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321 lines
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Plaintext
321 lines
10 KiB
Plaintext
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This directory contains the code for the user-defined type,
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SEG, representing laboratory measurements as floating point
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intervals.
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RATIONALE
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=========
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The geometry of measurements is usually more complex than that of a
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point in a numeric continuum. A measurement is usually a segment of
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that continuum with somewhat fuzzy limits. The measurements come out
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as intervals because of uncertainty and randomness, as well as because
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the value being measured may naturally be an interval indicating some
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condition, such as the temperature range of stability of a protein.
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Using just common sense, it appears more convenient to store such data
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as intervals, rather than pairs of numbers. In practice, it even turns
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out more efficient in most applications.
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Further along the line of common sense, the fuzziness of the limits
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suggests that the use of traditional numeric data types leads to a
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certain loss of information. Consider this: your instrument reads
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6.50, and you input this reading into the database. What do you get
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when you fetch it? Watch:
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test=> select 6.50 as "pH";
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pH
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---
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6.5
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(1 row)
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In the world of measurements, 6.50 is not the same as 6.5. It may
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sometimes be critically different. The experimenters usually write
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down (and publish) the digits they trust. 6.50 is actually a fuzzy
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interval contained within a bigger and even fuzzier interval, 6.5,
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with their center points being (probably) the only common feature they
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share. We definitely do not want such different data items to appear the
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same.
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Conclusion? It is nice to have a special data type that can record the
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limits of an interval with arbitrarily variable precision. Variable in
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a sense that each data element records its own precision.
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Check this out:
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test=> select '6.25 .. 6.50'::seg as "pH";
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pH
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------------
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6.25 .. 6.50
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(1 row)
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FILES
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=====
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Makefile building instructions for the shared library
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README.seg the file you are now reading
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seg.c the implementation of this data type in c
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seg.sql.in SQL code needed to register this type with postgres
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(transformed to seg.sql by make)
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segdata.h the data structure used to store the segments
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segparse.y the grammar file for the parser (used by seg_in() in seg.c)
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segscan.l scanner rules (used by seg_yyparse() in segparse.y)
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seg-validate.pl a simple input validation script. It is probably a
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little stricter than the type itself: for example,
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it rejects '22 ' because of the trailing space. Use
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as a filter to discard bad values from a single column;
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redirect to /dev/null to see the offending input
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sort-segments.pl a script to sort the tables having a SEG type column
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INSTALLATION
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============
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To install the type, run
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make
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make install
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For this to work, make sure that:
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. the seg source directory is in the postgres contrib directory
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. the user running "make install" has postgres administrative authority
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. this user's environment defines the PGLIB and PGDATA variables and has
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postgres binaries in the PATH.
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This only installs the type implementation and documentation. To make the
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type available in any particular database, do
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psql -d databasename < seg.sql
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If you install the type in the template1 database, all subsequently created
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databases will inherit it.
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To test the new type, after "make install" do
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make installcheck
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If it fails, examine the file regression.diffs to find out the reason (the
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test code is a direct adaptation of the regression tests from the main
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source tree).
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SYNTAX
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======
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The external representation of an interval is formed using one or two
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floating point numbers joined by the range operator ('..' or '...').
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Optional certainty indicators (<, > and ~) are ignored by the internal
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logics, but are retained in the data.
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Grammar
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-------
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rule 1 seg -> boundary PLUMIN deviation
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rule 2 seg -> boundary RANGE boundary
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rule 3 seg -> boundary RANGE
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rule 4 seg -> RANGE boundary
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rule 5 seg -> boundary
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rule 6 boundary -> FLOAT
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rule 7 boundary -> EXTENSION FLOAT
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rule 8 deviation -> FLOAT
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Tokens
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------
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RANGE (\.\.)(\.)?
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PLUMIN \'\+\-\'
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integer [+-]?[0-9]+
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real [+-]?[0-9]+\.[0-9]+
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FLOAT ({integer}|{real})([eE]{integer})?
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EXTENSION [<>~]
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Examples of valid SEG representations:
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--------------------------------------
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Any number (rules 5,6) -- creates a zero-length segment (a point,
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if you will)
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~5.0 (rules 5,7) -- creates a zero-length segment AND records
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'~' in the data. This notation reads 'approximately 5.0',
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but its meaning is not recognized by the code. It is ignored
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until you get the value back. View it is a short-hand comment.
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<5.0 (rules 5,7) -- creates a point at 5.0; '<' is ignored but
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is preserved as a comment
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>5.0 (rules 5,7) -- creates a point at 5.0; '>' is ignored but
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is preserved as a comment
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5(+-)0.3
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5'+-'0.3 (rules 1,8) -- creates an interval '4.7..5.3'. As of this
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writing (02/09/2000), this mechanism isn't completely accurate
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in determining the number of significant digits for the
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boundaries. For example, it adds an extra digit to the lower
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boundary if the resulting interval includes a power of ten:
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template1=> select '10(+-)1'::seg as seg;
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seg
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---------
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9.0 .. 11 -- should be: 9 .. 11
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Also, the (+-) notation is not preserved: 'a(+-)b' will
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always be returned as '(a-b) .. (a+b)'. The purpose of this
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notation is to allow input from certain data sources without
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conversion.
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50 .. (rule 3) -- everything that is greater than or equal to 50
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.. 0 (rule 4) -- everything that is less than or equal to 0
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1.5e-2 .. 2E-2 (rule 2) -- creates an interval (0.015 .. 0.02)
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1 ... 2 The same as 1...2, or 1 .. 2, or 1..2 (space is ignored).
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Because of the widespread use of '...' in the data sources,
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I decided to stick to is as a range operator. This, and
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also the fact that the white space around the range operator
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is ignored, creates a parsing conflict with numeric constants
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starting with a decimal point.
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Examples of invalid SEG input:
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------------------------------
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.1e7 should be: 0.1e7
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.1 .. .2 should be: 0.1 .. 0.2
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2.4 E4 should be: 2.4E4
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The following, although it is not a syntax error, is disallowed to improve
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the sanity of the data:
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5 .. 2 should be: 2 .. 5
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PRECISION
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=========
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The segments are stored internally as pairs of 32-bit floating point
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numbers. It means that the numbers with more than 7 significant digits
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will be truncated.
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The numbers with less than or exactly 7 significant digits retain their
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original precision. That is, if your query returns 0.00, you will be
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sure that the trailing zeroes are not the artifacts of formatting: they
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reflect the precision of the original data. The number of leading
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zeroes does not affect precision: the value 0.0067 is considered to
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have just 2 significant digits.
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USAGE
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=====
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The access method for SEG is a GiST (gist_seg_ops), which is a
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generalization of R-tree. GiSTs allow the postgres implementation of
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R-tree, originally encoded to support 2-D geometric types such as
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boxes and polygons, to be used with any data type whose data domain
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can be partitioned using the concepts of containment, intersection and
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equality. In other words, everything that can intersect or contain
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its own kind can be indexed with a GiST. That includes, among other
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things, all geometric data types, regardless of their dimensionality
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(see also contrib/cube).
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The operators supported by the GiST access method include:
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[a, b] << [c, d] Is left of
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The left operand, [a, b], occurs entirely to the left of the
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right operand, [c, d], on the axis (-inf, inf). It means,
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[a, b] << [c, d] is true if b < c and false otherwise
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[a, b] >> [c, d] Is right of
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[a, b] is occurs entirely to the right of [c, d].
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[a, b] >> [c, d] is true if b > c and false otherwise
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[a, b] &< [c, d] Over left
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The segment [a, b] overlaps the segment [c, d] in such a way
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that a <= c <= b and b <= d
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[a, b] &> [c, d] Over right
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The segment [a, b] overlaps the segment [c, d] in such a way
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that a > c and b <= c <= d
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[a, b] = [c, d] Same as
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The segments [a, b] and [c, d] are identical, that is, a == b
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and c == d
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[a, b] @ [c, d] Contains
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The segment [a, b] contains the segment [c, d], that is,
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a <= c and b >= d
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[a, b] @ [c, d] Contained in
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The segment [a, b] is contained in [c, d], that is,
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a >= c and b <= d
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Although the mnemonics of the following operators is questionable, I
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preserved them to maintain visual consistency with other geometric
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data types defined in Postgres.
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Other operators:
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[a, b] < [c, d] Less than
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[a, b] > [c, d] Greater than
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These operators do not make a lot of sense for any practical
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purpose but sorting. These operators first compare (a) to (c),
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and if these are equal, compare (b) to (d). That accounts for
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reasonably good sorting in most cases, which is useful if
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you want to use ORDER BY with this type
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There are a few other potentially useful functions defined in seg.c
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that vanished from the schema because I stopped using them. Some of
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these were meant to support type casting. Let me know if I was wrong:
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I will then add them back to the schema. I would also appreciate
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other ideas that would enhance the type and make it more useful.
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For examples of usage, see sql/seg.sql
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NOTE: The performance of an R-tree index can largely depend on the
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order of input values. It may be very helpful to sort the input table
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on the SEG column (see the script sort-segments.pl for an example)
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CREDITS
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=======
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My thanks are primarily to Prof. Joe Hellerstein
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(http://db.cs.berkeley.edu/~jmh/) for elucidating the gist of the GiST
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(http://gist.cs.berkeley.edu/). I am also grateful to all postgres
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developers, present and past, for enabling myself to create my own
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world and live undisturbed in it. And I would like to acknowledge my
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gratitude to Argonne Lab and to the U.S. Department of Energy for the
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years of faithful support of my database research.
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------------------------------------------------------------------------
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Gene Selkov, Jr.
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Computational Scientist
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Mathematics and Computer Science Division
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Argonne National Laboratory
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9700 S Cass Ave.
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Building 221
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Argonne, IL 60439-4844
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selkovjr@mcs.anl.gov
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