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Overview
| Comment: | Fix the generation of sqlite3_rtree_query_info.iRowid and add test cases to verify that it is fixed. |
|---|---|
| Downloads: | Tarball | ZIP archive | SQL archive |
| Timelines: | family | ancestors | descendants | both | rtree-enhancements |
| Files: | files | file ages | folders |
| SHA1: |
eba95ead49f8f8ce45d400186562ff00 |
| User & Date: | drh 2014-04-21 18:13:37 |
Context
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2014-04-25
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| 16:29 | Enhance the sqlite3_rtree_query_info object to report on the number of elements in the priority queue at each level. Closed-Leaf check-in: f7dad408 user: drh tags: rtree-enhancements | |
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2014-04-21
| ||
| 18:13 | Fix the generation of sqlite3_rtree_query_info.iRowid and add test cases to verify that it is fixed. check-in: eba95ead user: drh tags: rtree-enhancements | |
| 15:53 | Be sure to initialize the sqlite3_rtree_query_info.iRowid field for the leaves of the R-Tree when doing a query callback search. check-in: 43946938 user: drh tags: rtree-enhancements | |
Changes
Changes to ext/rtree/rtree.c.
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int nCoord = pInfo->nCoord; /* No. of coordinates */
int rc; /* Callback return code */
sqlite3_rtree_dbl aCoord[RTREE_MAX_DIMENSIONS*2]; /* Decoded coordinates */
assert( pConstraint->op==RTREE_MATCH || pConstraint->op==RTREE_QUERY );
assert( nCoord==2 || nCoord==4 || nCoord==6 || nCoord==8 || nCoord==10 );
if( pConstraint->op==RTREE_MATCH && pSearch->iLevel==1 ){
pInfo->iRowid = readInt64(pCellData);
}
pCellData += 8;
for(i=0; i<nCoord; i++, pCellData += 4){
RTREE_DECODE_COORD(eInt, pCellData, aCoord[i]);
}
if( pConstraint->op==RTREE_MATCH ){
|
| |
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int nCoord = pInfo->nCoord; /* No. of coordinates */
int rc; /* Callback return code */
sqlite3_rtree_dbl aCoord[RTREE_MAX_DIMENSIONS*2]; /* Decoded coordinates */
assert( pConstraint->op==RTREE_MATCH || pConstraint->op==RTREE_QUERY );
assert( nCoord==2 || nCoord==4 || nCoord==6 || nCoord==8 || nCoord==10 );
if( pConstraint->op==RTREE_QUERY && pSearch->iLevel==1 ){
pInfo->iRowid = readInt64(pCellData);
}
pCellData += 8;
for(i=0; i<nCoord; i++, pCellData += 4){
RTREE_DECODE_COORD(eInt, pCellData, aCoord[i]);
}
if( pConstraint->op==RTREE_MATCH ){
|
Changes to ext/rtree/rtreeE.test.
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# 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}
# 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;
|
> > > > > > > > > > |
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# 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;
|
Changes to src/test_rtree.c.
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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{
/* 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;
}
}
if( nWithin==0 ){
p->eWithin = NOT_WITHIN;
}else if( nWithin>=4 ){
p->eWithin = FULLY_WITHIN;
}else{
p->eWithin = PARTLY_WITHIN;
|
| > > > > > > > > |
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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;
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