mirror of
https://git.postgresql.org/git/postgresql.git
synced 2024-12-03 08:00:21 +08:00
80b3513d57
directly from float8 values. (As opposed to converting the values to strings and then parsing the strings.) The functions are: cube(float8) returns cube cube(float8,float8) returns cube cube(cube,float8) returns cube cube(cube,float8,float8) returns cube Bruno Wolff III |
||
---|---|---|
.. | ||
data | ||
expected | ||
sql | ||
buffer.c | ||
buffer.h | ||
CHANGES | ||
cube.c | ||
cube.sql.in | ||
cubedata.h | ||
cubeparse.y | ||
cubescan.l | ||
Makefile | ||
README.cube |
This directory contains the code for the user-defined type, CUBE, representing multidimensional cubes. FILES ----- Makefile building instructions for the shared library README.cube the file you are now reading buffer.c globals and buffer access utilities shared between the parser (cubeparse.y) and the scanner (cubescan.l) buffer.h function prototypes for buffer.c cube.c the implementation of this data type in c cube.sql.in SQL code needed to register this type with postgres (transformed to cube.sql by make) cubedata.h the data structure used to store the cubes cubeparse.y the grammar file for the parser (used by cube_in() in cube.c) cubescan.l scanner rules (used by cube_yyparse() in cubeparse.y) INSTALLATION ============ To install the type, run make make install For this to work, make sure that: . the cube source directory is in the postgres contrib directory . the user running "make install" has postgres administrative authority . this user's environment defines the PGLIB and PGDATA variables and has postgres binaries in the PATH. This only installs the type implementation and documentation. To make the type available in any particular database, as a postgres superuser do: psql -d databasename < cube.sql If you install the type in the template1 database, all subsequently created databases will inherit it. To test the new type, after "make install" do make installcheck If it fails, examine the file regression.diffs to find out the reason (the test code is a direct adaptation of the regression tests from the main source tree). By default the external functions are made executable by anyone. SYNTAX ====== The following are valid external representations for the CUBE type: 'x' A floating point value representing a one-dimensional point or one-dimensional zero length cubement '(x)' Same as above 'x1,x2,x3,...,xn' A point in n-dimensional space, represented internally as a zero volume box '(x1,x2,x3,...,xn)' Same as above '(x),(y)' 1-D cubement starting at x and ending at y or vice versa; the order does not matter '(x1,...,xn),(y1,...,yn)' n-dimensional box represented by a pair of its opposite corners, no matter which. Functions take care of swapping to achieve "lower left -- upper right" representation before computing any values Grammar ------- rule 1 box -> O_BRACKET paren_list COMMA paren_list C_BRACKET rule 2 box -> paren_list COMMA paren_list rule 3 box -> paren_list rule 4 box -> list rule 5 paren_list -> O_PAREN list C_PAREN rule 6 list -> FLOAT rule 7 list -> list COMMA FLOAT Tokens ------ n [0-9]+ integer [+-]?{n} real [+-]?({n}\.{n}?|\.{n}) FLOAT ({integer}|{real})([eE]{integer})? O_BRACKET \[ C_BRACKET \] O_PAREN \( C_PAREN \) COMMA \, Examples of valid CUBE representations: -------------------------------------- 'x' A floating point value representing a one-dimensional point (or, zero-length one-dimensional interval) '(x)' Same as above 'x1,x2,x3,...,xn' A point in n-dimensional space, represented internally as a zero volume cube '(x1,x2,x3,...,xn)' Same as above '(x),(y)' A 1-D interval starting at x and ending at y or vice versa; the order does not matter '[(x),(y)]' Same as above '(x1,...,xn),(y1,...,yn)' An n-dimensional box represented by a pair of its diagonally opposite corners, regardless of order. Swapping is provided by all comarison routines to ensure the "lower left -- upper right" representation before actaul comparison takes place. '[(x1,...,xn),(y1,...,yn)]' Same as above White space is ignored, so '[(x),(y)]' can be: '[ ( x ), ( y ) ]' DEFAULTS ======== I believe this union: select cube_union('(0,5,2),(2,3,1)','0'); cube_union ------------------- (0, 0, 0),(2, 5, 2) (1 row) does not contradict to the common sense, neither does the intersection select cube_inter('(0,-1),(1,1)','(-2),(2)'); cube_inter ------------- (0, 0),(1, 0) (1 row) In all binary operations on differently sized boxes, I assume the smaller one to be a cartesian projection, i. e., having zeroes in place of coordinates omitted in the string representation. The above examples are equivalent to: cube_union('(0,5,2),(2,3,1)','(0,0,0),(0,0,0)'); cube_inter('(0,-1),(1,1)','(-2,0),(2,0)'); The following containment predicate uses the point syntax, while in fact the second argument is internally represented by a box. This syntax makes it unnecessary to define the special Point type and functions for (box,point) predicates. select cube_contains('(0,0),(1,1)', '0.5,0.5'); cube_contains -------------- t (1 row) PRECISION ========= Values are stored internally as 64-bit floating point numbers. This means that numbers with more than about 16 significant digits will be truncated. USAGE ===== The access method for CUBE is a GiST (gist_cube_ops), which is a generalization of R-tree. GiSTs allow the postgres implementation of R-tree, originally encoded to support 2-D geometric types such as boxes and polygons, to be used with any data type whose data domain can be partitioned using the concepts of containment, intersection and equality. In other words, everything that can intersect or contain its own kind can be indexed with a GiST. That includes, among other things, all geometric data types, regardless of their dimensionality (see also contrib/seg). The operators supported by the GiST access method include: [a, b] << [c, d] Is left of The left operand, [a, b], occurs entirely to the left of the right operand, [c, d], on the axis (-inf, inf). It means, [a, b] << [c, d] is true if b < c and false otherwise [a, b] >> [c, d] Is right of [a, b] is occurs entirely to the right of [c, d]. [a, b] >> [c, d] is true if b > c and false otherwise [a, b] &< [c, d] Over left The cubement [a, b] overlaps the cubement [c, d] in such a way that a <= c <= b and b <= d [a, b] &> [c, d] Over right The cubement [a, b] overlaps the cubement [c, d] in such a way that a > c and b <= c <= d [a, b] = [c, d] Same as The cubements [a, b] and [c, d] are identical, that is, a == b and c == d [a, b] @ [c, d] Contains The cubement [a, b] contains the cubement [c, d], that is, a <= c and b >= d [a, b] @ [c, d] Contained in The cubement [a, b] is contained in [c, d], that is, a >= c and b <= d Although the mnemonics of the following operators is questionable, I preserved them to maintain visual consistency with other geometric data types defined in Postgres. Other operators: [a, b] < [c, d] Less than [a, b] > [c, d] Greater than These operators do not make a lot of sense for any practical purpose but sorting. These operators first compare (a) to (c), and if these are equal, compare (b) to (d). That accounts for reasonably good sorting in most cases, which is useful if you want to use ORDER BY with this type The following functions are available: cube_distance(cube, cube) returns double cube_distance returns the distance between two cubes. If both cubes are points, this is the normal distance function. cube(text) returns cube cube takes text input and returns a cube. This is useful for making cubes from computed strings. cube(float8) returns cube This makes a one dimensional cube with both coordinates the same. If the type of the argument is a numeric type other than float8 an explicit cast to float8 may be needed. cube(1) == '(1)' cube(float8, float8) returns cube This makes a one dimensional cube. cube(1,2) == '(1),(2)' cube(cube, float8) returns cube This builds a new cube by adding a dimension on to an existing cube with the same values for both parts of the new coordinate. This is useful for building cubes piece by piece from calculated values. cube('(1)',2) == '(1,2),(1,2)' cube(cube, float8, float8) returns cube This builds a new cube by adding a dimension on to an existing cube. This is useful for building cubes piece by piece from calculated values. cube('(1,2)',3,4) == '(1,3),(2,4)' cube_dim(cube) returns int cube_dim returns the number of dimensions stored in the the data structure for a cube. This is useful for constraints on the dimensions of a cube. cube_ll_coord(cube, int) returns double cube_ll_coord returns the nth coordinate value for the lower left corner of a cube. This is useful for doing coordinate transformations. cube_ur_coord(cube, int) returns double cube_ur_coord returns the nth coordinate value for the upper right corner of a cube. This is useful for doing coordinate transformations. cube_is_point(cube) returns bool cube_is_point returns true if a cube is also a point. This is true when the two defining corners are the same. cube_enlarge(cube, double, int) returns cube cube_enlarge increases the size of a cube by a specified radius in at least n dimensions. If the radius is negative the box is shrunk instead. This is useful for creating bounding boxes around a point for searching for nearby points. All defined dimensions are changed by the radius. If n is greater than the number of defined dimensions and the cube is being increased (r >= 0) then 0 is used as the base for the extra coordinates. LL coordinates are decreased by r and UR coordinates are increased by r. If a LL coordinate is increased to larger than the corresponding UR coordinate (this can only happen when r < 0) than both coordinates are set to their average. To make it harder for people to break things there is an effective maximum on the dimension of cubes of 100. This is set in cubedata.h if you need something bigger. There are a few other potentially useful functions defined in cube.c that vanished from the schema because I stopped using them. Some of these were meant to support type casting. Let me know if I was wrong: I will then add them back to the schema. I would also appreciate other ideas that would enhance the type and make it more useful. For examples of usage, see sql/cube.sql CREDITS ======= This code is essentially based on the example written for Illustra, http://garcia.me.berkeley.edu/~adong/rtree My thanks are primarily to Prof. Joe Hellerstein (http://db.cs.berkeley.edu/~jmh/) for elucidating the gist of the GiST (http://gist.cs.berkeley.edu/), and to his former student, Andy Dong (http://best.me.berkeley.edu/~adong/), for his exemplar. I am also grateful to all postgres developers, present and past, for enabling myself to create my own world and live undisturbed in it. And I would like to acknowledge my gratitude to Argonne Lab and to the U.S. Department of Energy for the years of faithful support of my database research. ------------------------------------------------------------------------ Gene Selkov, Jr. Computational Scientist Mathematics and Computer Science Division Argonne National Laboratory 9700 S Cass Ave. Building 221 Argonne, IL 60439-4844 selkovjr@mcs.anl.gov ------------------------------------------------------------------------ Minor updates to this package were made by Bruno Wolff III <bruno@wolff.to> in August/September of 2002. These include changing the precision from single precision to double precision and adding some new functions.