]));
rLogSize = estLog(pProbe->aiRowLogEst[0]);
/* Consider using a skip-scan if there are no WHERE clause constraints
** available for the left-most terms of the index, and if the average
** number of repeats in the left-most terms is at least 18. The magic
** number 18 was found by experimentation to be the payoff point where
** skip-scan become faster than a full-scan.
*/
** number of repeats in the left-most terms is at least 18.
**
** The magic number 18 is selected on the basis that scanning 17 rows
** is almost always quicker than an index seek (even though if the index
** contains fewer than 2^17 rows we assume otherwise in other parts of
** the code). And, even if it is not, it should not be too much slower.
** On the other hand, the extra seeks could end up being significantly
** more expensive. */
assert( 42==sqlite3LogEst(18) );
if( pTerm==0
&& saved_nEq==saved_nSkip
&& saved_nEq+1<pProbe->nKeyCol
&& pProbe->aiRowEst[saved_nEq+1]>=18 /* TUNING: Minimum for skip-scan */
&& pProbe->aiRowLogEst[saved_nEq+1]>=42 /* TUNING: Minimum for skip-scan */
&& (rc = whereLoopResize(db, pNew, pNew->nLTerm+1))==SQLITE_OK
){
LogEst nIter;
@ -4074,34 +4121,40 @@ static int whereLoopAddBtreeIndex(
pNew->u.btree.nSkip++;
pNew->aLTerm[pNew->nLTerm++] = 0;
pNew->wsFlags |= WHERE_SKIPSCAN;
nIter = sqlite3LogEst(pProbe->aiRowEst[0]/pProbe->aiRowEst[saved_nEq+1]);
pNew->rRun = rLogSize + nIter;
pNew->nOut += nIter;
whereLoopAddBtreeIndex(pBuilder, pSrc, pProbe, nIter);
nIter = pProbe->aiRowLogEst[saved_nEq] - pProbe->aiRowLogEst[saved_nEq+1];
pNew->nOut -= nIter;
whereLoopAddBtreeIndex(pBuilder, pSrc, pProbe, nIter + nInMul);
pNew->nOut = saved_nOut;
}
for(; rc==SQLITE_OK && pTerm!=0; pTerm = whereScanNext(&scan)){
u16 eOp = pTerm->eOperator; /* Shorthand for pTerm->eOperator */
LogEst rCostIdx;
LogEst nOutUnadjusted; /* nOut before IN() and WHERE adjustments */
int nIn = 0;
#ifdef SQLITE_ENABLE_STAT3_OR_STAT4
int nRecValid = pBuilder->nRecValid;
#endif
if( (pTerm->eOperator==WO_ISNULL || (pTerm->wtFlags&TERM_VNULL)!=0)
if( (eOp==WO_ISNULL || (pTerm->wtFlags&TERM_VNULL)!=0)
&& (iCol<0 || pSrc->pTab->aCol[iCol].notNull)
){
continue; /* ignore IS [NOT] NULL constraints on NOT NULL columns */
}
if( pTerm->prereqRight & pNew->maskSelf ) continue;
assert( pNew->nOut==saved_nOut );
pNew->wsFlags = saved_wsFlags;
pNew->u.btree.nEq = saved_nEq;
pNew->nLTerm = saved_nLTerm;
if( whereLoopResize(db, pNew, pNew->nLTerm+1) ) break; /* OOM */
pNew->aLTerm[pNew->nLTerm++] = pTerm;
pNew->prereq = (saved_prereq | pTerm->prereqRight) & ~pNew->maskSelf;
pNew->rRun = rLogSize; /* Baseline cost is log2(N). Adjustments below */
if( pTerm->eOperator & WO_IN ){
assert( nInMul==0
|| (pNew->wsFlags & WHERE_COLUMN_NULL)!=0
|| (pNew->wsFlags & WHERE_COLUMN_IN)!=0
|| (pNew->wsFlags & WHERE_SKIPSCAN)!=0
);
if( eOp & WO_IN ){
Expr *pExpr = pTerm->pExpr;
pNew->wsFlags |= WHERE_COLUMN_IN;
if( ExprHasProperty(pExpr, EP_xIsSelect) ){
@ -4113,83 +4166,118 @@ static int whereLoopAddBtreeIndex(
}
assert( nIn>0 ); /* RHS always has 2 or more terms... The parser
** changes "x IN (?)" into "x=?". */
pNew->rRun += nIn;
pNew->u.btree.nEq++;
pNew->nOut = nRowEst + nInMul + nIn;
}else if( pTerm->eOperator & (WO_EQ) ){
assert(
(pNew->wsFlags & (WHERE_COLUMN_NULL|WHERE_COLUMN_IN|WHERE_SKIPSCAN))!=0
|| nInMul==0
);
}else if( eOp & (WO_EQ) ){
pNew->wsFlags |= WHERE_COLUMN_EQ;
if( iCol<0 || (nInMul==0 && pNew->u.btree.nEq==pProbe->nKeyCol-1)){
assert( (pNew->wsFlags & WHERE_COLUMN_IN)==0 || iCol<0 );
if( iCol<0 || (nInMul==0 && pNew->u.btree.nEq==pProbe->nKeyCol-1) ){
if( iCol>=0 && pProbe->onError==OE_None ){
pNew->wsFlags |= WHERE_UNQ_WANTED;
}else{
pNew->wsFlags |= WHERE_ONEROW;
}
}
pNew->u.btree.nEq++;
pNew->nOut = nRowEst + nInMul;
}else if( pTerm->eOperator & (WO_ISNULL) ){
}else if( eOp & WO_ISNULL ){
pNew->wsFlags |= WHERE_COLUMN_NULL;
pNew->u.btree.nEq++;
/* TUNING: IS NULL selects 2 rows */
nIn = 10; assert( 10==sqlite3LogEst(2) );
pNew->nOut = nRowEst + nInMul + nIn;
}else if( pTerm->eOperator & (WO_GT|WO_GE) ){
testcase( pTerm->eOperator & WO_GT );
testcase( pTerm->eOperator & WO_GE );
}else if( eOp & (WO_GT|WO_GE) ){
testcase( eOp & WO_GT );
testcase( eOp & WO_GE );
pNew->wsFlags |= WHERE_COLUMN_RANGE|WHERE_BTM_LIMIT;
pBtm = pTerm;
pTop = 0;
}else{
assert( pTerm->eOperator & (WO_LT|WO_LE) );
testcase( pTerm->eOperator & WO_LT );
testcase( pTerm->eOperator & WO_LE );
assert( eOp & (WO_LT|WO_LE) );
testcase( eOp & WO_LT );
testcase( eOp & WO_LE );
pNew->wsFlags |= WHERE_COLUMN_RANGE|WHERE_TOP_LIMIT;
pTop = pTerm;
pBtm = (pNew->wsFlags & WHERE_BTM_LIMIT)!=0 ?
pNew->aLTerm[pNew->nLTerm-2] : 0;
}
/* At this point pNew->nOut is set to the number of rows expected to
** be visited by the index scan before considering term pTerm, or the
** values of nIn and nInMul. In other words, assuming that all
** "x IN(...)" terms are replaced with "x = ?". This block updates
** the value of pNew->nOut to account for pTerm (but not nIn/nInMul). */
assert( pNew->nOut==saved_nOut );
if( pNew->wsFlags & WHERE_COLUMN_RANGE ){
/* Adjust nOut and rRun for STAT3 range values */
assert( pNew->nOut==saved_nOut );
/* Adjust nOut using stat3/stat4 data. Or, if there is no stat3/stat4
** data, using some other estimate. */
whereRangeScanEst(pParse, pBuilder, pBtm, pTop, pNew);
}
}else{
int nEq = ++pNew->u.btree.nEq;
assert( eOp & (WO_ISNULL|WO_EQ|WO_IN) );
assert( pNew->nOut==saved_nOut );
if( pTerm->truthProb<=0 && iCol>=0 ){
assert( (eOp & WO_IN) || nIn==0 );
testcase( eOp & WO_IN );
pNew->nOut += pTerm->truthProb;
pNew->nOut -= nIn;
pNew->wsFlags |= WHERE_LIKELIHOOD;
}else{
#ifdef SQLITE_ENABLE_STAT3_OR_STAT4
if( nInMul==0
&& pProbe->nSample
&& pNew->u.btree.nEq<=pProbe->nSampleCol
&& OptimizationEnabled(db, SQLITE_Stat3)
){
Expr *pExpr = pTerm->pExpr;
tRowcnt nOut = 0;
if( (pTerm->eOperator & (WO_EQ|WO_ISNULL))!=0 ){
testcase( pTerm->eOperator & WO_EQ );
testcase( pTerm->eOperator & WO_ISNULL );
rc = whereEqualScanEst(pParse, pBuilder, pExpr->pRight, &nOut);
}else if( (pTerm->eOperator & WO_IN)
&& !ExprHasProperty(pExpr, EP_xIsSelect) ){
rc = whereInScanEst(pParse, pBuilder, pExpr->x.pList, &nOut);
}
assert( nOut==0 || rc==SQLITE_OK );
if( nOut ){
pNew->nOut = sqlite3LogEst(nOut);
if( pNew->nOut>saved_nOut ) pNew->nOut = saved_nOut;
}
}
tRowcnt nOut = 0;
if( nInMul==0
&& pProbe->nSample
&& pNew->u.btree.nEq<=pProbe->nSampleCol
&& OptimizationEnabled(db, SQLITE_Stat3)
&& ((eOp & WO_IN)==0 || !ExprHasProperty(pTerm->pExpr, EP_xIsSelect))
&& (pNew->wsFlags & WHERE_LIKELIHOOD)==0
){
Expr *pExpr = pTerm->pExpr;
if( (eOp & (WO_EQ|WO_ISNULL))!=0 ){
testcase( eOp & WO_EQ );
testcase( eOp & WO_ISNULL );
rc = whereEqualScanEst(pParse, pBuilder, pExpr->pRight, &nOut);
}else{
rc = whereInScanEst(pParse, pBuilder, pExpr->x.pList, &nOut);
}
assert( rc!=SQLITE_OK || nOut>0 );
if( rc==SQLITE_NOTFOUND ) rc = SQLITE_OK;
if( rc!=SQLITE_OK ) break; /* Jump out of the pTerm loop */
if( nOut ){
pNew->nOut = sqlite3LogEst(nOut);
if( pNew->nOut>saved_nOut ) pNew->nOut = saved_nOut;
pNew->nOut -= nIn;
}
}
if( nOut==0 )
#endif
if( (pNew->wsFlags & (WHERE_IDX_ONLY|WHERE_IPK))==0 ){
/* Each row involves a step of the index, then a binary search of
** the main table */
pNew->rRun = sqlite3LogEstAdd(pNew->rRun,rLogSize>27 ? rLogSize-17 : 10);
{
pNew->nOut += (pProbe->aiRowLogEst[nEq] - pProbe->aiRowLogEst[nEq-1]);
if( eOp & WO_ISNULL ){
/* TUNING: If there is no likelihood() value, assume that a
** "col IS NULL" expression matches twice as many rows
** as (col=?). */
pNew->nOut += 10;
}
}
}
}
/* Step cost for each output row */
pNew->rRun = sqlite3LogEstAdd(pNew->rRun, pNew->nOut);
/* Set rCostIdx to the cost of visiting selected rows in index. Add
** it to pNew->rRun, which is currently set to the cost of the index
** seek only. Then, if this is a non-covering index, add the cost of
** visiting the rows in the main table. */
rCostIdx = pNew->nOut + 1 + (15*pProbe->szIdxRow)/pSrc->pTab->szTabRow;
pNew->rRun = sqlite3LogEstAdd(rLogSize, rCostIdx);
if( (pNew->wsFlags & (WHERE_IDX_ONLY|WHERE_IPK))==0 ){
pNew->rRun = sqlite3LogEstAdd(pNew->rRun, pNew->nOut + 16);
}
nOutUnadjusted = pNew->nOut;
pNew->rRun += nInMul + nIn;
pNew->nOut += nInMul + nIn;
whereLoopOutputAdjust(pBuilder->pWC, pNew);
rc = whereLoopInsert(pBuilder, pNew);
if( pNew->wsFlags & WHERE_COLUMN_RANGE ){
pNew->nOut = saved_nOut;
}else{
pNew->nOut = nOutUnadjusted;
}
if( (pNew->wsFlags & WHERE_TOP_LIMIT)==0
&& pNew->u.btree.nEq<(pProbe->nKeyCol + (pProbe->zName!=0))
){
@ -4273,6 +4361,29 @@ static int whereUsablePartialIndex(int iTab, WhereClause *pWC, Expr *pWhere){
** Add all WhereLoop objects for a single table of the join where the table
** is idenfied by pBuilder->pNew->iTab. That table is guaranteed to be
** a b-tree table, not a virtual table.
**
** The costs (WhereLoop.rRun) of the b-tree loops added by this function
** are calculated as follows:
**
** For a full scan, assuming the table (or index) contains nRow rows:
**
** cost = nRow * 3.0 // full-table scan
** cost = nRow * K // scan of covering index
** cost = nRow * (K+3.0) // scan of non-covering index
**
** where K is a value between 1.1 and 3.0 set based on the relative
** estimated average size of the index and table records.
**
** For an index scan, where nVisit is the number of index rows visited
** by the scan, and nSeek is the number of seek operations required on
** the index b-tree:
**
** cost = nSeek * (log(nRow) + K * nVisit) // covering index
** cost = nSeek * (log(nRow) + (K+3.0) * nVisit) // non-covering index
**
** Normally, nSeek is 1. nSeek values greater than 1 come about if the
** WHERE clause includes "x IN (....)" terms used in place of "x=?". Or when
** implicit "x IN (SELECT x FROM tbl)" terms are added for skip-scans.
*/
static int whereLoopAddBtree(
WhereLoopBuilder *pBuilder, /* WHERE clause information */
@ -4281,7 +4392,7 @@ static int whereLoopAddBtree(
WhereInfo *pWInfo; /* WHERE analysis context */
Index *pProbe; /* An index we are evaluating */
Index sPk; /* A fake index object for the primary key */
tRowcnt aiRowEstPk[2]; /* The aiRowEst[] value for the sPk index */
LogEst aiRowEstPk[2]; /* The aiRowLogEst[] value for the sPk index */
i16 aiColumnPk = -1; /* The aColumn[] value for the sPk index */
SrcList *pTabList; /* The FROM clause */
struct SrcList_item *pSrc; /* The FROM clause btree term to add */
@ -4316,11 +4427,12 @@ static int whereLoopAddBtree(
memset(&sPk, 0, sizeof(Index));
sPk.nKeyCol = 1;
sPk.aiColumn = &aiColumnPk;
sPk.aiRowEst = aiRowEstPk;
sPk.aiRowLogEst = aiRowEstPk;
sPk.onError = OE_Replace;
sPk.pTable = pTab;
aiRowEstPk[0] = pTab->nRowEst;
aiRowEstPk[1] = 1;
sPk.szIdxRow = pTab->szTabRow;
aiRowEstPk[0] = pTab->nRowLogEst;
aiRowEstPk[1] = 0;
pFirst = pSrc->pTab->pIndex;
if( pSrc->notIndexed==0 ){
/* The real indices of the table are only considered if the
@ -4329,7 +4441,7 @@ static int whereLoopAddBtree(
}
pProbe = &sPk;
}
rSize = sqlite3LogEst(pTab->nRowEst);
rSize = pTab->nRowLogEst;
rLogSize = estLog(rSize);
#ifndef SQLITE_OMIT_AUTOMATIC_INDEX
@ -4379,6 +4491,7 @@ static int whereLoopAddBtree(
&& !whereUsablePartialIndex(pNew->iTab, pWC, pProbe->pPartIdxWhere) ){
continue; /* Partial index inappropriate for this query */
}
rSize = pProbe->aiRowLogEst[0];
pNew->u.btree.nEq = 0;
pNew->u.btree.nSkip = 0;
pNew->nLTerm = 0;
@ -4396,10 +4509,8 @@ static int whereLoopAddBtree(
/* Full table scan */
pNew->iSortIdx = b ? iSortIdx : 0;
/* TUNING: Cost of full table scan is 3*(N + log2(N)).
** + The extra 3 factor is to encourage the use of indexed lookups
** over full scans. FIXME */
pNew->rRun = sqlite3LogEstAdd(rSize,rLogSize) + 16;
/* TUNING: Cost of full table scan is (N*3.0). */
pNew->rRun = rSize + 16;
whereLoopOutputAdjust(pWC, pNew);
rc = whereLoopInsert(pBuilder, pNew);
pNew->nOut = rSize;
@ -4426,35 +4537,16 @@ static int whereLoopAddBtree(
)
){
pNew->iSortIdx = b ? iSortIdx : 0;
/* TUNING: The base cost of an index scan is N + log2(N).
** The log2(N) is for the initial seek to the beginning and the N
** is for the scan itself. */
pNew->rRun = sqlite3LogEstAdd(rSize, rLogSize);
if( m==0 ){
/* TUNING: Cost of a covering index scan is K*(N + log2(N)).
** + The extra factor K of between 1.1 and 3.0 that depends
** on the relative sizes of the table and the index. K
** is smaller for smaller indices, thus favoring them.
** The upper bound on K (3.0) matches the penalty factor
** on a full table scan that tries to encourage the use of
** indexed lookups over full scans.
*/
pNew->rRun += 1 + (15*pProbe->szIdxRow)/pTab->szTabRow;
}else{
/* TUNING: The cost of scanning a non-covering index is multiplied
** by log2(N) to account for the binary search of the main table
** that must happen for each row of the index.
** TODO: Should there be a multiplier here, analogous to the 3x
** multiplier for a fulltable scan or covering index scan, to
** further discourage the use of an index scan? Or is the log2(N)
** term sufficient discouragement?
** TODO: What if some or all of the WHERE clause terms can be
** computed without reference to the original table. Then the
** penality should reduce to logK where K is the number of output
** rows.
*/
pNew->rRun += rLogSize;
/* The cost of visiting the index rows is N*K, where K is
** between 1.1 and 3.0, depending on the relative sizes of the
** index and table rows. If this is a non-covering index scan,
** also add the cost of visiting table rows (N*3.0). */
pNew->rRun = rSize + 1 + (15*pProbe->szIdxRow)/pTab->szTabRow;
if( m!=0 ){
pNew->rRun = sqlite3LogEstAdd(pNew->rRun, rSize+16);
}
whereLoopOutputAdjust(pWC, pNew);
rc = whereLoopInsert(pBuilder, pNew);
pNew->nOut = rSize;
@ -4658,7 +4750,7 @@ static int whereLoopAddOr(WhereLoopBuilder *pBuilder, Bitmask mExtra){
int iCur;
WhereClause tempWC;
WhereLoopBuilder sSubBuild;
WhereOrSet sSum, sCur, sPrev;
WhereOrSet sSum, sCur;
struct SrcList_item *pItem;
pWC = pBuilder->pWC;
@ -4714,6 +4806,7 @@ static int whereLoopAddOr(WhereLoopBuilder *pBuilder, Bitmask mExtra){
whereOrMove(&sSum, &sCur);
once = 0;
}else{
WhereOrSet sPrev;
whereOrMove(&sPrev, &sSum);
sSum.n = 0;
for(i=0; i<sPrev.n; i++){
@ -4732,8 +4825,19 @@ static int whereLoopAddOr(WhereLoopBuilder *pBuilder, Bitmask mExtra){
pNew->iSortIdx = 0;
memset(&pNew->u, 0, sizeof(pNew->u));
for(i=0; rc==SQLITE_OK && i<sSum.n; i++){
/* TUNING: Multiple by 3.5 for the secondary table lookup */
pNew->rRun = sSum.a[i].rRun + 18;
/* TUNING: Currently sSum.a[i].rRun is set to the sum of the costs
** of all sub-scans required by the OR-scan. However, due to rounding
** errors, it may be that the cost of the OR-scan is equal to its
** most expensive sub-scan. Add the smallest possible penalty
** (equivalent to multiplying the cost by 1.07) to ensure that
** this does not happen. Otherwise, for WHERE clauses such as the
** following where there is an index on "y":
**
** WHERE likelihood(x=?, 0.99) OR y=?
**
** the planner may elect to "OR" together a full-table scan and an
** index lookup. And other similarly odd results. */
pNew->rRun = sSum.a[i].rRun + 1;
pNew->nOut = sSum.a[i].nOut;
pNew->prereq = sSum.a[i].prereq;
rc = whereLoopInsert(pBuilder, pNew);
@ -4857,14 +4961,6 @@ static i8 wherePathSatisfiesOrderBy(
*/
assert( pOrderBy!=0 );
/* Sortability of virtual tables is determined by the xBestIndex method
** of the virtual table itself */
if( pLast->wsFlags & WHERE_VIRTUALTABLE ){
testcase( nLoop>0 ); /* True when outer loops are one-row and match
** no ORDER BY terms */
return pLast->u.vtab.isOrdered;
}
if( nLoop && OptimizationDisabled(db, SQLITE_OrderByIdxJoin) ) return 0;
nOrderBy = pOrderBy->nExpr;
@ -4877,7 +4973,10 @@ static i8 wherePathSatisfiesOrderBy(
for(iLoop=0; isOrderDistinct && obSat<obDone && iLoop<=nLoop; iLoop++){
if( iLoop>0 ) ready |= pLoop->maskSelf;
pLoop = iLoop<nLoop ? pPath->aLoop[iLoop] : pLast;
assert( (pLoop->wsFlags & WHERE_VIRTUALTABLE)==0 );
if( pLoop->wsFlags & WHERE_VIRTUALTABLE ){
if( pLoop->u.vtab.isOrdered ) obSat = obDone;
break;
}
iCur = pWInfo->pTabList->a[pLoop->iTab].iCursor;
/* Mark off any ORDER BY term X that is a column in the table of
@ -5184,22 +5283,27 @@ static int wherePathSolver(WhereInfo *pWInfo, LogEst nRowEst){
pWInfo->pOrderBy, pFrom, pWInfo->wctrlFlags,
iLoop, pWLoop, &revMask);
if( isOrdered>=0 && isOrdered<nOrderBy ){
/* TUNING: Estimated cost of sorting is N*log(N).
** If the order-by clause has X terms but only the last Y terms
** are out of order, then block-sorting will reduce the sorting
** cost to N*log(N)*log(Y/X). The log(Y/X) term is computed
** by rScale.
** TODO: Should the sorting cost get a small multiplier to help
** discourage the use of sorting and encourage the use of index
** scans instead?
*/
/* TUNING: Estimated cost of a full external sort, where N is
** the number of rows to sort is:
**
** cost = (3.0 * N * log(N)).
**
** Or, if the order-by clause has X terms but only the last Y
** terms are out of order, then block-sorting will reduce the
** sorting cost to:
**
** cost = (3.0 * N * log(N)) * (Y/X)
**
** The (Y/X) term is implemented using stack variable rScale
** below. */
LogEst rScale, rSortCost;
assert( nOrderBy>0 );
assert( nOrderBy>0 && 66==sqlite3LogEst(100) );
rScale = sqlite3LogEst((nOrderBy-isOrdered)*100/nOrderBy) - 66;
rSortCost = nRowEst + estLog(nRowEst) + rScale;
rSortCost = nRowEst + estLog(nRowEst) + rScale + 16;
/* TUNING: The cost of implementing DISTINCT using a B-TREE is
** also N*log(N) but it has a larger constant of proportionality.
** Multiply by 3.0. */
** similar but with a larger constant of proportionality.
** Multiply by an additional factor of 3.0. */
if( pWInfo->wctrlFlags & WHERE_WANT_DISTINCT ){
rSortCost += 16;
}

1
src/whereInt.h

@ -458,3 +458,4 @@ struct WhereInfo {
#define WHERE_AUTO_INDEX 0x00004000 /* Uses an ephemeral index */
#define WHERE_SKIPSCAN 0x00008000 /* Uses the skip-scan algorithm */
#define WHERE_UNQ_WANTED 0x00010000 /* WHERE_ONEROW would have been helpful*/
#define WHERE_LIKELIHOOD 0x00020000 /* A likelihood() is affecting nOut */

42
test/analyze3.test

@ -103,12 +103,21 @@ do_test analyze3-1.1.1 {
}
} {1}
do_execsql_test analyze3-1.1.x {
SELECT count(*) FROM t1 WHERE x>200 AND x<300;
SELECT count(*) FROM t1 WHERE x>0 AND x<1100;
} {99 1000}
# The first of the following two SELECT statements visits 99 rows. So
# it is better to use the index. But the second visits every row in
# the table (1000 in total) so it is better to do a full-table scan.
#
do_eqp_test analyze3-1.1.2 {
SELECT sum(y) FROM t1 WHERE x>200 AND x<300
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (x>? AND x<?)}}
do_eqp_test analyze3-1.1.3 {
SELECT sum(y) FROM t1 WHERE x>0 AND x<1100
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (x>? AND x<?)}}
} {0 0 0 {SCAN TABLE t1}}
do_test analyze3-1.1.4 {
sf_execsql { SELECT sum(y) FROM t1 WHERE x>200 AND x<300 }
@ -125,17 +134,17 @@ do_test analyze3-1.1.6 {
} {199 0 14850}
do_test analyze3-1.1.7 {
sf_execsql { SELECT sum(y) FROM t1 WHERE x>0 AND x<1100 }
} {2000 0 499500}
} {999 999 499500}
do_test analyze3-1.1.8 {
set l [string range "0" 0 end]
set u [string range "1100" 0 end]
sf_execsql { SELECT sum(y) FROM t1 WHERE x>$l AND x<$u }
} {2000 0 499500}
} {999 999 499500}
do_test analyze3-1.1.9 {
set l [expr int(0)]
set u [expr int(1100)]
sf_execsql { SELECT sum(y) FROM t1 WHERE x>$l AND x<$u }
} {2000 0 499500}
} {999 999 499500}
# The following tests are similar to the block above. The difference is
@ -152,12 +161,17 @@ do_test analyze3-1.2.1 {
ANALYZE;
}
} {}
do_execsql_test analyze3-2.1.x {
SELECT count(*) FROM t2 WHERE x>1 AND x<2;
SELECT count(*) FROM t2 WHERE x>0 AND x<99;
} {200 990}
do_eqp_test analyze3-1.2.2 {
SELECT sum(y) FROM t2 WHERE x>1 AND x<2
} {0 0 0 {SEARCH TABLE t2 USING INDEX i2 (x>? AND x<?)}}
do_eqp_test analyze3-1.2.3 {
SELECT sum(y) FROM t2 WHERE x>0 AND x<99
} {0 0 0 {SEARCH TABLE t2 USING INDEX i2 (x>? AND x<?)}}
} {0 0 0 {SCAN TABLE t2}}
do_test analyze3-1.2.4 {
sf_execsql { SELECT sum(y) FROM t2 WHERE x>12 AND x<20 }
} {161 0 4760}
@ -173,17 +187,17 @@ do_test analyze3-1.2.6 {
} {161 0 integer integer 4760}
do_test analyze3-1.2.7 {
sf_execsql { SELECT sum(y) FROM t2 WHERE x>0 AND x<99 }
} {1981 0 490555}
} {999 999 490555}
do_test analyze3-1.2.8 {
set l [string range "0" 0 end]
set u [string range "99" 0 end]
sf_execsql {SELECT typeof($l), typeof($u), sum(y) FROM t2 WHERE x>$l AND x<$u}
} {1981 0 text text 490555}
} {999 999 text text 490555}
do_test analyze3-1.2.9 {
set l [expr int(0)]
set u [expr int(99)]
sf_execsql {SELECT typeof($l), typeof($u), sum(y) FROM t2 WHERE x>$l AND x<$u}
} {1981 0 integer integer 490555}
} {999 999 integer integer 490555}
# Same tests a third time. This time, column x has INTEGER affinity and
# is not the leftmost column of the table. This triggered a bug causing
@ -199,12 +213,16 @@ do_test analyze3-1.3.1 {
ANALYZE;
}
} {}
do_execsql_test analyze3-1.3.x {
SELECT count(*) FROM t3 WHERE x>200 AND x<300;
SELECT count(*) FROM t3 WHERE x>0 AND x<1100
} {99 1000}
do_eqp_test analyze3-1.3.2 {
SELECT sum(y) FROM t3 WHERE x>200 AND x<300
} {0 0 0 {SEARCH TABLE t3 USING INDEX i3 (x>? AND x<?)}}
do_eqp_test analyze3-1.3.3 {
SELECT sum(y) FROM t3 WHERE x>0 AND x<1100
} {0 0 0 {SEARCH TABLE t3 USING INDEX i3 (x>? AND x<?)}}
} {0 0 0 {SCAN TABLE t3}}
do_test analyze3-1.3.4 {
sf_execsql { SELECT sum(y) FROM t3 WHERE x>200 AND x<300 }
@ -221,17 +239,17 @@ do_test analyze3-1.3.6 {
} {199 0 14850}
do_test analyze3-1.3.7 {
sf_execsql { SELECT sum(y) FROM t3 WHERE x>0 AND x<1100 }
} {2000 0 499500}
} {999 999 499500}
do_test analyze3-1.3.8 {
set l [string range "0" 0 end]
set u [string range "1100" 0 end]
sf_execsql { SELECT sum(y) FROM t3 WHERE x>$l AND x<$u }
} {2000 0 499500}
} {999 999 499500}
do_test analyze3-1.3.9 {
set l [expr int(0)]
set u [expr int(1100)]
sf_execsql { SELECT sum(y) FROM t3 WHERE x>$l AND x<$u }
} {2000 0 499500}
} {999 999 499500}
#-------------------------------------------------------------------------
# Test that the values of bound SQL variables may be used for the LIKE

10
test/analyze9.test

@ -566,7 +566,7 @@ foreach {tn schema} {
drop_all_tables
do_test 13.1 {
execsql {
CREATE TABLE t1(a, b, c);
CREATE TABLE t1(a, b, c, d);
CREATE INDEX i1 ON t1(a);
CREATE INDEX i2 ON t1(b, c);
}
@ -577,16 +577,16 @@ do_test 13.1 {
execsql ANALYZE
} {}
do_eqp_test 13.2.1 {
SELECT * FROM t1 WHERE a='abc' AND rowid<15 AND b<20
SELECT * FROM t1 WHERE a='abc' AND rowid<15 AND b<12
} {/SEARCH TABLE t1 USING INDEX i1/}
do_eqp_test 13.2.2 {
SELECT * FROM t1 WHERE a='abc' AND rowid<'15' AND b<20
SELECT * FROM t1 WHERE a='abc' AND rowid<'15' AND b<12
} {/SEARCH TABLE t1 USING INDEX i1/}
do_eqp_test 13.3.1 {
SELECT * FROM t1 WHERE a='abc' AND rowid<100 AND b<20
SELECT * FROM t1 WHERE a='abc' AND rowid<100 AND b<12
} {/SEARCH TABLE t1 USING INDEX i2/}
do_eqp_test 13.3.2 {
SELECT * FROM t1 WHERE a='abc' AND rowid<'100' AND b<20
SELECT * FROM t1 WHERE a='abc' AND rowid<'100' AND b<12
} {/SEARCH TABLE t1 USING INDEX i2/}
#-------------------------------------------------------------------------

2
test/autoindex1.test

@ -97,6 +97,8 @@ do_test autoindex1-210 {
PRAGMA automatic_index=ON;
ANALYZE;
UPDATE sqlite_stat1 SET stat='10000' WHERE tbl='t1';
-- Table t2 actually contains 8 rows.
UPDATE sqlite_stat1 SET stat='16' WHERE tbl='t2';
ANALYZE sqlite_master;
SELECT b, (SELECT d FROM t2 WHERE c=a) FROM t1;
}

251
test/cost.test Normal file

@ -0,0 +1,251 @@
# 2014-04-26
#
# 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.
#
#***********************************************************************
#
set testdir [file dirname $argv0]
source $testdir/tester.tcl
set testprefix cost
do_execsql_test 1.1 {
CREATE TABLE t3(id INTEGER PRIMARY KEY, b NOT NULL);
CREATE TABLE t4(c, d, e);
CREATE UNIQUE INDEX i3 ON t3(b);
CREATE UNIQUE INDEX i4 ON t4(c, d);
}
do_eqp_test 1.2 {
SELECT e FROM t3, t4 WHERE b=c ORDER BY b, d;
} {
0 0 0 {SCAN TABLE t3 USING COVERING INDEX i3}
0 1 1 {SEARCH TABLE t4 USING INDEX i4 (c=?)}
}
do_execsql_test 2.1 {
CREATE TABLE t1(a, b);
CREATE INDEX i1 ON t1(a);
}
# It is better to use an index for ORDER BY than sort externally, even
# if the index is a non-covering index.
do_eqp_test 2.2 {
SELECT * FROM t1 ORDER BY a;
} {
0 0 0 {SCAN TABLE t1 USING INDEX i1}
}
do_execsql_test 3.1 {
CREATE TABLE t5(a INTEGER PRIMARY KEY,b,c,d,e,f,g);
CREATE INDEX t5b ON t5(b);
CREATE INDEX t5c ON t5(c);
CREATE INDEX t5d ON t5(d);
CREATE INDEX t5e ON t5(e);
CREATE INDEX t5f ON t5(f);
CREATE INDEX t5g ON t5(g);
}
do_eqp_test 3.2 {
SELECT a FROM t5
WHERE b IS NULL OR c IS NULL OR d IS NULL
ORDER BY a;
} {
0 0 0 {SEARCH TABLE t5 USING INDEX t5b (b=?)}
0 0 0 {SEARCH TABLE t5 USING INDEX t5c (c=?)}
0 0 0 {SEARCH TABLE t5 USING INDEX t5d (d=?)}
0 0 0 {USE TEMP B-TREE FOR ORDER BY}
}
#-------------------------------------------------------------------------
# If there is no likelihood() or stat3 data, SQLite assumes that a closed
# range scan (e.g. one constrained by "col BETWEEN ? AND ?" constraint)
# visits 1/64 of the rows in a table.
#
# Note: 1/63 =~ 0.016
# Note: 1/65 =~ 0.015
#
reset_db
do_execsql_test 4.1 {
CREATE TABLE t1(a, b);
CREATE INDEX i1 ON t1(a);
CREATE INDEX i2 ON t1(b);
}
do_eqp_test 4.2 {
SELECT * FROM t1 WHERE likelihood(a=?, 0.014) AND b BETWEEN ? AND ?;
} {
0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a=?)}
}
do_eqp_test 4.3 {
SELECT * FROM t1 WHERE likelihood(a=?, 0.016) AND b BETWEEN ? AND ?;
} {
0 0 0 {SEARCH TABLE t1 USING INDEX i2 (b>? AND b<?)}
}
#-------------------------------------------------------------------------
#
reset_db
do_execsql_test 5.1 {
CREATE TABLE t2(x, y);
CREATE INDEX t2i1 ON t2(x);
}
do_eqp_test 5.2 {
SELECT * FROM t2 ORDER BY x, y;
} {
0 0 0 {SCAN TABLE t2 USING INDEX t2i1}
0 0 0 {USE TEMP B-TREE FOR RIGHT PART OF ORDER BY}
}
do_eqp_test 5.3 {
SELECT * FROM t2 WHERE x BETWEEN ? AND ? ORDER BY rowid;
} {
0 0 0 {SEARCH TABLE t2 USING INDEX t2i1 (x>? AND x<?)}
0 0 0 {USE TEMP B-TREE FOR ORDER BY}
}
# where7.test, where8.test:
#
do_execsql_test 6.1 {
CREATE TABLE t3(a INTEGER PRIMARY KEY, b, c);
CREATE INDEX t3i1 ON t3(b);
CREATE INDEX t3i2 ON t3(c);
}
do_eqp_test 6.2 {
SELECT a FROM t3 WHERE (b BETWEEN 2 AND 4) OR c=100 ORDER BY a
} {
0 0 0 {SEARCH TABLE t3 USING INDEX t3i1 (b>? AND b<?)}
0 0 0 {SEARCH TABLE t3 USING INDEX t3i2 (c=?)}
0 0 0 {USE TEMP B-TREE FOR ORDER BY}
}
#-------------------------------------------------------------------------
#
reset_db
do_execsql_test 7.1 {
CREATE TABLE t1(a INTEGER PRIMARY KEY,b,c,d,e,f,g);
CREATE INDEX t1b ON t1(b);
CREATE INDEX t1c ON t1(c);
CREATE INDEX t1d ON t1(d);
CREATE INDEX t1e ON t1(e);
CREATE INDEX t1f ON t1(f);
CREATE INDEX t1g ON t1(g);
}
do_eqp_test 7.2 {
SELECT a FROM t1
WHERE (b>=950 AND b<=1010) OR (b IS NULL AND c NOT NULL)
ORDER BY a
} {
0 0 0 {SEARCH TABLE t1 USING INDEX t1b (b>? AND b<?)}
0 0 0 {SEARCH TABLE t1 USING INDEX t1b (b=?)}
0 0 0 {USE TEMP B-TREE FOR ORDER BY}
}
do_eqp_test 7.3 {
SELECT rowid FROM t1
WHERE (+b IS NULL AND c NOT NULL AND d NOT NULL)
OR (b NOT NULL AND c IS NULL AND d NOT NULL)
OR (b NOT NULL AND c NOT NULL AND d IS NULL)
} {
0 0 0 {SCAN TABLE t1}
}
do_eqp_test 7.4 {
SELECT rowid FROM t1 WHERE (+b IS NULL AND c NOT NULL) OR c IS NULL
} {
0 0 0 {SCAN TABLE t1}
}
#-------------------------------------------------------------------------
#
reset_db
do_execsql_test 8.1 {
CREATE TABLE composer(
cid INTEGER PRIMARY KEY,
cname TEXT
);
CREATE TABLE album(
aid INTEGER PRIMARY KEY,
aname TEXT
);
CREATE TABLE track(
tid INTEGER PRIMARY KEY,
cid INTEGER REFERENCES composer,
aid INTEGER REFERENCES album,
title TEXT
);
CREATE INDEX track_i1 ON track(cid);
CREATE INDEX track_i2 ON track(aid);
}
do_eqp_test 8.2 {
SELECT DISTINCT aname
FROM album, composer, track
WHERE cname LIKE '%bach%'
AND unlikely(composer.cid=track.cid)
AND unlikely(album.aid=track.aid);
} {
0 0 2 {SCAN TABLE track}
0 1 0 {SEARCH TABLE album USING INTEGER PRIMARY KEY (rowid=?)}
0 2 1 {SEARCH TABLE composer USING INTEGER PRIMARY KEY (rowid=?)}
0 0 0 {USE TEMP B-TREE FOR DISTINCT}
}
#-------------------------------------------------------------------------
#
do_execsql_test 9.1 {
CREATE TABLE t1(
a,b,c,d,e, f,g,h,i,j,
k,l,m,n,o, p,q,r,s,t
);
CREATE INDEX i1 ON t1(k,l,m,n,o,p,q,r,s,t);
}
do_test 9.2 {
for {set i 0} {$i < 100} {incr i} {
execsql { INSERT INTO t1 DEFAULT VALUES }
}
execsql {
ANALYZE;
CREATE INDEX i2 ON t1(a,b,c,d,e,f,g,h,i,j);
}
} {}
set L [list a=? b=? c=? d=? e=? f=? g=? h=? i=? j=?]
foreach {tn nTerm nRow} {
1 1 10
2 2 9
3 3 8
4 4 7
5 5 6
6 6 5
7 7 5
8 8 5
9 9 5
10 10 5
} {
set w [join [lrange $L 0 [expr $nTerm-1]] " AND "]
set p1 [expr ($nRow-1) / 100.0]
set p2 [expr ($nRow+1) / 100.0]
set sql1 "SELECT * FROM t1 WHERE likelihood(k=?, $p1) AND $w"
set sql2 "SELECT * FROM t1 WHERE likelihood(k=?, $p2) AND $w"
do_eqp_test 9.3.$tn.1 $sql1 {/INDEX i1/}
do_eqp_test 9.3.$tn.2 $sql2 {/INDEX i2/}
}
finish_test

5
test/e_createtable.test

@ -884,9 +884,10 @@ do_execsql_test e_createtable-3.3.1 {
);
} {}
# EVIDENCE-OF: R-10288-43169 For the purposes of the DEFAULT clause, an
# EVIDENCE-OF: R-36381-62919 For the purposes of the DEFAULT clause, an
# expression is considered constant provided that it does not contain
# any sub-queries or string constants enclosed in double quotes.
# any sub-queries, column or table references, or string literals
# enclosed in double-quotes instead of single-quotes.
#
do_createtable_tests 3.4.1 -error {
default value of column [x] is not constant

11
test/e_fkey.test

@ -135,9 +135,9 @@ reset_db
#
# This also tests that foreign key constraints are disabled by default.
#
# EVIDENCE-OF: R-59578-04990 Foreign key constraints are disabled by
# EVIDENCE-OF: R-44261-39702 Foreign key constraints are disabled by
# default (for backwards compatibility), so must be enabled separately
# for each database connection separately.
# for each database connection.
#
drop_all_tables
do_test e_fkey-4.1 {
@ -163,9 +163,10 @@ do_test e_fkey-4.2 {
} {world}
#-------------------------------------------------------------------------
# EVIDENCE-OF: R-15278-54456 The application can can also use a PRAGMA
# EVIDENCE-OF: R-08013-37737 The application can also use a PRAGMA
# foreign_keys statement to determine if foreign keys are currently
# enabled.
#
# This also tests the example code in section 2 of foreignkeys.in.
#
@ -2990,8 +2991,8 @@ if {[clang_sanitize_address]==0} {
# The setting of the recursive_triggers pragma does not affect foreign
# key actions.
#
# EVIDENCE-OF: R-51769-32730 The PRAGMA recursive_triggers setting does
# not not affect the operation of foreign key actions.
# EVIDENCE-OF: R-44355-00270 The PRAGMA recursive_triggers setting does
# not affect the operation of foreign key actions.
#
foreach recursive_triggers_setting [list 0 1 ON OFF] {
drop_all_tables

12
test/eqp.test

@ -312,8 +312,8 @@ do_eqp_test 4.2.3 {
} {
1 0 0 {SCAN TABLE t1}
1 0 0 {USE TEMP B-TREE FOR ORDER BY}
2 0 0 {SCAN TABLE t2}
2 0 0 {USE TEMP B-TREE FOR ORDER BY}
2 0 0 {SCAN TABLE t2 USING INDEX t2i1}
2 0 0 {USE TEMP B-TREE FOR RIGHT PART OF ORDER BY}
0 0 0 {COMPOUND SUBQUERIES 1 AND 2 (UNION)}
}
do_eqp_test 4.2.4 {
@ -321,8 +321,8 @@ do_eqp_test 4.2.4 {
} {
1 0 0 {SCAN TABLE t1}
1 0 0 {USE TEMP B-TREE FOR ORDER BY}
2 0 0 {SCAN TABLE t2}
2 0 0 {USE TEMP B-TREE FOR ORDER BY}
2 0 0 {SCAN TABLE t2 USING INDEX t2i1}
2 0 0 {USE TEMP B-TREE FOR RIGHT PART OF ORDER BY}
0 0 0 {COMPOUND SUBQUERIES 1 AND 2 (INTERSECT)}
}
do_eqp_test 4.2.5 {
@ -330,8 +330,8 @@ do_eqp_test 4.2.5 {
} {
1 0 0 {SCAN TABLE t1}
1 0 0 {USE TEMP B-TREE FOR ORDER BY}
2 0 0 {SCAN TABLE t2}
2 0 0 {USE TEMP B-TREE FOR ORDER BY}
2 0 0 {SCAN TABLE t2 USING INDEX t2i1}
2 0 0 {USE TEMP B-TREE FOR RIGHT PART OF ORDER BY}
0 0 0 {COMPOUND SUBQUERIES 1 AND 2 (EXCEPT)}
}

5
test/index6.test

@ -145,11 +145,11 @@ do_test index6-2.1 {
execsql {
CREATE TABLE t2(a,b);
INSERT INTO t2(a,b) SELECT value, value FROM nums WHERE value<1000;
UPDATE t2 SET a=NULL WHERE b%5==0;
UPDATE t2 SET a=NULL WHERE b%2==0;
CREATE INDEX t2a1 ON t2(a) WHERE a IS NOT NULL;
SELECT count(*) FROM t2 WHERE a IS NOT NULL;
}
} {800}
} {500}
do_test index6-2.2 {
execsql {
EXPLAIN QUERY PLAN
@ -157,6 +157,7 @@ do_test index6-2.2 {
}
} {/.* TABLE t2 USING INDEX t2a1 .*/}
ifcapable stat4||stat3 {
execsql ANALYZE
do_test index6-2.3stat4 {
execsql {
EXPLAIN QUERY PLAN

4
test/orderby5.test

@ -80,12 +80,12 @@ do_execsql_test 2.1a {
EXPLAIN QUERY PLAN
SELECT * FROM t2 WHERE a=0 ORDER BY a, b, c;
} {~/B-TREE/}
do_execsql_test 2.1b {
EXPLAIN QUERY PLAN
SELECT * FROM t1 WHERE a=0 ORDER BY a, b, c;
SELECT * FROM t1 WHERE likelihood(a=0, 0.05) ORDER BY a, b, c;
} {/B-TREE/}
do_execsql_test 2.2 {
EXPLAIN QUERY PLAN
SELECT * FROM t1 WHERE +a=0 ORDER BY a, b, c;

106
test/orderby7.test Normal file

@ -0,0 +1,106 @@
# 2014-04-25
#
# 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 regression tests for SQLite library. The
# focus of this file is testing ORDER BY optimizations on joins
# that involve virtual tables.
#
set testdir [file dirname $argv0]
source $testdir/tester.tcl
set ::testprefix orderby7
ifcapable !fts3 {
finish_test
return
}
do_execsql_test 1.0 {
CREATE VIRTUAL TABLE fts USING fts3(content TEXT);
INSERT INTO fts(rowid,content)
VALUES(1,'this is a test of the fts3 virtual'),
(2,'table used as part of a join together'),
(3,'with the DISTINCT keyword. There was'),
(4,'a bug at one time (2013-06 through 2014-04)'),
(5,'that prevented this from working correctly.'),
(11,'a row that occurs twice'),
(12,'a row that occurs twice');
CREATE TABLE t1(x TEXT PRIMARY KEY, y);
INSERT OR IGNORE INTO t1 SELECT content, rowid+100 FROM fts;
} {}
do_execsql_test 1.1 {
SELECT DISTINCT fts.rowid, t1.y
FROM fts, t1
WHERE fts MATCH 'that twice'
AND content=x
ORDER BY y;
} {11 111 12 111}
do_execsql_test 1.2 {
SELECT DISTINCT fts.rowid, t1.x
FROM fts, t1
WHERE fts MATCH 'that twice'
AND content=x
ORDER BY 1;
} {11 {a row that occurs twice} 12 {a row that occurs twice}}
do_execsql_test 1.3 {
SELECT DISTINCT t1.x
FROM fts, t1
WHERE fts MATCH 'that twice'
AND content=x
ORDER BY 1;
} {{a row that occurs twice}}
do_execsql_test 1.4 {
SELECT t1.x
FROM fts, t1
WHERE fts MATCH 'that twice'
AND content=x
ORDER BY 1;
} {{a row that occurs twice} {a row that occurs twice}}
do_execsql_test 1.5 {
SELECT DISTINCT t1.x
FROM fts, t1
WHERE fts MATCH 'that twice'
AND content=x;
} {{a row that occurs twice}}
do_execsql_test 1.6 {
SELECT t1.x
FROM fts, t1
WHERE fts MATCH 'that twice'
AND content=x;
} {{a row that occurs twice} {a row that occurs twice}}
do_execsql_test 2.1 {
SELECT DISTINCT t1.x
FROM fts, t1
WHERE fts.rowid=11
AND content=x
ORDER BY fts.rowid;
} {{a row that occurs twice}}
do_execsql_test 2.2 {
SELECT DISTINCT t1.*
FROM fts, t1
WHERE fts.rowid=11
AND content=x
ORDER BY fts.rowid;
} {{a row that occurs twice} 111}
do_execsql_test 2.3 {
SELECT DISTINCT t1.*
FROM fts, t1
WHERE fts.rowid=11
AND content=x
ORDER BY t1.y
} {{a row that occurs twice} 111}
finish_test

65
test/selectA.test

@ -21,6 +21,7 @@
set testdir [file dirname $argv0]
source $testdir/tester.tcl
set testprefix selectA
ifcapable !compound {
finish_test
@ -1310,4 +1311,68 @@ do_execsql_test selectA-3.98 {
SELECT n FROM xyz ORDER BY +n;
} {MAD MAD+ MAD++}
#-------------------------------------------------------------------------
# At one point the following code exposed a temp register reuse problem.
#
proc f {args} { return 1 }
db func f f
do_execsql_test 4.1.1 {
CREATE TABLE t4(a, b);
CREATE TABLE t5(c, d);
INSERT INTO t5 VALUES(1, 'x');
INSERT INTO t5 VALUES(2, 'x');
INSERT INTO t4 VALUES(3, 'x');
INSERT INTO t4 VALUES(4, 'x');
CREATE INDEX i1 ON t4(a);
CREATE INDEX i2 ON t5(c);
}
do_eqp_test 4.1.2 {
SELECT c, d FROM t5
UNION ALL
SELECT a, b FROM t4 WHERE f()==f()
ORDER BY 1,2
} {
1 0 0 {SCAN TABLE t5 USING INDEX i2}
1 0 0 {USE TEMP B-TREE FOR RIGHT PART OF ORDER BY}
2 0 0 {SCAN TABLE t4 USING INDEX i1}
2 0 0 {USE TEMP B-TREE FOR RIGHT PART OF ORDER BY}
0 0 0 {COMPOUND SUBQUERIES 1 AND 2 (UNION ALL)}
}
do_execsql_test 4.1.3 {
SELECT c, d FROM t5
UNION ALL
SELECT a, b FROM t4 WHERE f()==f()
ORDER BY 1,2
} {
1 x 2 x 3 x 4 x
}
do_execsql_test 4.2.1 {
CREATE TABLE t6(a, b);
CREATE TABLE t7(c, d);
INSERT INTO t7 VALUES(2, 9);
INSERT INTO t6 VALUES(3, 0);
INSERT INTO t6 VALUES(4, 1);
INSERT INTO t7 VALUES(5, 6);
INSERT INTO t6 VALUES(6, 0);
INSERT INTO t7 VALUES(7, 6);
CREATE INDEX i6 ON t6(a);
CREATE INDEX i7 ON t7(c);
}
do_execsql_test 4.2.2 {
SELECT c, f(d,c,d,c,d) FROM t7
UNION ALL
SELECT a, b FROM t6
ORDER BY 1,2
} {/2 . 3 . 4 . 5 . 6 . 7 ./}
finish_test

57
test/show_speedtest1_rtree.tcl Normal file

@ -0,0 +1,57 @@
#!/usr/bin/tclsh
#
# This script displays the field of rectangles used by --testset rtree
# of speedtest1. Run this script as follows:
#
# rm test.db
# ./speedtest1 --testset rtree --size 25 test.db
# sqlite3 --separator ' ' test.db 'SELECT * FROM rt1' >data.txt
# wish show_speedtest1_rtree.tcl
#
# The filename "data.txt" is hard coded into this script and so that name
# must be used on lines 3 and 4 above. Elsewhere, different filenames can
# be used. The --size N parameter can be adjusted as desired.
#
package require Tk
set f [open data.txt rb]
set data [read $f]
close $f
canvas .c
frame .b
button .b.b1 -text X-Y -command refill-xy
button .b.b2 -text X-Z -command refill-xz
button .b.b3 -text Y-Z -command refill-yz
pack .b.b1 .b.b2 .b.b3 -side left
pack .c -side top -fill both -expand 1
pack .b -side top
proc resize_canvas_to_fit {} {
foreach {x0 y0 x1 y1} [.c bbox all] break
set w [expr {$x1-$x0}]
set h [expr {$y1-$y0}]
.c config -width $w -height $h
}
proc refill-xy {} {
.c delete all
foreach {id x0 x1 y0 y1 z0 z1} $::data {
.c create rectangle $x0 $y0 $x1 $y1
}
.c scale all 0 0 0.05 0.05
resize_canvas_to_fit
}
proc refill-xz {} {
.c delete all
foreach {id x0 x1 y0 y1 z0 z1} $::data {
.c create rectangle $x0 $z0 $x1 $z1
}
.c scale all 0 0 0.05 0.05
resize_canvas_to_fit
}
proc refill-yz {} {
.c delete all
foreach {id x0 x1 y0 y1 z0 z1} $::data {
.c create rectangle $y0 $z0 $y1 $z1
}
.c scale all 0 0 0.05 0.05
resize_canvas_to_fit
}
refill-xy

1
test/skipscan2.test

@ -74,6 +74,7 @@ do_execsql_test skipscan2-1.4 {
-- of a skip-scan. So make a manual adjustment to the stat1 table
-- to make it seem like there are many more.
UPDATE sqlite_stat1 SET stat='10000 5000 20' WHERE idx='people_idx1';
UPDATE sqlite_stat1 SET stat='10000 1' WHERE idx='sqlite_autoindex_people_1';
ANALYZE sqlite_master;
}
db cache flush

186
test/speedtest1.c

@ -30,6 +30,7 @@ static const char zHelp[] =
" --threads N Use up to N threads for sorting\n"
" --utf16be Set text encoding to UTF-16BE\n"
" --utf16le Set text encoding to UTF-16LE\n"
" --verify Run additional verification steps.\n"
" --without-rowid Use WITHOUT ROWID where appropriate\n"
;
@ -52,6 +53,7 @@ static struct Global {
int bReprepare; /* True to reprepare the SQL on each rerun */
int bSqlOnly; /* True to print the SQL once only */
int bExplain; /* Print SQL with EXPLAIN prefix */
int bVerify; /* Try to verify that results are correct */
int szTest; /* Scale factor for test iterations */
const char *zWR; /* Might be WITHOUT ROWID */
const char *zNN; /* Might be NOT NULL */
@ -932,6 +934,183 @@ void testset_cte(void){
}
/* Generate two numbers between 1 and mx. The first number is less than
** the second. Usually the numbers are near each other but can sometimes
** be far apart.
*/
static void twoCoords(
int p1, int p2, /* Parameters adjusting sizes */
unsigned mx, /* Range of 1..mx */
unsigned *pX0, unsigned *pX1 /* OUT: write results here */
){
unsigned d, x0, x1, span;
span = mx/100 + 1;
if( speedtest1_random()%3==0 ) span *= p1;
if( speedtest1_random()%p2==0 ) span = mx/2;
d = speedtest1_random()%span + 1;
x0 = speedtest1_random()%(mx-d) + 1;
x1 = x0 + d;
*pX0 = x0;
*pX1 = x1;
}
/* The following routine is an R-Tree geometry callback. It returns
** true if the object overlaps a slice on the Y coordinate between the
** two values given as arguments. In other words
**
** SELECT count(*) FROM rt1 WHERE id MATCH xslice(10,20);
**
** Is the same as saying:
**
** SELECT count(*) FROM rt1 WHERE y1>=10 AND y0<=20;
*/
static int xsliceGeometryCallback(
sqlite3_rtree_geometry *p,
int nCoord,
double *aCoord,
int *pRes
){
*pRes = aCoord[3]>=p->aParam[0] && aCoord[2]<=p->aParam[1];
return SQLITE_OK;
}
/*
** A testset for the R-Tree virtual table
*/
void testset_rtree(int p1, int p2){
unsigned i, n;
unsigned mxCoord;
unsigned x0, x1, y0, y1, z0, z1;
unsigned iStep;
int *aCheck = sqlite3_malloc( sizeof(int)*g.szTest*100 );
mxCoord = 15000;
n = g.szTest*100;
speedtest1_begin_test(100, "%d INSERTs into an r-tree", n);
speedtest1_exec("BEGIN");
speedtest1_exec("CREATE VIRTUAL TABLE rt1 USING rtree(id,x0,x1,y0,y1,z0,z1)");
speedtest1_prepare("INSERT INTO rt1(id,x0,x1,y0,y1,z0,z1)"
"VALUES(?1,?2,?3,?4,?5,?6,?7)");
for(i=1; i<=n; i++){
twoCoords(p1, p2, mxCoord, &x0, &x1);
twoCoords(p1, p2, mxCoord, &y0, &y1);
twoCoords(p1, p2, mxCoord, &z0, &z1);
sqlite3_bind_int(g.pStmt, 1, i);
sqlite3_bind_int(g.pStmt, 2, x0);
sqlite3_bind_int(g.pStmt, 3, x1);
sqlite3_bind_int(g.pStmt, 4, y0);
sqlite3_bind_int(g.pStmt, 5, y1);
sqlite3_bind_int(g.pStmt, 6, z0);
sqlite3_bind_int(g.pStmt, 7, z1);
speedtest1_run();
}
speedtest1_exec("COMMIT");
speedtest1_end_test();
speedtest1_begin_test(101, "Copy from rtree to a regular table");
speedtest1_exec("CREATE TABLE t1(id INTEGER PRIMARY KEY,x0,x1,y0,y1,z0,z1)");
speedtest1_exec("INSERT INTO t1 SELECT * FROM rt1");
speedtest1_end_test();
n = g.szTest*20;
speedtest1_begin_test(110, "%d one-dimensional intersect slice queries", n);
speedtest1_prepare("SELECT count(*) FROM rt1 WHERE x0>=?1 AND x1<=?2");
iStep = mxCoord/n;
for(i=0; i<n; i++){
sqlite3_bind_int(g.pStmt, 1, i*iStep);
sqlite3_bind_int(g.pStmt, 2, (i+1)*iStep);
speedtest1_run();
aCheck[i] = atoi(g.zResult);
}
speedtest1_end_test();
if( g.bVerify ){
n = g.szTest*20;
speedtest1_begin_test(111, "Verify result from 1-D intersect slice queries");
speedtest1_prepare("SELECT count(*) FROM t1 WHERE x0>=?1 AND x1<=?2");
iStep = mxCoord/n;
for(i=0; i<n; i++){
sqlite3_bind_int(g.pStmt, 1, i*iStep);
sqlite3_bind_int(g.pStmt, 2, (i+1)*iStep);
speedtest1_run();
if( aCheck[i]!=atoi(g.zResult) ){
fatal_error("Count disagree step %d: %d..%d. %d vs %d",
i, i*iStep, (i+1)*iStep, aCheck[i], atoi(g.zResult));
}
}
speedtest1_end_test();
}
n = g.szTest*20;
speedtest1_begin_test(120, "%d one-dimensional overlap slice queries", n);
speedtest1_prepare("SELECT count(*) FROM rt1 WHERE y1>=?1 AND y0<=?2");
iStep = mxCoord/n;
for(i=0; i<n; i++){
sqlite3_bind_int(g.pStmt, 1, i*iStep);
sqlite3_bind_int(g.pStmt, 2, (i+1)*iStep);
speedtest1_run();
aCheck[i] = atoi(g.zResult);
}
speedtest1_end_test();
if( g.bVerify ){
n = g.szTest*20;
speedtest1_begin_test(121, "Verify result from 1-D overlap slice queries");
speedtest1_prepare("SELECT count(*) FROM t1 WHERE y1>=?1 AND y0<=?2");
iStep = mxCoord/n;
for(i=0; i<n; i++){
sqlite3_bind_int(g.pStmt, 1, i*iStep);
sqlite3_bind_int(g.pStmt, 2, (i+1)*iStep);
speedtest1_run();
if( aCheck[i]!=atoi(g.zResult) ){
fatal_error("Count disagree step %d: %d..%d. %d vs %d",
i, i*iStep, (i+1)*iStep, aCheck[i], atoi(g.zResult));
}
}
speedtest1_end_test();
}
n = g.szTest*20;
speedtest1_begin_test(125, "%d custom geometry callback queries", n);
sqlite3_rtree_geometry_callback(g.db, "xslice", xsliceGeometryCallback, 0);
speedtest1_prepare("SELECT count(*) FROM rt1 WHERE id MATCH xslice(?1,?2)");
iStep = mxCoord/n;
for(i=0; i<n; i++){
sqlite3_bind_int(g.pStmt, 1, i*iStep);
sqlite3_bind_int(g.pStmt, 2, (i+1)*iStep);
speedtest1_run();
if( aCheck[i]!=atoi(g.zResult) ){
fatal_error("Count disagree step %d: %d..%d. %d vs %d",
i, i*iStep, (i+1)*iStep, aCheck[i], atoi(g.zResult));
}
}
speedtest1_end_test();
n = g.szTest*80;
speedtest1_begin_test(130, "%d three-dimensional intersect box queries", n);
speedtest1_prepare("SELECT count(*) FROM rt1 WHERE x1>=?1 AND x0<=?2"
" AND y1>=?1 AND y0<=?2 AND z1>=?1 AND z0<=?2");
iStep = mxCoord/n;
for(i=0; i<n; i++){
sqlite3_bind_int(g.pStmt, 1, i*iStep);
sqlite3_bind_int(g.pStmt, 2, (i+1)*iStep);
speedtest1_run();
aCheck[i] = atoi(g.zResult);
}
speedtest1_end_test();
n = g.szTest*100;
speedtest1_begin_test(140, "%d rowid queries", n);
speedtest1_prepare("SELECT * FROM rt1 WHERE id=?1");
for(i=1; i<=n; i++){
sqlite3_bind_int(g.pStmt, 1, i);
speedtest1_run();
}
speedtest1_end_test();
}
/*
** A testset used for debugging speedtest1 itself.
*/
@ -1055,6 +1234,8 @@ int main(int argc, char **argv){
zEncoding = "utf16le";
}else if( strcmp(z,"utf16be")==0 ){
zEncoding = "utf16be";
}else if( strcmp(z,"verify")==0 ){
g.bVerify = 1;
}else if( strcmp(z,"without-rowid")==0 ){
g.zWR = "WITHOUT ROWID";
g.zPK = "PRIMARY KEY";
@ -1151,8 +1332,11 @@ int main(int argc, char **argv){
testset_debug1();
}else if( strcmp(zTSet,"cte")==0 ){
testset_cte();
}else if( strcmp(zTSet,"rtree")==0 ){
testset_rtree(6, 147);
}else{
fatal_error("unknown testset: \"%s\"\n", zTSet);
fatal_error("unknown testset: \"%s\"\nChoices: main debug1 cte rtree\n",
zTSet);
}
speedtest1_final();

53
test/tkt-f67b41381a.test Normal file

@ -0,0 +1,53 @@
# 2014 April 26
#
# 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.
#
#***********************************************************************
# Test that ticket f67b41381a has been resolved.
#
set testdir [file dirname $argv0]
source $testdir/tester.tcl
set testprefix tkt-f67b41381a
do_execsql_test 1.0 {
CREATE TABLE t1(a);
INSERT INTO t1 VALUES(1);
ALTER TABLE t1 ADD COLUMN b DEFAULT 2;
CREATE TABLE t2(a, b);
INSERT INTO t2 SELECT * FROM t1;
SELECT * FROM t2;
} {1 2}
db cache size 0
foreach {tn tbls xfer} {
1 { CREATE TABLE t1(a, b); CREATE TABLE t2(a, b) } 1
2 { CREATE TABLE t1(a, b DEFAULT 'x'); CREATE TABLE t2(a, b) } 0
3 { CREATE TABLE t1(a, b DEFAULT 'x'); CREATE TABLE t2(a, b DEFAULT 'x') } 1
4 { CREATE TABLE t1(a, b DEFAULT NULL); CREATE TABLE t2(a, b) } 0
5 { CREATE TABLE t1(a DEFAULT 2, b); CREATE TABLE t2(a DEFAULT 1, b) } 1
6 { CREATE TABLE t1(a DEFAULT 1, b); CREATE TABLE t2(a DEFAULT 1, b) } 1
7 { CREATE TABLE t1(a DEFAULT 1, b DEFAULT 1);
CREATE TABLE t2(a DEFAULT 3, b DEFAULT 1) } 1
8 { CREATE TABLE t1(a DEFAULT 1, b DEFAULT 1);
CREATE TABLE t2(a DEFAULT 3, b DEFAULT 3) } 0
} {
execsql { DROP TABLE t1; DROP TABLE t2 }
execsql $tbls
set res 1
db eval { EXPLAIN INSERT INTO t1 SELECT * FROM t2 } {
if {$opcode == "Column"} { set res 0 }
}
do_test 2.$tn [list set res] $xfer
}
finish_test

2
test/unordered.test

@ -42,7 +42,7 @@ foreach idxmode {ordered unordered} {
1 "SELECT * FROM t1 ORDER BY a"
{0 0 0 {SCAN TABLE t1 USING INDEX i1}}
{0 0 0 {SCAN TABLE t1} 0 0 0 {USE TEMP B-TREE FOR ORDER BY}}
2 "SELECT * FROM t1 WHERE a >?"
2 "SELECT * FROM t1 WHERE a > 100"
{0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a>?)}}
{0 0 0 {SCAN TABLE t1}}
3 "SELECT * FROM t1 WHERE a = ? ORDER BY rowid"

8
test/wal2.test

@ -811,7 +811,13 @@ do_test wal2-7.1.1 {
do_test wal2-7.1.2 {
forcecopy test.db test2.db
forcecopy test.db-wal test2.db-wal
hexio_write test2.db-wal 48 FF
# The first 32 bytes of the WAL file contain the WAL header. Offset 48
# is the first byte of the checksum for the first frame in the WAL.
# The following three lines replaces the contents of that byte with
# a different value.
set newval FF
if {$newval == [hexio_read test2.db-wal 48 1]} { set newval 00 }
hexio_write test2.db-wal 48 $newval
} {1}
do_test wal2-7.1.3 {
sqlite3 db2 test2.db

3
test/where3.test

@ -231,6 +231,7 @@ do_execsql_test where3-3.0 {
CREATE TABLE t301(a INTEGER PRIMARY KEY,b,c);
CREATE INDEX t301c ON t301(c);
INSERT INTO t301 VALUES(1,2,3);
INSERT INTO t301 VALUES(2,2,3);
CREATE TABLE t302(x, y);
INSERT INTO t302 VALUES(4,5);
ANALYZE;
@ -251,7 +252,7 @@ do_execsql_test where3-3.2 {
} {}
do_execsql_test where3-3.3 {
SELECT * FROM t301 WHERE c=3 AND a IS NOT NULL;
} {1 2 3}
} {1 2 3 2 2 3}
if 0 { # Query planner no longer does this
# Verify that when there are multiple tables in a join which must be

42
test/whereG.test

@ -14,6 +14,7 @@
set testdir [file dirname $argv0]
source $testdir/tester.tcl
set testprefix whereG
do_execsql_test whereG-1.0 {
CREATE TABLE composer(
@ -179,5 +180,46 @@ do_execsql_test whereG-4.0 {
ORDER BY x;
} {right}
#-------------------------------------------------------------------------
# Test that likelihood() specifications on indexed terms are taken into
# account by various forms of loops.
#
# 5.1.*: open ended range scans
# 5.2.*: skip-scans
#
reset_db
do_execsql_test 5.1 {
CREATE TABLE t1(a, b, c);
CREATE INDEX i1 ON t1(a, b);
}
do_eqp_test 5.1.2 {
SELECT * FROM t1 WHERE a>?
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a>?)}}
do_eqp_test 5.1.3 {
SELECT * FROM t1 WHERE likelihood(a>?, 0.9)
} {0 0 0 {SCAN TABLE t1}}
do_test 5.2 {
for {set i 0} {$i < 100} {incr i} {
execsql { INSERT INTO t1 VALUES('abc', $i, $i); }
}
execsql { INSERT INTO t1 SELECT 'def', b, c FROM t1; }
execsql { ANALYZE }
} {}
do_eqp_test 5.2.2 {
SELECT * FROM t1 WHERE likelihood(b>?, 0.01)
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (ANY(a) AND b>?)}}
do_eqp_test 5.2.3 {
SELECT * FROM t1 WHERE likelihood(b>?, 0.9)
} {0 0 0 {SCAN TABLE t1}}
do_eqp_test 5.3.1 {
SELECT * FROM t1 WHERE a=?
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a=?)}}
do_eqp_test 5.3.2 {
SELECT * FROM t1 WHERE likelihood(a=?, 0.9)
} {0 0 0 {SCAN TABLE t1}}
finish_test

7
tool/logest.c

@ -83,7 +83,8 @@ static LogEst logEstFromDouble(double x){
LogEst e;
assert( sizeof(x)==8 && sizeof(a)==8 );
if( x<=0.0 ) return -32768;
if( x<1.0 ) return -logEstFromDouble(1/x);
if( x<0.01 ) return -logEstFromDouble(1.0/x);
if( x<1.0 ) return logEstFromDouble(100.0*x) - 66;
if( x<1024.0 ) return logEstFromInteger((sqlite3_uint64)(1024.0*x)) - 100;
if( x<=2000000000.0 ) return logEstFromInteger((sqlite3_uint64)x);
memcpy(&a, &x, 8);
@ -156,8 +157,10 @@ int main(int argc, char **argv){
}
}
for(i=n-1; i>=0; i--){
if( a[i]<0 ){
if( a[i]<-40 ){
printf("%5d (%f)\n", a[i], 1.0/(double)logEstToInt(-a[i]));
}else if( a[i]<10 ){
printf("%5d (%f)\n", a[i], logEstToInt(a[i]+100)/1024.0);
}else{
sqlite3_uint64 x = logEstToInt(a[i]+100)*100/1024;
printf("%5d (%lld.%02lld)\n", a[i], x/100, x%100);