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从上游同步代码
2023-06-27 18:34:42 +08:00
# 2021 September 13
#
# 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.
#
#***********************************************************************
#
# The focus of this file is testing the r-tree extension.
#
if {![info exists testdir]} {
set testdir [file join [file dirname [info script]] .. .. test]
}
source [file join [file dirname [info script]] rtree_util.tcl]
source $testdir/tester.tcl
set testprefix rtreedoc
ifcapable !rtree {
finish_test
return
}
# This command returns the number of columns in table $tbl within the
# database opened by database handle $db
proc column_count {db tbl} {
set nCol 0
$db eval "PRAGMA table_info = $tbl" { incr nCol }
return $nCol
}
proc column_name_list {db tbl} {
set lCol [list]
$db eval "PRAGMA table_info = $tbl" {
lappend lCol $name
}
return $lCol
}
unset -nocomplain res
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 3 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-1
# EVIDENCE-OF: R-15060-13876 A 1-dimensional R*Tree thus has 3 columns.
do_execsql_test 1.1.1 { CREATE VIRTUAL TABLE rt1 USING rtree(id, x1,x2) }
do_test 1.1.2 { column_count db rt1 } 3
# EVIDENCE-OF: R-19353-19546 A 2-dimensional R*Tree has 5 columns.
do_execsql_test 1.2.1 { CREATE VIRTUAL TABLE rt2 USING rtree(id,x1,x2, y1,y2) }
do_test 1.2.2 { column_count db rt2 } 5
# EVIDENCE-OF: R-13615-19528 A 3-dimensional R*Tree has 7 columns.
do_execsql_test 1.3.1 {
CREATE VIRTUAL TABLE rt3 USING rtree(id, x1,x2, y1,y2, z1,z2)
}
do_test 1.3.2 { column_count db rt3 } 7
# EVIDENCE-OF: R-53479-41922 A 4-dimensional R*Tree has 9 columns.
do_execsql_test 1.4.1 {
CREATE VIRTUAL TABLE rt4 USING rtree(id, x1,x2, y1,y2, z1,z2, v1,v2)
}
do_test 1.4.2 { column_count db rt4 } 9
# EVIDENCE-OF: R-13981-28768 And a 5-dimensional R*Tree has 11 columns.
do_execsql_test 1.5.1 {
CREATE VIRTUAL TABLE rt5 USING rtree(id, x1,x2, y1,y2, z1,z2, v1,v2, w1,w2)
}
do_test 1.5.2 { column_count db rt5 } 11
# Attempt to create r-tree tables with 6 and 7 dimensions.
#
# EVIDENCE-OF: R-61533-25862 The SQLite R*Tree implementation does not
# support R*Trees wider than 5 dimensions.
do_catchsql_test 2.1.1 {
CREATE VIRTUAL TABLE rt6 USING rtree(
id, x1,x2, y1,y2, z1,z2, v1,v2, w1,w2, a1,a2
)
} {1 {Too many columns for an rtree table}}
do_catchsql_test 2.1.2 {
CREATE VIRTUAL TABLE rt6 USING rtree(
id, x1,x2, y1,y2, z1,z2, v1,v2, w1,w2, a1,a2, b1, b2
)
} {1 {Too many columns for an rtree table}}
# Attempt to create r-tree tables with no columns, a single column, or
# an even number of columns. This and the tests above establish that:
#
# EVIDENCE-OF: R-16717-50504 Each R*Tree index is a virtual table with
# an odd number of columns between 3 and 11.
foreach {tn cols err} {
1 "" "Too few columns for an rtree table"
2 "x" "Too few columns for an rtree table"
3 "x,y" "Too few columns for an rtree table"
4 "a,b,c,d" "Wrong number of columns for an rtree table"
5 "a,b,c,d,e,f" "Wrong number of columns for an rtree table"
6 "a,b,c,d,e,f,g,h" "Wrong number of columns for an rtree table"
7 "a,b,c,d,e,f,g,h,i,j" "Wrong number of columns for an rtree table"
8 "a,b,c,d,e,f,g,h,i,j,k,l" "Too many columns for an rtree table"
} {
do_catchsql_test 3.$tn "
CREATE VIRTUAL TABLE xyz USING rtree($cols)
" [list 1 $err]
}
# EVIDENCE-OF: R-17874-21123 The first column of an SQLite R*Tree is
# similar to an integer primary key column of a normal SQLite table.
#
# EVIDENCE-OF: R-46619-65417 The first column is always a 64-bit signed
# integer primary key.
#
# EVIDENCE-OF: R-46866-24036 It may only store a 64-bit signed integer
# value.
#
# EVIDENCE-OF: R-00250-64843 If an attempt is made to insert any other
# non-integer value into this column, the r-tree module silently
# converts it to an integer before writing it into the database.
#
do_execsql_test 4.0 { CREATE VIRTUAL TABLE rt USING rtree(id, x1, x2) }
foreach {tn val res} {
1 10 10
2 10.6 10
3 10.99 10
4 '123' 123
5 X'313233' 123
6 -10 -10
7 9223372036854775807 9223372036854775807
8 -9223372036854775808 -9223372036854775808
9 '9223372036854775807' 9223372036854775807
10 '-9223372036854775808' -9223372036854775808
11 'hello+world' 0
} {
do_execsql_test 4.$tn.1 "
DELETE FROM rt;
INSERT INTO rt VALUES($val, 10, 20);
"
do_execsql_test 4.$tn.2 {
SELECT typeof(id), id FROM rt
} [list integer $res]
}
# EVIDENCE-OF: R-15544-29079 Inserting a NULL value into this column
# causes SQLite to automatically generate a new unique primary key
# value.
do_execsql_test 5.1 {
DELETE FROM rt;
INSERT INTO rt VALUES(100, 1, 2);
INSERT INTO rt VALUES(NULL, 1, 2);
}
do_execsql_test 5.2 { SELECT id FROM rt } {100 101}
do_execsql_test 5.3 {
INSERT INTO rt VALUES(9223372036854775807, 1, 2);
INSERT INTO rt VALUES(NULL, 1, 2);
}
do_execsql_test 5.4 {
SELECT count(*) FROM rt;
} 4
do_execsql_test 5.5 {
SELECT id IN(100, 101, 9223372036854775807) FROM rt ORDER BY 1;
} {0 1 1 1}
# EVIDENCE-OF: R-64317-38978 The other columns are pairs, one pair per
# dimension, containing the minimum and maximum values for that
# dimension, respectively.
#
# Show this by observing that attempts to insert rows with max>min fail.
#
do_execsql_test 6.1 {
CREATE VIRTUAL TABLE rtF USING rtree(id, x1,x2, y1,y2);
CREATE VIRTUAL TABLE rtI USING rtree_i32(id, x1,x2, y1,y2, z1,z2);
}
foreach {tn x1 x2 y1 y2 ok} {
1 10.3 20.1 30.9 40.2 1
2 10.3 20.1 40.2 30.9 0
3 10.3 30.9 20.1 40.2 1
4 20.1 10.3 30.9 40.2 0
} {
do_test 6.2.$tn {
catch { db eval { INSERT INTO rtF VALUES(NULL, $x1, $x2, $y1, $y2) } }
} [expr $ok==0]
}
foreach {tn x1 x2 y1 y2 z1 z2 ok} {
1 10 20 30 40 50 60 1
2 10 20 30 40 60 50 0
3 10 20 30 50 40 60 1
4 10 20 40 30 50 60 0
5 10 30 20 40 50 60 1
6 20 10 30 40 50 60 0
} {
do_test 6.3.$tn {
catch { db eval { INSERT INTO rtI VALUES(NULL,$x1,$x2,$y1,$y2,$z1,$z2) } }
} [expr $ok==0]
}
# EVIDENCE-OF: R-08054-15429 The min/max-value pair columns are stored
# as 32-bit floating point values for "rtree" virtual tables or as
# 32-bit signed integers in "rtree_i32" virtual tables.
#
# Show this by showing that large values are rounded in ways consistent
# with those two 32-bit types.
do_execsql_test 7.1 {
DELETE FROM rtI;
INSERT INTO rtI VALUES(
0, -2000000000, 2000000000, -5000000000, 5000000000,
-1000000000000, 10000000000000
);
SELECT * FROM rtI;
} {
0 -2000000000 2000000000 -705032704 705032704 727379968 1316134912
}
do_execsql_test 7.2 {
DELETE FROM rtF;
INSERT INTO rtF VALUES(
0, -2000000000, 2000000000,
-1000000000000, 10000000000000
);
SELECT * FROM rtF;
} {
0 -2000000000.0 2000000000.0 -1000000126976.0 10000000876544.0
}
# EVIDENCE-OF: R-47371-54529 Unlike regular SQLite tables which can
# store data in a variety of datatypes and formats, the R*Tree rigidly
# enforce these storage types.
#
# EVIDENCE-OF: R-39153-14977 If any other type of value is inserted into
# such a column, the r-tree module silently converts it to the required
# type before writing the new record to the database.
do_execsql_test 8.1 {
DELETE FROM rtI;
INSERT INTO rtI VALUES(
1, 'hello world', X'616263', NULL, 44.5, 1000, 9999.9999
);
SELECT * FROM rtI;
} {
1 0 0 0 44 1000 9999
}
do_execsql_test 8.2 {
SELECT
typeof(x1), typeof(x2), typeof(y1), typeof(y2), typeof(z1), typeof(z2)
FROM rtI
} {integer integer integer integer integer integer}
do_execsql_test 8.3 {
DELETE FROM rtF;
INSERT INTO rtF VALUES(
1, 'hello world', X'616263', NULL, 44
);
SELECT * FROM rtF;
} {
1 0.0 0.0 0.0 44.0
}
do_execsql_test 8.4 {
SELECT
typeof(x1), typeof(x2), typeof(y1), typeof(y2)
FROM rtF
} {real real real real}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 3.1 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-2
reset_db
foreach {tn name clist} {
1 t1 "id x1 x2"
2 t2 "id x1 x2 y1 y2 z1 z2"
} {
# EVIDENCE-OF: R-15142-18077 A new R*Tree index is created as follows:
# CREATE VIRTUAL TABLE <name> USING rtree(<column-names>);
do_execsql_test 1.$tn.1 "
CREATE VIRTUAL TABLE $name USING rtree([join $clist ,])
"
# EVIDENCE-OF: R-51698-09302 The <name> is the name your
# application chooses for the R*Tree index and <column-names> is a
# comma separated list of between 3 and 11 columns.
do_test 1.$tn.2 { column_name_list db $name } [list {*}$clist]
# EVIDENCE-OF: R-50130-53472 The virtual <name> table creates
# three shadow tables to actually store its content.
do_execsql_test 1.$tn.3 {
SELECT count(*) FROM sqlite_schema
} [expr 1+3]
# EVIDENCE-OF: R-45256-35998 The names of these shadow tables are:
# <name>_node <name>_rowid <name>_parent
do_execsql_test 1.$tn.4 {
SELECT name FROM sqlite_schema WHERE rootpage>0 ORDER BY 1
} [list ${name}_node ${name}_parent ${name}_rowid]
do_execsql_test 1.$tn.5 "DROP TABLE $name"
}
# EVIDENCE-OF: R-11241-54478 As an example, consider creating a
# two-dimensional R*Tree index for use in spatial queries: CREATE
# VIRTUAL TABLE demo_index USING rtree( id, -- Integer primary key minX,
# maxX, -- Minimum and maximum X coordinate minY, maxY -- Minimum and
# maximum Y coordinate );
do_execsql_test 2.0 {
CREATE VIRTUAL TABLE demo_index USING rtree(
id, -- Integer primary key
minX, maxX, -- Minimum and maximum X coordinate
minY, maxY -- Minimum and maximum Y coordinate
);
INSERT INTO demo_index VALUES(1,2,3,4,5);
INSERT INTO demo_index VALUES(6,7,8,9,10);
}
# EVIDENCE-OF: R-02287-33529 The shadow tables are ordinary SQLite data
# tables.
#
# Ordinary tables. With ordinary sqlite_schema entries.
do_execsql_test 2.1 {
SELECT type, name, sql FROM sqlite_schema WHERE sql NOT LIKE '%virtual%'
} {
table demo_index_rowid
{CREATE TABLE "demo_index_rowid"(rowid INTEGER PRIMARY KEY,nodeno)}
table demo_index_node
{CREATE TABLE "demo_index_node"(nodeno INTEGER PRIMARY KEY,data)}
table demo_index_parent
{CREATE TABLE "demo_index_parent"(nodeno INTEGER PRIMARY KEY,parentnode)}
}
# EVIDENCE-OF: R-10863-13089 You can query them directly if you like,
# though this unlikely to reveal anything particularly useful.
#
# Querying:
do_execsql_test 2.2 {
SELECT count(*) FROM demo_index_node;
SELECT count(*) FROM demo_index_rowid;
SELECT count(*) FROM demo_index_parent;
} {1 2 0}
# EVIDENCE-OF: R-05650-46070 And you can UPDATE, DELETE, INSERT or even
# DROP the shadow tables, though doing so will corrupt your R*Tree
# index.
do_execsql_test 2.3 {
DELETE FROM demo_index_rowid;
INSERT INTO demo_index_parent VALUES(2, 3);
UPDATE demo_index_node SET data = 'hello world'
}
do_catchsql_test 2.4 {
SELECT * FROM demo_index WHERE minX>10 AND maxX<30
} {1 {database disk image is malformed}}
do_execsql_test 2.5 {
DROP TABLE demo_index_rowid
}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 3.1.1 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-3
reset_db
# EVIDENCE-OF: R-44253-50720 In the argments to "rtree" in the CREATE
# VIRTUAL TABLE statement, the names of the columns are taken from the
# first token of each argument. All subsequent tokens within each
# argument are silently ignored.
#
foreach {tn cols lCol} {
1 {(id TEXT, x1 TEXT, x2 TEXT, y1 TEXT, y2 TEXT)} {id x1 x2 y1 y2}
2 {(id TEXT, x1 UNIQUE, x2 TEXT, y1 NOT NULL, y2 TEXT)} {id x1 x2 y1 y2}
3 {(id, x1 DEFAULT 4, x2 TEXT, y1 NOT NULL, y2 TEXT)} {id x1 x2 y1 y2}
} {
do_execsql_test 1.$tn.1 " CREATE VIRTUAL TABLE abc USING rtree $cols "
do_test 1.$tn.2 { column_name_list db abc } $lCol
# EVIDENCE-OF: R-52032-06717 This means, for example, that if you try to
# give a column a type affinity or add a constraint such as UNIQUE or
# NOT NULL or DEFAULT to a column, those extra tokens are accepted as
# valid, but they do not change the behavior of the rtree.
# Show there are no UNIQUE constraints
do_execsql_test 1.$tn.3 {
INSERT INTO abc VALUES(1, 10.0, 20.0, 10.0, 20.0);
INSERT INTO abc VALUES(2, 10.0, 20.0, 10.0, 20.0);
}
# Show the default values have not been modified
do_execsql_test 1.$tn.4 {
INSERT INTO abc DEFAULT VALUES;
SELECT * FROM abc WHERE rowid NOT IN (1,2)
} {3 0.0 0.0 0.0 0.0}
# Show that there are no NOT NULL constraints
do_execsql_test 1.$tn.5 {
INSERT INTO abc VALUES(NULL, NULL, NULL, NULL, NULL);
SELECT * FROM abc WHERE rowid NOT IN (1,2,3)
} {4 0.0 0.0 0.0 0.0}
# EVIDENCE-OF: R-06893-30579 In an RTREE virtual table, the first column
# always has a type affinity of INTEGER and all other data columns have
# a type affinity of REAL.
do_execsql_test 1.$tn.5 {
INSERT INTO abc VALUES('5', '5', '5', '5', '5');
SELECT * FROM abc WHERE rowid NOT IN (1,2,3,4)
} {5 5.0 5.0 5.0 5.0}
do_execsql_test 1.$tn.6 {
SELECT type FROM pragma_table_info('abc') ORDER BY cid
} {INT REAL REAL REAL REAL}
do_execsql_test 1.$tn.7 " CREATE VIRTUAL TABLE abc2 USING rtree_i32 $cols "
# EVIDENCE-OF: R-06224-52418 In an RTREE_I32 virtual table, all columns
# have type affinity of INTEGER.
do_execsql_test 1.$tn.8 {
INSERT INTO abc2 VALUES('6.0', '6.0', '6.0', '6.0', '6.0');
SELECT * FROM abc2
} {6 6 6 6 6}
do_execsql_test 1.$tn.9 {
SELECT type FROM pragma_table_info('abc2') ORDER BY cid
} {INT INT INT INT INT}
do_execsql_test 1.$tn.10 {
DROP TABLE abc;
DROP TABLE abc2;
}
}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 3.2 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-4
reset_db
# EVIDENCE-OF: R-36195-31555 The usual INSERT, UPDATE, and DELETE
# commands work on an R*Tree index just like on regular tables.
#
# Create a regular table and an rtree table. Perform INSERT, UPDATE and
# DELETE operations, then observe that the contents of the two tables
# are identical.
do_execsql_test 1.0 {
CREATE VIRTUAL TABLE rt USING rtree(id, x1, x2);
CREATE TABLE t1(id INTEGER PRIMARY KEY, x1 REAL, x2 REAL);
}
foreach {tn sql} {
1 "INSERT INTO %TBL% VALUES(5, 11,12)"
2 "INSERT INTO %TBL% VALUES(11, -11,14.5)"
3 "UPDATE %TBL% SET x1=-99 WHERE id=11"
4 "DELETE FROM %TBL% WHERE x2=14.5"
5 "DELETE FROM %TBL%"
} {
set sql1 [string map {%TBL% rt} $sql]
set sql2 [string map {%TBL% t1} $sql]
do_execsql_test 1.$tn.0 $sql1
do_execsql_test 1.$tn.1 $sql2
set data1 [execsql {SELECT * FROM rt ORDER BY 1}]
set data2 [execsql {SELECT * FROM t1 ORDER BY 1}]
set res [expr {$data1==$data2}]
do_test 1.$tn.2 {set res} 1
}
# EVIDENCE-OF: R-56987-45305
do_execsql_test 2.0 {
CREATE VIRTUAL TABLE demo_index USING rtree(
id, -- Integer primary key
minX, maxX, -- Minimum and maximum X coordinate
minY, maxY -- Minimum and maximum Y coordinate
);
INSERT INTO demo_index VALUES
(28215, -80.781227, -80.604706, 35.208813, 35.297367),
(28216, -80.957283, -80.840599, 35.235920, 35.367825),
(28217, -80.960869, -80.869431, 35.133682, 35.208233),
(28226, -80.878983, -80.778275, 35.060287, 35.154446),
(28227, -80.745544, -80.555382, 35.130215, 35.236916),
(28244, -80.844208, -80.841988, 35.223728, 35.225471),
(28262, -80.809074, -80.682938, 35.276207, 35.377747),
(28269, -80.851471, -80.735718, 35.272560, 35.407925),
(28270, -80.794983, -80.728966, 35.059872, 35.161823),
(28273, -80.994766, -80.875259, 35.074734, 35.172836),
(28277, -80.876793, -80.767586, 35.001709, 35.101063),
(28278, -81.058029, -80.956375, 35.044701, 35.223812),
(28280, -80.844208, -80.841972, 35.225468, 35.227203),
(28282, -80.846382, -80.844193, 35.223972, 35.225655);
}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 3.3 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-5
do_execsql_test 1.0 {
INSERT INTO demo_index
SELECT NULL, minX, maxX, minY+0.2, maxY+0.2 FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX+0.2, maxX+0.2, minY, maxY FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX, maxX, minY+0.4, maxY+0.4 FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX+0.4, maxX+0.4, minY, maxY FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX, maxX, minY+0.8, maxY+0.8 FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX+0.8, maxX+0.8, minY, maxY FROM demo_index;
SELECT count(*) FROM demo_index;
} {896}
proc do_vmstep_test {tn sql expr} {
execsql $sql
set step [db status vmstep]
do_test $tn.$step "expr {[subst $expr]}" 1
}
# EVIDENCE-OF: R-45880-07724 Any valid query will work against an R*Tree
# index.
do_execsql_test 1.1.0 {
CREATE TABLE demo_tbl AS SELECT * FROM demo_index;
}
foreach {tn sql} {
1 {SELECT * FROM %TBL% ORDER BY 1}
2 {SELECT max(minX) FROM %TBL% ORDER BY 1}
3 {SELECT max(minX) FROM %TBL% GROUP BY round(minY) ORDER BY 1}
} {
set sql1 [string map {%TBL% demo_index} $sql]
set sql2 [string map {%TBL% demo_tbl} $sql]
do_execsql_test 1.1.$tn $sql1 [execsql $sql2]
}
# EVIDENCE-OF: R-60814-18273 The R*Tree implementation just makes some
# kinds of queries especially efficient.
#
# The second query is more efficient than the first.
do_vmstep_test 1.2.1 {SELECT * FROM demo_index WHERE +rowid=28269} {$step>2000}
do_vmstep_test 1.2.2 {SELECT * FROM demo_index WHERE rowid=28269} {$step<100}
# EVIDENCE-OF: R-37800-50174 Queries against the primary key are
# efficient: SELECT * FROM demo_index WHERE id=28269;
do_vmstep_test 2.2 { SELECT * FROM demo_index WHERE id=28269 } {$step < 100}
# EVIDENCE-OF: R-35847-18866 The big reason for using an R*Tree is so
# that you can efficiently do range queries against the coordinate
# ranges.
#
# EVIDENCE-OF: R-49927-54202
do_vmstep_test 2.3 {
SELECT id FROM demo_index
WHERE minX<=-80.77470 AND maxX>=-80.77470
AND minY<=35.37785 AND maxY>=35.37785;
} {$step < 100}
# EVIDENCE-OF: R-12823-37176 The query above will quickly locate all
# zipcodes that contain the SQLite main office in their bounding box,
# even if the R*Tree contains many entries.
#
do_execsql_test 2.4 {
SELECT id FROM demo_index
WHERE minX<=-80.77470 AND maxX>=-80.77470
AND minY<=35.37785 AND maxY>=35.37785;
} {
28322 28269
}
# EVIDENCE-OF: R-07351-00257 For example, to find all zipcode bounding
# boxes that overlap with the 28269 zipcode: SELECT A.id FROM demo_index
# AS A, demo_index AS B WHERE A.maxX>=B.minX AND A.minX<=B.maxX
# AND A.maxY>=B.minY AND A.minY<=B.maxY AND B.id=28269;
#
# Also check that it is efficient
#
# EVIDENCE-OF: R-39094-01937 This second query will find both 28269
# entry (since every bounding box overlaps with itself) and also other
# zipcode that is close enough to 28269 that their bounding boxes
# overlap.
#
# 28269 is there in the result.
#
do_vmstep_test 2.5.1 {
SELECT A.id FROM demo_index AS A, demo_index AS B
WHERE A.maxX>=B.minX AND A.minX<=B.maxX
AND A.maxY>=B.minY AND A.minY<=B.maxY
AND B.id=28269
} {$step < 100}
do_execsql_test 2.5.2 {
SELECT A.id FROM demo_index AS A, demo_index AS B
WHERE A.maxX>=B.minX AND A.minX<=B.maxX
AND A.maxY>=B.minY AND A.minY<=B.maxY
AND B.id=28269;
} {
28293 28216 28322 28286 28269
28215 28336 28262 28291 28320
28313 28298 28287
}
# EVIDENCE-OF: R-02723-34107 Note that it is not necessary for all
# coordinates in an R*Tree index to be constrained in order for the
# index search to be efficient.
#
# EVIDENCE-OF: R-22490-27246 One might, for example, want to query all
# objects that overlap with the 35th parallel: SELECT id FROM demo_index
# WHERE maxY>=35.0 AND minY<=35.0;
do_vmstep_test 2.6.1 {
SELECT id FROM demo_index
WHERE maxY>=35.0 AND minY<=35.0;
} {$step < 100}
do_execsql_test 2.6.2 {
SELECT id FROM demo_index
WHERE maxY>=35.0 AND minY<=35.0;
} {}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 3.4 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-6
reset_db
# EVIDENCE-OF: R-08327-00674 By default, coordinates are stored in an
# R*Tree using 32-bit floating point values.
#
# EVIDENCE-OF: R-22000-53613 The default virtual table ("rtree") stores
# coordinates as single-precision (4-byte) floating point numbers.
#
# Show this by showing that rounding is consistent with 32-bit float
# rounding.
do_execsql_test 1.0 {
CREATE VIRTUAL TABLE rt USING rtree(id, a,b);
}
do_execsql_test 1.1 {
INSERT INTO rt VALUES(14, -1000000000000, 1000000000000);
SELECT * FROM rt;
} {14 -1000000126976.0 1000000126976.0}
# EVIDENCE-OF: R-39127-51288 When a coordinate cannot be exactly
# represented by a 32-bit floating point number, the lower-bound
# coordinates are rounded down and the upper-bound coordinates are
# rounded up.
foreach {tn val} {
1 100000000000
2 200000000000
3 300000000000
4 400000000000
5 -100000000000
6 -200000000000
7 -300000000000
8 -400000000000
} {
set val [expr $val]
do_execsql_test 2.$tn.0 {DELETE FROM rt}
do_execsql_test 2.$tn.1 {INSERT INTO rt VALUES(23, $val, $val)}
do_execsql_test 2.$tn.2 {
SELECT $val>=a, $val<=b, a!=b FROM rt
} {1 1 1}
}
do_execsql_test 3.0 {
DROP TABLE rt;
CREATE VIRTUAL TABLE rt USING rtree(id, x1,x2, y1,y2);
}
# EVIDENCE-OF: R-45870-62834 Thus, bounding boxes might be slightly
# larger than specified, but will never be any smaller.
foreach {tn x1 x2 y1 y2} {
1 100000000000 200000000000 300000000000 400000000000
} {
set val [expr $val]
do_execsql_test 3.$tn.0 {DELETE FROM rt}
do_execsql_test 3.$tn.1 {INSERT INTO rt VALUES(23, $x1, $x2, $y1, $y2)}
do_execsql_test 3.$tn.2 {
SELECT (x2-x1)*(y2-y1) >= ($x2-$x1)*($y2-$y1) FROM rt
} {1}
}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 3.5 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-7
reset_db
# EVIDENCE-OF: R-55979-39402 It is the nature of the Guttman R-Tree
# algorithm that any write might radically restructure the tree, and in
# the process change the scan order of the nodes.
#
# In the test below, the INSERT marked "THIS INSERT!!" does not affect
# the results of queries with an ORDER BY, but does affect the results
# of one without an ORDER BY. Therefore the INSERT changed the scan
# order.
do_execsql_test 1.0 {
CREATE VIRTUAL TABLE rt USING rtree(id, minX, maxX);
WITH s(i) AS (
SELECT 1 UNION ALL SELECT i+1 FROM s WHERE i<51
)
INSERT INTO rt SELECT NULL, i%10, (i%10)+5 FROM s
}
do_execsql_test 1.1 { SELECT count(*) FROM rt_node } 1
do_test 1.2 {
set res1 [db eval {SELECT * FROM rt WHERE maxX < 30}]
set res1o [db eval {SELECT * FROM rt WHERE maxX < 30 ORDER BY +id}]
db eval { INSERT INTO rt VALUES(NULL, 50, 50) } ;# THIS INSERT!!
set res2 [db eval {SELECT * FROM rt WHERE maxX < 30}]
set res2o [db eval {SELECT * FROM rt WHERE maxX < 30 ORDER BY +id}]
list [expr {$res1==$res2}] [expr {$res1o==$res2o}]
} {0 1}
do_execsql_test 1.3 { SELECT count(*) FROM rt_node } 3
# EVIDENCE-OF: R-00683-48865 For this reason, it is not generally
# possible to modify the R-Tree in the middle of a query of the R-Tree.
# Attempts to do so will fail with a SQLITE_LOCKED "database table is
# locked" error.
#
# SQLITE_LOCKED==6
#
do_test 1.4 {
set nCnt 3
db eval { SELECT * FROM rt WHERE minX>0 AND maxX<12 } {
incr nCnt -1
if {$nCnt==0} {
set rc [catch {db eval {
INSERT INTO rt VALUES(NULL, 51, 51);
}} msg]
set errorcode [db errorcode]
break
}
}
list $errorcode $rc $msg
} {6 1 {database table is locked}}
# EVIDENCE-OF: R-19740-29710 So, for example, suppose an application
# runs one query against an R-Tree like this: SELECT id FROM demo_index
# WHERE maxY>=35.0 AND minY<=35.0; Then for each "id" value
# returned, suppose the application creates an UPDATE statement like the
# following and binds the "id" value returned against the "?1"
# parameter: UPDATE demo_index SET maxY=maxY+0.5 WHERE id=?1;
#
# EVIDENCE-OF: R-52919-32711 Then the UPDATE might fail with an
# SQLITE_LOCKED error.
do_execsql_test 2.0 {
CREATE VIRTUAL TABLE demo_index USING rtree(
id, -- Integer primary key
minX, maxX, -- Minimum and maximum X coordinate
minY, maxY -- Minimum and maximum Y coordinate
);
INSERT INTO demo_index VALUES
(28215, -80.781227, -80.604706, 35.208813, 35.297367),
(28216, -80.957283, -80.840599, 35.235920, 35.367825),
(28217, -80.960869, -80.869431, 35.133682, 35.208233),
(28226, -80.878983, -80.778275, 35.060287, 35.154446);
}
do_test 2.1 {
db eval { SELECT id FROM demo_index WHERE maxY>=35.0 AND minY<=35.0 } {
set rc [catch {
db eval { UPDATE demo_index SET maxY=maxY+0.5 WHERE id=$id }
} msg]
set errorcode [db errorcode]
break
}
list $errorcode $rc $msg
} {6 1 {database table is locked}}
# EVIDENCE-OF: R-32604-49843 Ordinary tables in SQLite are able to read
# and write at the same time.
#
do_execsql_test 3.0 {
CREATE TABLE x1(a INTEGER PRIMARY KEY, b, c);
INSERT INTO x1 VALUES(1, 1, 1);
INSERT INTO x1 VALUES(2, 2, 2);
INSERT INTO x1 VALUES(3, 3, 3);
INSERT INTO x1 VALUES(4, 4, 4);
}
do_test 3.1 {
unset -nocomplain res
set res [list]
db eval { SELECT * FROM x1 } {
lappend res $a $b $c
switch -- $a {
1 {
db eval { INSERT INTO x1 VALUES(5, 5, 5) }
}
2 {
db eval { UPDATE x1 SET c=20 WHERE a=2 }
}
3 {
db eval { DELETE FROM x1 WHERE c IN (3,4) }
}
}
}
set res
} {1 1 1 2 2 2 3 3 3 5 5 5}
do_execsql_test 3.2 {
SELECT * FROM x1
} {1 1 1 2 2 20 5 5 5}
# EVIDENCE-OF: R-06177-00576 And R-Tree can appear to read and write at
# the same time in some circumstances, if it can figure out how to
# reliably run the query to completion before starting the update.
#
# In 8.2, it can, it 8.1, it cannot.
do_test 8.1 {
db eval { SELECT * FROM rt } {
set rc [catch { db eval { INSERT INTO rt VALUES(53,53,53) } } msg]
break;
}
list $rc $msg
} {1 {database table is locked}}
do_test 8.2 {
db eval { SELECT * FROM rt ORDER BY +id } {
set rc [catch { db eval { INSERT INTO rt VALUES(53,53,53) } } msg]
break
}
list $rc $msg
} {0 {}}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 4 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-8
reset_db
# EVIDENCE-OF: R-21062-30088 For the example above, one might create an
# auxiliary table as follows: CREATE TABLE demo_data( id INTEGER PRIMARY
# KEY, -- primary key objname TEXT, -- name of the object objtype TEXT,
# -- object type boundary BLOB -- detailed boundary of object );
#
# One might.
#
do_execsql_test 1.0 {
CREATE TABLE demo_data(
id INTEGER PRIMARY KEY, -- primary key
objname TEXT, -- name of the object
objtype TEXT, -- object type
boundary BLOB -- detailed boundary of object
);
}
do_execsql_test 1.1 {
CREATE VIRTUAL TABLE demo_index USING rtree(
id, -- Integer primary key
minX, maxX, -- Minimum and maximum X coordinate
minY, maxY -- Minimum and maximum Y coordinate
);
INSERT INTO demo_index VALUES
(28215, -80.781227, -80.604706, 35.208813, 35.297367),
(28216, -80.957283, -80.840599, 35.235920, 35.367825),
(28217, -80.960869, -80.869431, 35.133682, 35.208233),
(28226, -80.878983, -80.778275, 35.060287, 35.154446),
(28227, -80.745544, -80.555382, 35.130215, 35.236916),
(28244, -80.844208, -80.841988, 35.223728, 35.225471),
(28262, -80.809074, -80.682938, 35.276207, 35.377747),
(28269, -80.851471, -80.735718, 35.272560, 35.407925),
(28270, -80.794983, -80.728966, 35.059872, 35.161823),
(28273, -80.994766, -80.875259, 35.074734, 35.172836),
(28277, -80.876793, -80.767586, 35.001709, 35.101063),
(28278, -81.058029, -80.956375, 35.044701, 35.223812),
(28280, -80.844208, -80.841972, 35.225468, 35.227203),
(28282, -80.846382, -80.844193, 35.223972, 35.225655);
INSERT INTO demo_index
SELECT NULL, minX, maxX, minY+0.2, maxY+0.2 FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX+0.2, maxX+0.2, minY, maxY FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX, maxX, minY+0.4, maxY+0.4 FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX+0.4, maxX+0.4, minY, maxY FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX, maxX, minY+0.8, maxY+0.8 FROM demo_index;
INSERT INTO demo_index
SELECT NULL, minX+0.8, maxX+0.8, minY, maxY FROM demo_index;
INSERT INTO demo_data(id) SELECT id FROM demo_index;
SELECT count(*) FROM demo_index;
} {896}
set ::contained_in 0
proc contained_in {args} {incr ::contained_in ; return 0}
db func contained_in contained_in
# EVIDENCE-OF: R-32671-43888 Then an efficient way to find the specific
# ZIP code for the main SQLite office would be to run a query like this:
# SELECT objname FROM demo_data, demo_index WHERE
# demo_data.id=demo_index.id AND contained_in(demo_data.boundary,
# 35.37785, -80.77470) AND minX<=-80.77470 AND maxX>=-80.77470 AND
# minY<=35.37785 AND maxY>=35.37785;
do_vmstep_test 1.2 {
SELECT objname FROM demo_data, demo_index
WHERE demo_data.id=demo_index.id
AND contained_in(demo_data.boundary, 35.37785, -80.77470)
AND minX<=-80.77470 AND maxX>=-80.77470
AND minY<=35.37785 AND maxY>=35.37785;
} {$step<100}
set ::contained_in1 $::contained_in
# EVIDENCE-OF: R-32761-23915 One would get the same answer without the
# use of the R*Tree index using the following simpler query: SELECT
# objname FROM demo_data WHERE contained_in(demo_data.boundary,
# 35.37785, -80.77470);
set ::contained_in 0
do_vmstep_test 1.3 {
SELECT objname FROM demo_data
WHERE contained_in(demo_data.boundary, 35.37785, -80.77470);
} {$step>3200}
# EVIDENCE-OF: R-40261-32799 The problem with this latter query is that
# it must apply the contained_in() function to all entries in the
# demo_data table.
#
# 896 of them, IIRC.
do_test 1.4 {
set ::contained_in
} 896
# EVIDENCE-OF: R-24212-52761 The use of the R*Tree in the penultimate
# query reduces the number of calls to contained_in() function to a
# small subset of the entire table.
#
# 2 is a small subset of 896.
#
# EVIDENCE-OF: R-39057-63901 The R*Tree index did not find the exact
# answer itself, it merely limited the search space.
#
# contained_in() filtered out those 2 rows.
do_test 1.5 {
set ::contained_in1
} {2}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 4.1 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-9
reset_db
# EVIDENCE-OF: R-46566-43213 Beginning with SQLite version 3.24.0
# (2018-06-04), r-tree tables can have auxiliary columns that store
# arbitrary data. Auxiliary columns can be used in place of secondary
# tables such as "demo_data".
#
# EVIDENCE-OF: R-41287-48160 Auxiliary columns are marked with a "+"
# symbol before the column name.
#
# This interface cannot conveniently be used to prove anything about
# versions of SQLite prior to 3.24.0.
#
do_execsql_test 1.0 {
CREATE VIRTUAL TABLE rta USING rtree(
id, u1,u2, v1,v2, +aux
);
INSERT INTO rta(aux) VALUES(NULL);
INSERT INTO rta(aux) VALUES(45);
INSERT INTO rta(aux) VALUES(22.3);
INSERT INTO rta(aux) VALUES('hello');
INSERT INTO rta(aux) VALUES(X'ABCD');
SELECT typeof(aux), quote(aux) FROM rta;
} {
null NULL
integer 45
real 22.3
text 'hello'
blob X'ABCD'
}
# EVIDENCE-OF: R-30514-26093 Auxiliary columns must come after all of
# the coordinate boundary columns.
foreach {tn cols} {
1 "id x1,x2, +extra, y1,y2"
2 "extra, +id x1,x2, y1,y2"
3 "id, x1,+x2, extra, y1,y2"
} {
do_catchsql_test 2.$tn "
CREATE VIRTUAL TABLE rrr USING rtree($cols)
" {1 {Auxiliary rtree columns must be last}}
}
do_catchsql_test 3.0 {
CREATE VIRTUAL TABLE rrr USING rtree(+id, extra, x1, x2);
} {1 {near "+": syntax error}}
# EVIDENCE-OF: R-01280-03635 An RTREE table can have no more than 100
# columns total. In other words, the count of columns including the
# integer primary key column, the coordinate boundary columns, and all
# auxiliary columns must be 100 or less.
do_catchsql_test 3.1 {
CREATE VIRTUAL TABLE r1 USING rtree(intid, u1,u2,
+c00, +c01, +c02, +c03, +c04, +c05, +c06, +c07, +c08, +c09,
+c10, +c11, +c12, +c13, +c14, +c15, +c16, +c17, +c18, +c19,
+c20, +c21, +c22, +c23, +c24, +c25, +c26, +c27, +c28, +c29,
+c30, +c31, +c32, +c33, +c34, +c35, +c36, +c37, +c38, +c39,
+c40, +c41, +c42, +c43, +c44, +c45, +c46, +c47, +c48, +c49,
+c50, +c51, +c52, +c53, +c54, +c55, +c56, +c57, +c58, +c59,
+c60, +c61, +c62, +c63, +c64, +c65, +c66, +c67, +c68, +c69,
+c70, +c71, +c72, +c73, +c74, +c75, +c76, +c77, +c78, +c79,
+c80, +c81, +c82, +c83, +c84, +c85, +c86, +c87, +c88, +c89,
+c90, +c91, +c92, +c93, +c94, +c95, +c96
);
} {0 {}}
do_catchsql_test 3.2 {
DROP TABLE r1;
CREATE VIRTUAL TABLE r1 USING rtree(intid, u1,u2,
+c00, +c01, +c02, +c03, +c04, +c05, +c06, +c07, +c08, +c09,
+c10, +c11, +c12, +c13, +c14, +c15, +c16, +c17, +c18, +c19,
+c20, +c21, +c22, +c23, +c24, +c25, +c26, +c27, +c28, +c29,
+c30, +c31, +c32, +c33, +c34, +c35, +c36, +c37, +c38, +c39,
+c40, +c41, +c42, +c43, +c44, +c45, +c46, +c47, +c48, +c49,
+c50, +c51, +c52, +c53, +c54, +c55, +c56, +c57, +c58, +c59,
+c60, +c61, +c62, +c63, +c64, +c65, +c66, +c67, +c68, +c69,
+c70, +c71, +c72, +c73, +c74, +c75, +c76, +c77, +c78, +c79,
+c80, +c81, +c82, +c83, +c84, +c85, +c86, +c87, +c88, +c89,
+c90, +c91, +c92, +c93, +c94, +c95, +c96, +c97
);
} {1 {Too many columns for an rtree table}}
do_catchsql_test 3.3 {
CREATE VIRTUAL TABLE r1 USING rtree(intid, u1,u2, v1,v2,
+c00, +c01, +c02, +c03, +c04, +c05, +c06, +c07, +c08, +c09,
+c10, +c11, +c12, +c13, +c14, +c15, +c16, +c17, +c18, +c19,
+c20, +c21, +c22, +c23, +c24, +c25, +c26, +c27, +c28, +c29,
+c30, +c31, +c32, +c33, +c34, +c35, +c36, +c37, +c38, +c39,
+c40, +c41, +c42, +c43, +c44, +c45, +c46, +c47, +c48, +c49,
+c50, +c51, +c52, +c53, +c54, +c55, +c56, +c57, +c58, +c59,
+c60, +c61, +c62, +c63, +c64, +c65, +c66, +c67, +c68, +c69,
+c70, +c71, +c72, +c73, +c74, +c75, +c76, +c77, +c78, +c79,
+c80, +c81, +c82, +c83, +c84, +c85, +c86, +c87, +c88, +c89,
+c90, +c91, +c92, +c93, +c94,
);
} {0 {}}
do_catchsql_test 3.4 {
DROP TABLE r1;
CREATE VIRTUAL TABLE r1 USING rtree(intid, u1,u2, v1,v2,
+c00, +c01, +c02, +c03, +c04, +c05, +c06, +c07, +c08, +c09,
+c10, +c11, +c12, +c13, +c14, +c15, +c16, +c17, +c18, +c19,
+c20, +c21, +c22, +c23, +c24, +c25, +c26, +c27, +c28, +c29,
+c30, +c31, +c32, +c33, +c34, +c35, +c36, +c37, +c38, +c39,
+c40, +c41, +c42, +c43, +c44, +c45, +c46, +c47, +c48, +c49,
+c50, +c51, +c52, +c53, +c54, +c55, +c56, +c57, +c58, +c59,
+c60, +c61, +c62, +c63, +c64, +c65, +c66, +c67, +c68, +c69,
+c70, +c71, +c72, +c73, +c74, +c75, +c76, +c77, +c78, +c79,
+c80, +c81, +c82, +c83, +c84, +c85, +c86, +c87, +c88, +c89,
+c90, +c91, +c92, +c93, +c94, +c95,
);
} {1 {Too many columns for an rtree table}}
# EVIDENCE-OF: R-05552-15084
do_execsql_test 4.0 {
CREATE VIRTUAL TABLE demo_index2 USING rtree(
id, -- Integer primary key
minX, maxX, -- Minimum and maximum X coordinate
minY, maxY, -- Minimum and maximum Y coordinate
+objname TEXT, -- name of the object
+objtype TEXT, -- object type
+boundary BLOB -- detailed boundary of object
);
}
do_execsql_test 4.1 {
CREATE VIRTUAL TABLE demo_index USING rtree(
id, -- Integer primary key
minX, maxX, -- Minimum and maximum X coordinate
minY, maxY -- Minimum and maximum Y coordinate
);
CREATE TABLE demo_data(
id INTEGER PRIMARY KEY, -- primary key
objname TEXT, -- name of the object
objtype TEXT, -- object type
boundary BLOB -- detailed boundary of object
);
INSERT INTO demo_index2(id) VALUES(1);
INSERT INTO demo_index(id) VALUES(1);
INSERT INTO demo_data(id) VALUES(1);
}
do_test 4.2 {
catch { array unset R }
db eval {SELECT * FROM demo_index2} R { set r1 [array names R] }
catch { array unset R }
db eval {SELECT * FROM demo_index NATURAL JOIN demo_data } R {
set r2 [array names R]
}
expr {$r1==$r2}
} {1}
# EVIDENCE-OF: R-26099-32169 SELECT objname FROM demo_index2 WHERE
# contained_in(boundary, 35.37785, -80.77470) AND minX<=-80.77470 AND
# maxX>=-80.77470 AND minY<=35.37785 AND maxY>=35.37785;
do_execsql_test 4.3.1 {
DELETE FROM demo_index2;
INSERT INTO demo_index2(id,minX,maxX,minY,maxY) VALUES
(28215, -80.781227, -80.604706, 35.208813, 35.297367),
(28216, -80.957283, -80.840599, 35.235920, 35.367825),
(28217, -80.960869, -80.869431, 35.133682, 35.208233),
(28226, -80.878983, -80.778275, 35.060287, 35.154446),
(28227, -80.745544, -80.555382, 35.130215, 35.236916),
(28244, -80.844208, -80.841988, 35.223728, 35.225471),
(28262, -80.809074, -80.682938, 35.276207, 35.377747),
(28269, -80.851471, -80.735718, 35.272560, 35.407925),
(28270, -80.794983, -80.728966, 35.059872, 35.161823),
(28273, -80.994766, -80.875259, 35.074734, 35.172836),
(28277, -80.876793, -80.767586, 35.001709, 35.101063),
(28278, -81.058029, -80.956375, 35.044701, 35.223812),
(28280, -80.844208, -80.841972, 35.225468, 35.227203),
(28282, -80.846382, -80.844193, 35.223972, 35.225655);
}
set ::contained_in 0
proc contained_in {args} {
incr ::contained_in
return 0
}
db func contained_in contained_in
do_execsql_test 4.3.2 {
SELECT objname FROM demo_index2
WHERE contained_in(boundary, 35.37785, -80.77470)
AND minX<=-80.77470 AND maxX>=-80.77470
AND minY<=35.37785 AND maxY>=35.37785;
}
do_test 4.3.3 {
# Function invoked only once because r-tree filtering happened first.
set ::contained_in
} 1
set ::contained_in 0
do_execsql_test 4.3.4 {
SELECT objname FROM demo_index2
WHERE contained_in(boundary, 35.37785, -80.77470)
}
do_test 4.3.3 {
# Function invoked 14 times because no r-tree filtering. Inefficient.
set ::contained_in
} 14
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 4.1.1 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-9
reset_db
# EVIDENCE-OF: R-24021-02490 For auxiliary columns, only the name of the
# column matters. The type affinity is ignored.
#
# EVIDENCE-OF: R-39906-44154 Constraints such as NOT NULL, UNIQUE,
# REFERENCES, or CHECK are also ignored.
do_execsql_test 1.0 { PRAGMA foreign_keys = on }
foreach {tn auxcol nm} {
1 "+extra INTEGER" extra
2 "+extra TEXT" extra
3 "+extra BLOB" extra
4 "+extra REAL" extra
5 "+col NOT NULL" col
6 "+col CHECK (col IS NOT NULL)" col
7 "+col REFERENCES tbl(x)" col
} {
do_execsql_test 1.$tn.1 "
CREATE VIRTUAL TABLE rt USING rtree_i32(k, a,b, $auxcol)
"
# Check that the aux column has no affinity. Or NOT NULL constraint.
# And that the aux column is the child key of an FK constraint.
#
do_execsql_test 1.$tn.2 "
INSERT INTO rt($nm) VALUES(NULL), (45), (-123.2), ('456'), (X'ABCD');
SELECT typeof($nm), quote($nm) FROM rt;
" {
null NULL
integer 45
real -123.2
text '456'
blob X'ABCD'
}
# Check that there is no UNIQUE constraint either.
#
do_execsql_test 1.$tn.3 "
INSERT INTO rt($nm) VALUES('xyz'), ('xyz'), ('xyz');
"
do_execsql_test 1.$tn.2 {
DROP TABLE rt
}
}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 5 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-10
# EVIDENCE-OF: R-21011-43790 If integer coordinates are desired, declare
# the table using "rtree_i32" instead: CREATE VIRTUAL TABLE intrtree
# USING rtree_i32(id,x0,x1,y0,y1,z0,z1);
do_execsql_test 1.0 {
CREATE VIRTUAL TABLE intrtree USING rtree_i32(id,x0,x1,y0,y1,z0,z1);
INSERT INTO intrtree DEFAULT VALUES;
SELECT typeof(x0) FROM intrtree;
} {integer}
# EVIDENCE-OF: R-09193-49806 An rtree_i32 stores coordinates as 32-bit
# signed integers.
#
# Show that coordinates are cast in a way consistent with casting to
# a signed 32-bit integer.
do_execsql_test 1.1 {
DELETE FROM intrtree;
INSERT INTO intrtree VALUES(333,
1<<44, (1<<44)+1,
10000000000, 10000000001,
-10000000001, -10000000000
);
SELECT * FROM intrtree;
} {
333 0 1 1410065408 1410065409 -1410065409 -1410065408
}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 7.1 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-11
reset_db
# This command assumes that the argument is a node blob for a 2 dimensional
# i32 r-tree table. It decodes and returns a list of cells from the node
# as a list. Each cell is itself a list of the following form:
#
# {$rowid $minX $maxX $minY $maxY}
#
# For internal (non-leaf) nodes, the rowid is replaced by the child node
# number.
#
proc rnode {aData} {
set nDim 2
set nData [string length $aData]
set nBytePerCell [expr (8 + 2*$nDim*4)]
binary scan [string range $aData 2 3] S nCell
set res [list]
for {set i 0} {$i < $nCell} {incr i} {
set iOff [expr $i*$nBytePerCell+4]
set cell [string range $aData $iOff [expr $iOff+$nBytePerCell-1]]
binary scan $cell WIIII rowid x1 x2 y1 y2
lappend res [list $rowid $x1 $x2 $y1 $y2]
}
return $res
}
# aData must be a node blob. This command returns true if the node contains
# rowid $rowid, or false otherwise.
#
proc rnode_contains {aData rowid} {
set L [rnode $aData]
foreach cell $L {
set r [lindex $cell 0]
if {$r==$rowid} { return 1 }
}
return 0
}
proc rnode_replace_cell {aData iCell cell} {
set aCell [binary format WIIII {*}$cell]
set nDim 2
set nBytePerCell [expr (8 + 2*$nDim*4)]
set iOff [expr $iCell*$nBytePerCell+4]
set aNew [binary format a*a*a* \
[string range $aData 0 $iOff-1] \
$aCell \
[string range $aData $iOff+$nBytePerCell end] \
]
return $aNew
}
db function rnode rnode
db function rnode_contains rnode_contains
db function rnode_replace_cell rnode_replace_cell
foreach {tn nm} {
1 x1
2 asdfghjkl
3 hello_world
} {
do_execsql_test 1.$tn.1 "
CREATE VIRTUAL TABLE $nm USING rtree(a,b,c,d,e);
"
# EVIDENCE-OF: R-33789-46762 The content of an R*Tree index is actually
# stored in three ordinary SQLite tables with names derived from the
# name of the R*Tree.
#
# EVIDENCE-OF: R-39849-06566 This is their schema: CREATE TABLE
# %_node(nodeno INTEGER PRIMARY KEY, data) CREATE TABLE %_parent(nodeno
# INTEGER PRIMARY KEY, parentnode) CREATE TABLE %_rowid(rowid INTEGER
# PRIMARY KEY, nodeno)
#
# EVIDENCE-OF: R-07489-10051 The "%" in the name of each shadow table is
# replaced by the name of the R*Tree virtual table. So, if the name of
# the R*Tree table is "xyz" then the three shadow tables would be
# "xyz_node", "xyz_parent", and "xyz_rowid".
do_execsql_test 1.$tn.2 {
SELECT sql FROM sqlite_schema WHERE name!=$nm ORDER BY 1
} [string map [list % $nm] "
{CREATE TABLE \"%_node\"(nodeno INTEGER PRIMARY KEY,data)}
{CREATE TABLE \"%_parent\"(nodeno INTEGER PRIMARY KEY,parentnode)}
{CREATE TABLE \"%_rowid\"(rowid INTEGER PRIMARY KEY,nodeno)}
"]
do_execsql_test 1.$tn "DROP TABLE $nm"
}
# EVIDENCE-OF: R-51070-59303 There is one entry in the %_node table for
# each R*Tree node.
#
# The following creates a 6 node r-tree structure.
#
do_execsql_test 2.0 {
CREATE VIRTUAL TABLE r1 USING rtree_i32(i, x1,x2, y1,y2);
WITH t(i) AS (
VALUES(1) UNION SELECT i+1 FROM t WHERE i<110
)
INSERT INTO r1 SELECT i, (i%10), (i%10)+2, (i%6), (i%7)+6 FROM t;
}
do_execsql_test 2.1 {
SELECT count(*) FROM r1_node;
} 6
# EVIDENCE-OF: R-27261-09153 All nodes other than the root have an entry
# in the %_parent shadow table that identifies the parent node.
#
# In this case nodes 2-6 are the children of node 1.
#
do_execsql_test 2.3 {
SELECT nodeno, parentnode FROM r1_parent
} {2 1 3 1 4 1 5 1 6 1}
# EVIDENCE-OF: R-02358-35037 The %_rowid shadow table maps entry rowids
# to the node that contains that entry.
#
do_execsql_test 2.4 {
SELECT 'failed' FROM r1_rowid WHERE 0==rnode_contains(
(SELECT data FROM r1_node WHERE nodeno=r1_rowid.nodeno), rowid
)
}
do_test 2.5 {
db eval { SELECT nodeno, data FROM r1_node WHERE nodeno!=1 } {
set L [rnode $data]
foreach cell $L {
set rowid [lindex $cell 0]
set rowid_nodeno 0
db eval {SELECT nodeno AS rowid_nodeno FROM r1_rowid WHERE rowid=$rowid} {
break
}
if {$rowid_nodeno!=$nodeno} { error "data mismatch!" }
}
}
} {}
# EVIDENCE-OF: R-65201-22208 Extra columns appended to the %_rowid table
# hold the content of auxiliary columns.
#
# EVIDENCE-OF: R-44161-28345 The names of these extra %_rowid columns
# are probably not the same as the actual auxiliary column names.
#
# In this case, the auxiliary columns are named "e1" and "e2". The
# extra %_rowid columns are named "a0" and "a1".
#
do_execsql_test 3.0 {
CREATE VIRTUAL TABLE rtaux USING rtree(id, x1,x2, y1,y2, +e1, +e2);
SELECT sql FROM sqlite_schema WHERE name='rtaux_rowid';
} {
{CREATE TABLE "rtaux_rowid"(rowid INTEGER PRIMARY KEY,nodeno,a0,a1)}
}
do_execsql_test 3.1 {
INSERT INTO rtaux(e1, e2) VALUES('hello', 'world'), (123, 456);
}
do_execsql_test 3.2 {
SELECT a0, a1 FROM rtaux_rowid;
} {
hello world 123 456
}
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# Section 7.2 of documentation.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
set testprefix rtreedoc-12
reset_db
forcedelete test.db2
db function rnode rnode
db function rnode_contains rnode_contains
db function rnode_replace_cell rnode_replace_cell
# EVIDENCE-OF: R-13571-45795 The scalar SQL function rtreecheck(R) or
# rtreecheck(S,R) runs an integrity check on the rtree table named R
# contained within database S.
#
# EVIDENCE-OF: R-36011-59963 The function returns a human-language
# description of any problems found, or the string 'ok' if everything is
# ok.
#
do_execsql_test 1.0 {
CREATE VIRTUAL TABLE rt1 USING rtree(id, a, b);
WITH s(i) AS (
VALUES(1) UNION ALL SELECT i+1 FROM s WHERE i<200
)
INSERT INTO rt1 SELECT i, i, i FROM s;
ATTACH 'test.db2' AS 'aux';
CREATE VIRTUAL TABLE aux.rt1 USING rtree(id, a, b);
INSERT INTO aux.rt1 SELECT * FROM rt1;
}
do_execsql_test 1.1.1 { SELECT rtreecheck('rt1'); } {ok}
do_execsql_test 1.1.2 { SELECT rtreecheck('main', 'rt1'); } {ok}
do_execsql_test 1.1.3 { SELECT rtreecheck('aux', 'rt1'); } {ok}
do_catchsql_test 1.1.4 {
SELECT rtreecheck('nosuchdb', 'rt1');
} {1 {SQL logic error}}
# Corrupt the table in database 'main':
do_execsql_test 1.2.1 { UPDATE rt1_node SET nodeno=21 WHERE nodeno=3; }
do_execsql_test 1.2.1 { SELECT rtreecheck('rt1')=='ok'; } {0}
do_execsql_test 1.2.2 { SELECT rtreecheck('main', 'rt1')=='ok'; } {0}
do_execsql_test 1.2.3 { SELECT rtreecheck('aux', 'rt1')=='ok'; } {1}
do_execsql_test 1.2.4 { UPDATE rt1_node SET nodeno=3 WHERE nodeno=21; }
# Corrupt the table in database 'aux':
do_execsql_test 1.2.1 { UPDATE aux.rt1_node SET nodeno=21 WHERE nodeno=3; }
do_execsql_test 1.2.1 { SELECT rtreecheck('rt1')=='ok'; } {1}
do_execsql_test 1.2.2 { SELECT rtreecheck('main', 'rt1')=='ok'; } {1}
do_execsql_test 1.2.3 { SELECT rtreecheck('aux', 'rt1')=='ok'; } {0}
do_execsql_test 1.2.4 { UPDATE rt1_node SET nodeno=3 WHERE nodeno=21; }
# EVIDENCE-OF: R-45759-33459 Example: To verify that an R*Tree named
# "demo_index" is well-formed and internally consistent, run: SELECT
# rtreecheck('demo_index');
do_execsql_test 2.0 {
CREATE VIRTUAL TABLE demo_index USING rtree(id, x1,x2, y1,y2);
INSERT INTO demo_index SELECT id, a, b, a, b FROM rt1;
}
do_execsql_test 2.1 { SELECT rtreecheck('demo_index') } {ok}
do_execsql_test 2.2 {
UPDATE demo_index_rowid SET nodeno=44 WHERE rowid=44;
SELECT rtreecheck('demo_index');
} {{Found (44 -> 44) in %_rowid table, expected (44 -> 4)}}
do_execsql_test 3.0 {
CREATE VIRTUAL TABLE rt2 USING rtree_i32(id, a, b, c, d);
WITH s(i) AS (
VALUES(1) UNION ALL SELECT i+1 FROM s WHERE i<200
)
INSERT INTO rt2 SELECT i, i, i+2, i, i+2 FROM s;
}
# EVIDENCE-OF: R-02555-31045 for each dimension, (coord1 <= coord2).
#
execsql BEGIN
do_test 3.1 {
set cell [
lindex [execsql {SELECT rnode(data) FROM rt2_node WHERE nodeno=3}] 0 3
]
set cell [list [lindex $cell 0] \
[lindex $cell 2] [lindex $cell 1] \
[lindex $cell 3] [lindex $cell 4] \
]
execsql {
UPDATE rt2_node SET data=rnode_replace_cell(data, 3, $cell) WHERE nodeno=3
}
execsql { SELECT rtreecheck('rt2') }
} {{Dimension 0 of cell 3 on node 3 is corrupt}}
execsql ROLLBACK
# EVIDENCE-OF: R-13844-15873 unless the cell is on the root node, that
# the cell is bounded by the parent cell on the parent node.
#
execsql BEGIN
do_test 3.2 {
set cell [
lindex [execsql {SELECT rnode(data) FROM rt2_node WHERE nodeno=3}] 0 3
]
lset cell 3 450
lset cell 4 451
execsql {
UPDATE rt2_node SET data=rnode_replace_cell(data, 3, $cell) WHERE nodeno=3
}
execsql { SELECT rtreecheck('rt2') }
} {{Dimension 1 of cell 3 on node 3 is corrupt relative to parent}}
execsql ROLLBACK
# EVIDENCE-OF: R-02505-03621 for leaf nodes, that there is an entry in
# the %_rowid table corresponding to the cell's rowid value that points
# to the correct node.
#
execsql BEGIN
do_test 3.3 {
execsql {
UPDATE rt2_rowid SET rowid=452 WHERE rowid=100
}
execsql { SELECT rtreecheck('rt2') }
} {{Mapping (100 -> 6) missing from %_rowid table}}
execsql ROLLBACK
# EVIDENCE-OF: R-50927-02218 for cells on non-leaf nodes, that there is
# an entry in the %_parent table mapping from the cell's child node to
# the node that it resides on.
#
execsql BEGIN
do_test 3.4.1 {
execsql {
UPDATE rt2_parent SET parentnode=123 WHERE nodeno=3
}
execsql { SELECT rtreecheck('rt2') }
} {{Found (3 -> 123) in %_parent table, expected (3 -> 1)}}
execsql ROLLBACK
execsql BEGIN
do_test 3.4.2 {
execsql {
UPDATE rt2_parent SET nodeno=123 WHERE nodeno=3
}
execsql { SELECT rtreecheck('rt2') }
} {{Mapping (3 -> 1) missing from %_parent table}}
execsql ROLLBACK
# EVIDENCE-OF: R-23235-09153 That there are the same number of entries
# in the %_rowid table as there are leaf cells in the r-tree structure,
# and that there is a leaf cell that corresponds to each entry in the
# %_rowid table.
execsql BEGIN
do_test 3.5 {
execsql { INSERT INTO rt2_rowid VALUES(1000, 1000) }
execsql { SELECT rtreecheck('rt2') }
} {{Wrong number of entries in %_rowid table - expected 200, actual 201}}
execsql ROLLBACK
# EVIDENCE-OF: R-62800-43436 That there are the same number of entries
# in the %_parent table as there are non-leaf cells in the r-tree
# structure, and that there is a non-leaf cell that corresponds to each
# entry in the %_parent table.
execsql BEGIN
do_test 3.6 {
execsql { INSERT INTO rt2_parent VALUES(1000, 1000) }
execsql { SELECT rtreecheck('rt2') }
} {{Wrong number of entries in %_parent table - expected 9, actual 10}}
execsql ROLLBACK
finish_test