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Overview</a></div> +<div class="fancy-toc1"><a href="#compiling_the_r_tree_module">2. Compiling The R*Tree Module</a></div> +<div class="fancy-toc1"><a href="#using_the_r_tree_module">3. Using the R*Tree Module</a></div> +<div class="fancy-toc2"><a href="#creating_an_r_tree_index">3.1. Creating An R*Tree Index</a></div> +<div class="fancy-toc3"><a href="#column_naming_details">3.1.1. Column naming details</a></div> +<div class="fancy-toc2"><a href="#populating_an_r_tree_index">3.2. Populating An R*Tree Index</a></div> +<div class="fancy-toc2"><a href="#querying_an_r_tree_index">3.3. Querying An R*Tree Index</a></div> +<div class="fancy-toc2"><a href="#roundoff_error">3.4. Roundoff Error</a></div> +<div class="fancy-toc2"><a href="#reading_and_writing_at_the_same_time">3.5. Reading And Writing At The Same Time</a></div> +<div class="fancy-toc1"><a href="#using_r_trees_effectively">4. Using R*Trees Effectively</a></div> +<div class="fancy-toc2"><a href="#auxiliary_columns">4.1. Auxiliary Columns</a></div> +<div class="fancy-toc3"><a href="#limitations">4.1.1. Limitations</a></div> +<div class="fancy-toc1"><a href="#integer_valued_r_trees">5. Integer-Valued R-Trees</a></div> +<div class="fancy-toc1"><a href="#custom_r_tree_queries">6. Custom R-Tree Queries</a></div> +<div class="fancy-toc2"><a href="#the_legacy_xgeom_callback">6.1. The Legacy xGeom Callback</a></div> +<div class="fancy-toc2"><a href="#the_new_xqueryfunc_callback">6.2. The New xQueryFunc Callback</a></div> +<div class="fancy-toc2"><a href="#additional_considerations_for_custom_queries">6.3. Additional Considerations for Custom Queries</a></div> +<div class="fancy-toc1"><a href="#implementation_details">7. Implementation Details</a></div> +<div class="fancy-toc2"><a href="#shadow_tables">7.1. Shadow Tables</a></div> +<div class="fancy-toc2"><a href="#integrity_check_using_the_rtreecheck_sql_function">7.2. Integrity Check using the rtreecheck() SQL function</a></div> +</div> +</div> +<script> +function toggle_toc(){ +var sub = document.getElementById("toc_sub") +var mk = document.getElementById("toc_mk") +if( sub.style.display!="block" ){ +sub.style.display = "block"; +mk.innerHTML = "▼"; +} else { +sub.style.display = "none"; +mk.innerHTML = "►"; +} +} +</script> +</div> + + + + +<h1 id="overview"><span>1. </span>Overview</h1> + +<p> +An <a href="http://en.wikipedia.org/wiki/R-tree">R-Tree</a> is a special +index that is designed for doing range queries. R-Trees are most commonly +used in geospatial systems where each entry is a rectangle with minimum and +maximum X and Y coordinates. Given a query rectangle, an R-Tree is able +to quickly find all entries that are contained within the query rectangle +or which overlap the query rectangle. This idea is easily extended to +three dimensions for use in CAD systems. R-Trees also find use in time-domain +range look-ups. For example, suppose a database records the starting and +ending times for a large number of events. A R-Tree is able to quickly +find all events that were active at any time during a given +time interval, or all events that started during a particular time interval, +or all events that both started and ended within a given time interval. +And so forth. +</p> + +<p> +The R-Tree concept originated with +<a href="https://link.springer.com/referenceworkentry/10.1007/978-0-387-35973-1_1151">Toni Guttman</a>: +<em>R-Trees: A Dynamic Index Structure for Spatial Searching</em>, +Proc. 1984 ACM SIGMOD International Conference on Management of Data, +pp. 47-57. +The implementation found in SQLite is a refinement of Guttman's original +idea, commonly called "R*Trees", that was described by +Norbert Beckmann, Hans-Peter Kriegel, Ralf Schneider, Bernhard Seeger: +<em>The R*-Tree: An Efficient and Robust Access Method for Points +and Rectangles.</em> SIGMOD Conference 1990: 322-331. +</p> + +<h1 id="compiling_the_r_tree_module"><span>2. </span>Compiling The R*Tree Module</h1> + +<p> +The source code to the SQLite R*Tree module is included as part +of the <a href="amalgamation.html">amalgamation</a>. However, depending on configuration options +and the particular version of SQLite you are using, it may or may not +be enabled by default. To ensure that the R*Tree module is enabled, +simply compile with the <a href="compile.html#enable_rtree">SQLITE_ENABLE_RTREE</a> +C-preprocessor macro defined. With many compilers, this is accomplished +by adding the option "-DSQLITE_ENABLE_RTREE=1" to the compiler +command-line. +</p> + +<h1 id="using_the_r_tree_module"><span>3. </span>Using the R*Tree Module</h1> + +<p> +The SQLite R*Tree module is implemented as a +<a href="c3ref/create_module.html">virtual table</a>. Each R*Tree index is a +virtual table with an odd number of columns between 3 and 11. +The first column is always a 64-bit signed integer primary key. +The other columns are pairs, one pair per dimension, containing the +minimum and maximum values for that dimension, respectively. +A 1-dimensional R*Tree thus has 3 columns. +A 2-dimensional R*Tree has 5 columns. +A 3-dimensional R*Tree has 7 columns. +A 4-dimensional R*Tree has 9 columns. +And a 5-dimensional R*Tree has 11 columns. The SQLite R*Tree implementation +does not support R*Trees wider than 5 dimensions. +</p> + +<p> +The first column of an SQLite R*Tree is similar to an integer primary +key column of a normal SQLite table. It may only store a 64-bit signed +integer value. Inserting a NULL value into this column causes SQLite +to automatically generate a new unique primary key value. 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. +</p><p> +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. Unlike regular SQLite tables which can store data in a variety of +datatypes and formats, the R*Tree rigidly enforce these storage types. +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. + +</p><h2 id="creating_an_r_tree_index"><span>3.1. </span>Creating An R*Tree Index</h2> + +<p> +A new R*Tree index is created as follows: +</p> + +<div class="codeblock"><pre>CREATE VIRTUAL TABLE <em><name></em> USING rtree(<em><column-names></em>); +</pre></div> + +<p> +The <em><name></em> is the name your application chooses for the +R*Tree index and <em><column-names></em> is a comma separated list +of between 3 and 11 columns. +The virtual <name> table creates three <a href="vtab.html#xshadowname">shadow tables</a> to actually +store its content. The names of these shadow tables are: +</p> + +<div class="codeblock"><pre><em><name></em><strong>_node</strong><br> +<em><name></em><strong>_rowid</strong><br> +<em><name></em><strong>_parent</strong> +</pre></div> + + +<p> +The shadow tables are ordinary SQLite data tables. You can query them +directly if you like, though this unlikely to reveal anything particularly +useful. +And you can <a href="lang_update.html">UPDATE</a>, <a href="lang_delete.html">DELETE</a>, <a href="lang_insert.html">INSERT</a> or even <a href="lang_droptable.html">DROP</a> +the shadow tables, though doing so will corrupt your R*Tree index. +So it is best to simply ignore the shadow tables. Recognize that they +hold your R*Tree index information and let it go as that. +</p> + +<p> +As an example, consider creating a two-dimensional R*Tree index for use in +spatial queries: +</p> + +<div class="codeblock"><pre>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 +); +</pre></div> + + +<h3 id="column_naming_details"><span>3.1.1. </span>Column naming details</h3> + +<p> +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. +This means, for example, that if you try to give a column a +<a href="datatype3.html#affinity">type affinity</a> 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. +In an RTREE virtual table, the first column always has a +<a href="datatype3.html#affinity">type affinity</a> of INTEGER and all other data columns have a +<a href="datatype3.html#affinity">type affinity</a> of REAL. +In an RTREE_I32 virtual table, all columns have type affinity of INTEGER. + +</p><p> +Recommended practice is to omit any extra tokens in the rtree specification. +Let each argument to "rtree" be a single ordinary label that is the name of +the corresponding column, and omit all other tokens from the argument list. + +</p><h2 id="populating_an_r_tree_index"><span>3.2. </span>Populating An R*Tree Index</h2> + +<p> +The usual <a href="lang_insert.html">INSERT</a>, <a href="lang_update.html">UPDATE</a>, and <a href="lang_delete.html">DELETE</a> commands work on an R*Tree +index just like on regular tables. So to insert some data into our sample +R*Tree index, we can do something like this: +</p> + +<div class="codeblock"><pre>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); +</pre></div> + + +<p> +The entries above are bounding boxes (longitude and latitude) for 14 +zipcodes near Charlotte, NC. A real database would have many thousands, +millions, or billions of such entries, but this small 14-row sample will +be sufficient to illustrate the ideas. +</p> + +<h2 id="querying_an_r_tree_index"><span>3.3. </span>Querying An R*Tree Index</h2> + +<p> +Any valid query will work against an R*Tree index. The R*Tree +implementation just makes some kinds of queries especially +efficient. Queries against the primary key are efficient: +</p> + +<div class="codeblock"><pre>SELECT * FROM demo_index WHERE id=28269; +</pre></div> + + +<p> +Of course, an ordinary SQLite table will also do a query against its +integer primary key efficiently, so the previous is not important. +The big reason for using an R*Tree is so that +you can efficiently do range queries against the coordinate +ranges. For example, the main office of the SQLite project is +located at 35.37785, -80.77470. +To find which zipcodes might service that office, one could right: +</p> + +<div class="codeblock"><pre>SELECT id FROM demo_index + WHERE minX<=-80.77470 AND maxX>=-80.77470 + AND minY<=35.37785 AND maxY>=35.37785; +</pre></div> + + +<p> +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. The previous is an example +of a "contained-within" query. The R*Tree also supports "overlapping" +queries. For example, to find all zipcode bounding boxes that overlap +with the 28269 zipcode: +</p> + +<div class="codeblock"><pre>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; +</pre></div> + + +<p> +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. +</p> + +<p> +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. +One might, for example, want to query all objects that overlap with +the 35th parallel: +</p> + +<div class="codeblock"><pre>SELECT id FROM demo_index + WHERE maxY>=35.0 AND minY<=35.0; +</pre></div> + + +<p> +But, generally speaking, the more constraints that the R*Tree module +has to work with, and the smaller the bounding box, the faster the +results will come back. +</p> + +<h2 id="roundoff_error"><span>3.4. </span>Roundoff Error</h2> + +<p> +By default, coordinates are stored in an R*Tree using 32-bit floating +point values. 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. Thus, bounding boxes might +be slightly larger than specified, but will never be any smaller. This +is exactly what is desired for doing the more common "overlapping" queries +where the application wants to find every entry in the R*Tree that overlaps +a query bounding box. Rounding the entry bounding boxes outward might cause a +few extra entries to appears in an overlapping query if the edge of the +entry bounding box corresponds to an edge of the query bounding box. But +the overlapping query will never miss a valid table entry. + +</p><p>However, for a "contained-within" style query, rounding the bounding +boxes outward might cause some entries to be excluded from the result set +if the edge of the entry bounding box corresponds to the edge of the query +bounding box. To guard against this, applications should expand their +contained-within query boxes slightly (by 0.000012%) by rounding down the +lower coordinates and rounding up the top coordinates, in each dimension. + +<a name="readwrite"></a> + +</p><h2 id="reading_and_writing_at_the_same_time"><span>3.5. </span>Reading And Writing At The Same Time</h2> + +<p> +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. 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 <a href="rescode.html#locked">SQLITE_LOCKED</a> "database table is locked" error. + +</p><p> +So, for example, suppose an application runs one query against an R-Tree like +this: + +</p><div class="codeblock"><pre>SELECT id FROM demo_index + WHERE maxY>=35.0 AND minY<=35.0; +</pre></div> + +<p> +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: + +</p><div class="codeblock"><pre>UPDATE demo_index SET maxY=maxY+0.5 WHERE id=?1; +</pre></div> + +<p> +Then the UPDATE might fail with an SQLITE_LOCKED error. The reason is that +the initial query has not run to completion. It is remembering its place +in the middle of a scan of the R-Tree. So an update to the R-Tree cannot +be tolerated as this would disrupt the scan. + +</p><p> +This is a limitation of the R-Tree extension only. Ordinary tables in +SQLite are able to read and write at the same time. Other virtual tables +might (or might not) also that capability. 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. But +you shouldn't count on that for every query. Generally speaking, it is +best to avoid running queries and updates to the same R-Tree at the same +time. + +</p><p> +If you really need to update an R-Tree based on complex queries against +the same R-Tree, it is best to run the complex queries first and store +the results in a temporary table, then update the R-Tree based on the values +stored in the temporary table. + +</p><h1 id="using_r_trees_effectively"><span>4. </span>Using R*Trees Effectively</h1> + +<p> +For SQLite versions prior to 3.24.0 (2018-06-04), +the only information that an R*Tree index stores about an object is +its integer ID and its bounding box. Additional information needs to +be stored in separate tables and related to the R*Tree index using +the primary key. For the example above, one might create an auxiliary +table as follows: +</p> + +<div class="codeblock"><pre>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 +); +</pre></div> + +<p> +In this example, the demo_data.boundary field is intended to hold some +kind of binary representation of the precise boundaries of the object. +The R*Tree index only holds an axis-aligned rectangular boundary for the +object. The R*Tree boundary is just an approximation of the true object +boundary. So what typically happens is that the R*Tree index is used to +narrow a search down to a list of candidate objects and then more detailed +and expensive computations are done on each candidate to find if the +candidate truly meets the search criteria. +</p> + +<blockquote><p> +<strong>Key Point:</strong> +An R*Tree index does not normally provide the exact answer but merely +reduces the set of potential answers from millions to dozens. +</p></blockquote> + +<p> +Suppose the demo_data.boundary field holds some proprietary data description +of a complex two-dimensional boundary for a zipcode and suppose that the +application has used the <a href="c3ref/create_function.html">sqlite3_create_function()</a> interface to +created an application-defined function "contained_in(boundary,lat,long)" +that accepts the demo_data.boundary object and a latitute and longitude +and returns return true or false if the lat/long is contained within +the boundary. +One may assume that "contained_in()" is a relatively slow +functions that we do not want to invoke too frequently. +Then an efficient way to find the specific ZIP code for the main +SQLite office would be to run a query like this: +</p> + +<a name="diquery"></a> +<div class="codeblock"><pre>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; +</pre></div> + +<p>Notice how the query above works: The R*Tree index runs in the outer +loop to find entries that contain the SQLite main office in their +boundary box. +For each row found, SQLite looks up +the corresponding entry in the demo_data table. It then uses the boundary +field from the demo_data table as a parameter to the contained_in() +function and if that function returns true, then we know the sought after +coordinate is in that ZIP code boundary.</p> + +<p>One would get the same answer without the use of the R*Tree index +using the following simpler query:</p> + +<div class="codeblock"><pre>SELECT objname FROM demo_data + WHERE contained_in(demo_data.boundary, 35.37785, -80.77470); +</pre></div> + +<p>The problem with this latter query is that it must apply the +contained_in() function to all entries in the demo_data table. +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. +The R*Tree index did not find the exact answer itself, it merely +limited the search space.</p> + +<a name="auxcol"></a> + +<h2 id="auxiliary_columns"><span>4.1. </span>Auxiliary Columns</h2> + +<p> +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". + +</p><p> +Auxiliary columns are marked with a "+" symbol before the column name. +Auxiliary columns must come after all of the coordinate boundary columns. +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. +The following example shows an r-tree table with auxiliary columns that +is equivalent to the two tables "demo_index" and "demo_data" above: + +</p><div class="codeblock"><pre>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 +); +</pre></div> + +<p> +By combining location data and related information into the same +table, auxiliary columns can provide a cleaner model +and reduce the need to joins. +For example, the earlier +<a href="#diquery">join between demo_index and demo_data</a> can now +be written as a simple query, like this: + +</p><div class="codeblock"><pre>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; +</pre></div> + +<h3 id="limitations"><span>4.1.1. </span>Limitations</h3> + +<p> +For auxiliary columns, only the name of the column matters. +The <a href="datatype3.html#affinity">type affinity</a> is ignored. +Constraints such as NOT NULL, UNIQUE, REFERENCES, or CHECK +are also ignored. However, future versions +of SQLite might start paying attention to the type affinity and +constraints, so users of auxiliary columns are advised to leave +both blank, to avoid future compatibility problems. + +<a name="intrtree"></a> + +</p><h1 id="integer_valued_r_trees"><span>5. </span>Integer-Valued R-Trees</h1> + +<p> +The default virtual table ("rtree") stores coordinates as +single-precision (4-byte) floating point numbers. If integer coordinates +are desired, declare the table using "rtree_i32" instead: + +</p><div class="codeblock"><pre>CREATE VIRTUAL TABLE intrtree USING rtree_i32(id,x0,x1,y0,y1,z0,z1); +</pre></div> + +<p> +An rtree_i32 stores coordinates as 32-bit signed integers. +Even though it stores values using integer, the rtree_i32 virtual +table still uses floating point computations internally as part of +the r-tree algorithm. + +<a name="customquery"></a> + +</p><h1 id="custom_r_tree_queries"><span>6. </span>Custom R-Tree Queries</h1> + +<p>By using standard SQL expressions in the WHERE clause of a SELECT query, +a programmer can query for all R*Tree entries that +intersect with or are contained within a particular bounding-box. +Custom R*Tree queries, using the MATCH +operator in the WHERE clause of a SELECT, allow the programmer to query for +the set of R*Tree entries that intersect any arbitrary region or shape, not +just a box. This capability is useful, for example, in computing the +subset of objects in the R*Tree that are visible from a camera positioned +in 3-D space. + +</p><p>Regions for custom R*Tree queries are defined by R*Tree geometry callbacks +implemented by the application and registered with SQLite via a call to one +of the following two APIs: + +</p><div class="codeblock"><pre>int sqlite3_rtree_query_callback( + sqlite3 *db, + const char *zQueryFunc, + int (*xQueryFunc)(sqlite3_rtree_query_info*), + void *pContext, + void (*xDestructor)(void*) +); +int sqlite3_rtree_geometry_callback( + sqlite3 *db, + const char *zGeom, + int (*xGeom)(sqlite3_rtree_geometry *, int nCoord, double *aCoord, int *pRes), + void *pContext +); +</pre></div> + +<p>The sqlite3_rtree_query_callback() became available with SQLite +<a href="releaselog/3_8_5.html">version 3.8.5</a> (2014-06-04) and is the preferred interface. +The sqlite3_rtree_geometry_callback() is an older and less flexible +interface that is supported for backwards compatibility. + +</p><p>A call to one of the above APIs creates a new SQL function named by the +second parameter (zQueryFunc or zGeom). When that SQL function appears +on the right-hand side of the MATCH operator and the left-hand side of the +MATCH operator is any column in the R*Tree virtual table, then the callback +defined by the third argument (xQueryFunc or xGeom) is invoked to determine +if a particular object or subtree overlaps the desired region. + +</p><p>For example, a query like the following might be used to find all +R*Tree entries that overlap with a circle centered a 45.3,22.9 with a +radius of 5.0: + +</p><div class="codeblock"><pre>SELECT id FROM demo_index WHERE id MATCH circle(45.3, 22.9, 5.0) +</pre></div> + +<p>The SQL syntax for custom queries is the same regardless of which +interface, sqlite3_rtree_geometry_callback() or sqlite3_rtree_query_callback(), +is used to register the SQL function. However, the newer query-style +callbacks give the application greater control over how the query proceeds. + +</p><h2 id="the_legacy_xgeom_callback"><span>6.1. </span>The Legacy xGeom Callback</h2> + +<p>The legacy xGeom callback is invoked with four arguments. The first +argument is a pointer to an sqlite3_rtree_geometry structure which provides +information about how the SQL function was invoked. The second argument +is the number of coordinates in each r-tree entry, and is always the same +for any given R*Tree. The number of coordinates is 2 for a 1-dimensional R*Tree, +4 for a 2-dimensional R*Tree, 6 for a 3-dimensional R*Tree, and so forth. +The third argument, aCoord[], is an array of nCoord coordinates that defines +a bounding box to be tested. The last argument is a pointer into which +the callback result should be written. The result is zero +if the bounding-box defined by aCoord[] is completely outside +the region defined by the xGeom callback and the result is non-zero if +the bounding-box is inside or overlaps with the xGeom region. The xGeom +callback should normally return SQLITE_OK. If xGeom returns anything other +than SQLITE_OK, then the r-tree query will abort with an error. + +</p><p>The sqlite3_rtree_geometry structure that the first argument to the +xGeom callback points to has a structure shown below. The exact same +sqlite3_rtree_geometry +structure is used for every callback for same MATCH operator in the same +query. The contents of the sqlite3_rtree_geometry +structure are initialized by SQLite but are +not subsequently modified. The callback is free to make changes to the +pUser and xDelUser elements of the structure if desired. + +</p><div class="codeblock"><pre>typedef struct sqlite3_rtree_geometry sqlite3_rtree_geometry; +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 */ + void *pUser; /* Callback implementation user data */ + void (*xDelUser)(void *); /* Called by SQLite to clean up pUser */ +}; +</pre></div> + +<p>The pContext member of the sqlite3_rtree_geometry +structure is always set to a copy of the pContext +argument passed to sqlite3_rtree_geometry_callback() when the +callback is registered. The aParam[] array (size nParam) contains the parameter +values passed to the SQL function on the right-hand side of the MATCH operator. +In the example "circle" query above, nParam would be set to 3 and the aParam[] +array would contain the three values 45.3, 22.9 and 5.0. + +</p><p>The pUser and xDelUser members of the sqlite3_rtree_geometry structure are +initially set to NULL. The pUser variable may be set by the callback +implementation to any arbitrary value that may be useful to subsequent +invocations of the callback within the same query (for example, a +pointer to a complicated data structure used to test for region intersection). +If the xDelUser variable is set to a non-NULL value, then after the +query has finished running SQLite automatically invokes it with the +value of the pUser variable as the only argument. In other words, xDelUser +may be set to a destructor function for the pUser value. + +</p><p>The xGeom callback always does a depth-first search of the r-tree. + +<a name="xquery"></a> + +</p><h2 id="the_new_xqueryfunc_callback"><span>6.2. </span>The New xQueryFunc Callback</h2> + +<p>The newer xQueryFunc callback receives more information from the r-tree +query engine on each call, and it sends more information back to the query engine +before it returns. +To help keep the interface manageable, the xQueryFunc callback sends and receives +information from the query engine as fields in the +sqlite3_rtree_query_info structure: + +</p><div class="codeblock"><pre>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 */ + /* The following fields are only available in 3.8.11 and later */ + sqlite3_value **apSqlParam; /* Original SQL values of parameters */ +}; +</pre></div> + +<p>The first five fields of the sqlite3_rtree_query_info structure are identical +to the sqlite3_rtree_geometry structure, and have exactly the same meaning. +The sqlite3_rtree_query_info structure also contains nCoord and aCoord fields +which have the same meaning as the parameter of the same name in the xGeom callback. + +</p><p>The xQueryFunc must set the eWithin field of sqlite3_rtree_query_info to +one of the values NOT_WITHIN, PARTLY_WITHIN, or FULLY_WITHIN depending on whether +or not the bounding box defined by aCoord[] is completely outside the region, +overlaps the region, or is completely inside the region, respectively. In +addition, the xQueryFunc must set the rScore field to a non-negative value that +indicates the order in which subtrees and entries of the query should be analyzed +and returned. Smaller scores are processed first. + +</p><p>As its name implies, an R*Tree is organized as a tree. Each node of the +tree is a bounding box. The root of the tree is a bounding box that encapsulates +all elements of the tree. Beneath the root are a number of subtrees (typically +20 or more) each with their own smaller bounding boxes and each containing some +subset of the R*Tree entries. The subtrees may have sub-subtrees, and so forth +until finally one reaches the leaves of the tree which are the actual R*Tree +entries. + +</p><p>An R*Tree query is initialized by making the root node the only entry +in a priority queue sorted by rScore. +The query proceeds by extracting the entry from the priority queue that has +the lowest score. If that entry is a leaf (meaning that it is an actual +R*Tree entry and not a subtree) then that entry +is returned as one row of the query result. +If the extracted priority queue entry is a node (a subtree), +then the next child of that node is passed to the xQueryFunc callback. +If the node has more children then it is returned to the priority queue. +Otherwise it is discarded. Those subelements for which the xQueryFunc +callback sets eWithin to PARTLY_WITHIN or FULLY_WITHIN are added to the +priority queue using the score supplied by the callback. Subelements that +return NOT_WITHIN are discarded. The query runs until the priority queue is +empty. + +</p><p>Every leaf entry and node (subtree) within the R*Tree has an integer "level". +The leaves have a level of 0. The first containing subtree of the leaves has +a level of 1. The root of the R*Tree has the largest level value. The +mxLevel entry in the sqlite3_rtree_query_info structure is the level value for +the root of the R*Tree. The iLevel entry in sqlite3_rtree_query_info gives the +level for the object being interrogated. + +</p><p>Most R*Tree queries use a depth-first search. This is accomplished by setting +the rScore equal to iLevel. A depth-first search is usually preferred since it +minimizes the number of elements in the priority queue, which reduces memory +requirements and speeds processing. However, some application may prefer a +breadth-first search, which can be accomplished by setting rScore to mxLevel-iLevel. +By creating more complex formulas for rScore, applications can exercise +detailed control over the order in which subtree are searched and leaf +R*Tree entries are returned. For example, in an application with many +millions of R*Tree entries, the rScore might be arranged so that the +largest or most significant entries are returned first, allowing the +application to display the most important information quickly, and +filling in smaller and less important details as they become available. + +</p><p>Other information fields of the sqlite3_rtree_query_info structure are +available for use by the xQueryFunc callback, if desired. The iRowid field +is the rowid (the first of the 3 to 11 columns in the R*Tree) for the element +being considered. iRowid is only valid for leaves. The eParentWithin and +rParentScore values are copies of the eWithin and rScore values from the +containing subtree of the current row. The anQueue field is an array +of mxLevel+1 unsigned integers that tell the current number of elements in +the priority queue at each level. + +</p><h2 id="additional_considerations_for_custom_queries"><span>6.3. </span>Additional Considerations for Custom Queries</h2> + +<p> +The MATCH operator of a custom R*Tree query function must be a top-level +AND-connected term of the WHERE clause, or else it will not be usable +by the R*Tree query optimizer and the query will not be runnable. +If the MATCH operator is connected to other terms of the WHERE clause +via an OR operator, for example, the query will fail with an error. + +</p><p> +Two or more MATCH operators are allowed in the same WHERE clause, as long +as they are connected by AND operators. However, +the R*Tree query engine only contains a single priority queue. The priority +assigned to each node in the search is the lowest priority returned by any +of the MATCH operators. + +</p><h1 id="implementation_details"><span>7. </span>Implementation Details</h1> + +<p> +The following sections describe some low-level details of the R*Tree implementation, +that might be useful for trouble-shooting or performance analysis. + +<a name="xshadow"></a> + +</p><h2 id="shadow_tables"><span>7.1. </span>Shadow Tables</h2> + +<p>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. These +three tables are called "<a href="vtab.html#xshadowname">shadow tables</a>". This is their schema: + +</p><div class="codeblock"><pre>CREATE TABLE %_node(nodeno INTEGER PRIMARY KEY, data) +CREATE TABLE %_parent(nodeno INTEGER PRIMARY KEY, parentnode) +CREATE TABLE %_rowid(rowid INTEGER PRIMARY KEY, nodeno) +</pre></div> + +<p>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". + +</p><p>There is one entry in the %_node table for each R*Tree node. An +R*Tree node consists of one or more entries that are proximate to one another. +The nodes of an R*Tree for a tree. All nodes other than the root have an +entry in the %_parent shadow table that identifies the parent node. +Each entry in an R*Tree has a rowid. The %_rowid shadow table maps entry +rowids to the node that contains that entry. + +</p><p>Extra columns appended to the %_rowid table hold the +content of <a href="rtree.html#auxcol">auxiliary columns</a>. The names of these extra +%_rowid columns are probably not the same as the +actual auxiliary column names. + +<a name="rtreecheck"></a> + +</p><h2 id="integrity_check_using_the_rtreecheck_sql_function"><span>7.2. </span>Integrity Check using the rtreecheck() SQL function</h2> + +<p>The scalar SQL function rtreecheck(R) or rtreecheck(S,R) runs an +integrity check on the rtree table named R contained within database S. +The function returns a human-language description of any problems found, +or the string 'ok' if everything is ok. Running rtreecheck() on an R*Tree +virtual table is similar to running <a href="pragma.html#pragma_integrity_check">PRAGMA integrity_check</a> on a +database. + +</p><p>Example: To verify that an R*Tree named "demo_index" is well-formed +and internally consistent, run: + +</p><div class="codeblock"><pre>SELECT rtreecheck('demo_index'); +</pre></div> + +<p>The rtreecheck() function performs the following checks: + +</p><ol> +<li><p> +For each cell in the r-tree structure (%_node table), that: +</p><ol type="a"> +<li><p> for each dimension, (coord1 <= coord2). +</p></li><li><p> unless the cell is on the root node, that the cell is bounded + by the parent cell on the parent node. +</p></li><li><p> 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. +</p></li><li><p> 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. +</p></li></ol> +</li><li><p> +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. +</p></li><li><p> +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. +</p></li></ol> +<p align="center"><small><i>This page last modified on <a href="https://sqlite.org/docsrc/honeypot" id="mtimelink" data-href="https://sqlite.org/docsrc/finfo/pages/rtree.in?m=703d907909">2023-02-20 00:00:42</a> UTC </small></i></p> + |