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Current Oracle Spatial Blog Articles

    Using Oracle's ST_GEOMETRY type hierarchy with SDO_GEOMETRY: ST_PointN and ST_NumPoints
    Making Sdo Geometry Metadata
    SC4O Test log
    The Frontage Problem: Creating references from land parcel street frontage boundary to point in street
    Scheduling the Export of Spatial Data in Oracle to a Shapefile each night
    Oracle CENTROID package update
    Book: "Applying And Extending Oracle Spatial"
    Create Polygons and Linestrings From Bearings And Distances (COGO)
    Simple Implementation Of Travelling Salesman Problem
    ST_Densify for Object PLSQL
    PLSQL ST_AsEWKT and ST_FromWKT Functions For Oracle (any version)
    Useful Package of Wrapper Functions for Sdo_Util.AffineTransforms
    GeoRaptor 4.x Update 2 (Project has Stalled)
    Tip: Drop that Spatial Index!
    Convert Single Geometry to Multi-part Geometry in Oracle Spatial
    Optimized Rectangle to 5 Point Polygon
    Centroid Package now supports Y ordinate seeding
    Convert GeoJSON document to Sdo_Geometry objects
    Function That Returns a Compass Point From a Whole Circle Bearing
    Playing around with Centroids by using different seed values
    Simple Oracle C Sprintf or Java String.format
    Some Oriented Point Functions
    Extracting Inner Rings Changed Ordinate Ordering: A Trap For Players Who Don't Read Documentation!
    PLS-00306: wrong number or types of arguments in call to 'SDO_GEOMETRY'
    Converting Google Earth Formatted Longitude/Latitude points to decimal degrees
    Oracle Business Intelligence Warehousing and Analytics - Spatial Summit
    How far inside, is inside? Measuring actual distance.
    Noding and building a polygon from single, overlapping linestrings
    Analyzing Spatial Query Performance Improvements in Oracle Spatial and Graph 12c Through Cross-Vendor Comparison
    ST_VertexN / ST_PointN - Extracting a specific point from any geometry
    Convert Single Point stored in SDO_ORDINATES to SDO_POINT_TYPE
    Aggregate APPEND Islands and XOR polygons
    Circular Arcs in Geodetic Polygons
    Some SDO_GEOMETRY/DIMINFO handling functions
    Changing all DIMINFO sdo_tolerance values for all metadata records in one go.
    Building Polygons from Incomplete Linestrings using ST_PolygonBuilder
    Computing Cardinal Directions to nearby geometries
    Intersecting two aggregated polygon layers with SC4O
    Spatial and Oracle 12c
    Update Triggers and SDO_GEOMETRY Equality
    Duplicate Geometry data and Data Models
    CENTROID package update
    How to calculate cumulative length of a linestring
    Compute Location from known Lat/Long point using delta easting and northing in miles
    Sorting SDO_GEOMETRY data using the ORDER BY clause of a SELECT statement
    Creating linestrings from points
    Rounding Coordinates or Ordinates in SDO_GEOMETRY
    Effects of Sdo_Geometry Ordinate Precision on Performance
    Effects of Sdo_Geometry Ordinate Precision on Storage
    The Spatial filtering of geometries: The effect of tolerances on relationships
    Application of Delaunay Triangulation and Inverse Distance Weighting (IDW) in Oracle for Soils Interpolation
    Selecting all SDO_GTYPE values for all tables/sdo_geometry columns in a schema
    CENTROID package - Tips for Use
    Announcing the Spatial Companion For Oracle (SC4O)
    Filtering Rings (Oracle Spatial)
    Splitting a polygon using one or more linestrings
    isValid, isSimple, Dimension and CoordDim methods for SDO_Geometry
    Line Merging or Collecting lines together: ST_LineMerger
    ST_DeleteVertex for Oracle SDO_Geometry based on Jaspa/JTS
    3D/4D and SRID aware Conversion functions for SDO_Geometry: WKT and EWKT
    Topological vs Non-Topological Simplification/Generalization of Aggregated Area Geometies in Oracle
    Filtering very short linestrings via bitmap function index
    CENTROID For Oracle
    Gridding a sdo_geometry line/polygon object (Oracle)
    Finding centre and radius of a circular geometry
    Constraining geometry type for sdo_geometry column in a table.
    CASE Statements and SDO_GEOMETRY
    The Power of Constraints and Indexes for Spatial Constraints: stopping duplicate points
    Replacement for SDO_GEOM.RELATE - ST_Relate based on JTS
    Changing Oracle Spatial Index Parameters on existing index
    Writing Excel Spreadsheets files from within the Oracle database using Java and PL/SQL
    Writing xSV (eg csv) files from within the Oracle database using Java and PL/SQL
    A simple spike finder for Spatial/Locator
    JTS Java class compilation for 11g and above
    Random Spatial Search Procedure
    Geometry Snapping using JTS in Oracle
    Exposing JTS's MinimumBoundingCircle functionality
    Exposing JTS's Densifier functionality
    Using JTS's Comparison Functions - HausdorffSimilarityMeasure & AreaSimilarityMeasure with SDO_GEOMETRY
    Free JTS-based Area/Length Functions
    Handy way of systematically fixing polygon geometries with 13349 and other errors
    Standalone CENTROID package now available for download
    Free Union, Intersection, Xor and Difference Functions for Oracle Locator - Part 4 Processing Geodetic data
    Configurable Buffer: JTS and Oracle
    Free Union, Intersection, Xor and Difference Functions for Oracle Locator - Part 3
    Free Union, Intersection, Xor and Difference Functions for Oracle Locator - Part 2
    Free Union, Intersection, Xor and Difference Functions for Oracle Locator - Part 1
    Building Lines into Polygons in Oracle Locator / Spatial
    Finding Intersection Points between Line and Polygon
    Free version of sdo_length
    Alternative to my SQL based GetNumRings function
    External Tables and SDO_Geometry data.
    layer_gtype keyword issue when indexing linear data on 11g
    String Tokenizer for Oracle
    Free Aggregate Method for Concatenating 2D Lines in Oracle Locator 10g
    Reducing 5 Vertex Polygon to Optimized Rectangle
    Square Buffer
    Converting decimal seconds to string
    Valid conversion unit values for Oracle sdo_geom.sdo_length()
    Removing Steps in Gridded Vector Data - SmoothGrid for Oracle
    Oracle Spatial DISJOINT search/filtering
    Creating SDO_Geometry from geometric data recorded in the columns of a table
    Concave Hull Geometries in Oracle 11gR2
    Projecting SDO_GEOM_METADATA DIMINFO XY ordinates
    Instantiating MDSYS.VERTEX_TYPE
    New PL/SQL Packages - Rotate oriented point
    GeoRaptor Development Team
    Fast Refreshing Materialized View Containing SDO_GEOMETRY and SDO_GEOM.SDO_AREA function
    Performance of PL/SQL Functions using SQL vs Pure Code
    Implementing the BEST VicGrid Projection in Oracle 10gR2
    ORA-13011 errors when using SDO_GEOM.VALIDATE_LAYER_WITH_CONTEXT()
    Extract Polygons from Compound Polygon
    Detecting sdo_geometries with compound (3-point Arcs) segments
    GEOMETRY_COLUMNS for Oracle Spatial
    Convert GML to SDO_Geometry in Oracle 10gR2
    Spatial Sorting of Data via Morton Key
    Swapping Ordinates in an SDO_GEOMETRY object
    New To_3D Function
    Extend (Reduce/Contract/Skrink) Function for Oracle
    Loading and Processing GPX 1.1 files using Oracle XMLDB
    Loading Spatial Data from an external CSV file in Oracle
    Calling the Oracle Spatial shapefile loader from within the Oracle database itself
    Implementing SDO_VertexUpdate/ST_VertexUpdate for Oracle
    Implementing SDO_RemovePoint/ST_RemovePoint for Oracle
    Implementing SDO_AddPoint/ST_AddPoint for Oracle
    ESRI ArcSDE Exverted and Inverted Polygons and Oracle Spatial
    Funky Fix Ordinates By Formula
    Implementing a SetPoint/ST_SetPoint function in Oracle
    Implementing an ST_SnapToGrid (PostGIS) function for Oracle Spatial
    Generating random point data
    Implementing an Affine/ST_Affine function for Oracle Spatial
    Implementing a Scale/ST_Scale function for Oracle Spatial
    Implementing a Parallel/ST_Parallel function for linestring data for Oracle Spatial
    Implementing a Rotate/ST_Rotate function for Oracle Spatial
    Limiting table list returned when connecting to Oracle Database using ODBC
    ST_Azimuth for Oracle: AKA Cogo.Bearing
    Implementing a Translate/ST_Translate/Move function for Oracle Spatial
    Elem_Info_Array Processing: An alternative to SDO_UTIL.GetNumRings and querying SDO_ELEM_INFO itself
    Minumum Bounding Rectangle (MBR) Object Type for Oracle
    How to extract elements from the result of an sdo_intersection of two polygons.
    How to restart a database after failed parameter change
    Fixing failed spatial indexes after import using data pump
    generate_series: an Oracle implementation in light of SQL Design Patterns
    Multi-Centroid Shootout
    Oracle Spatial Centroid Shootout
    On the use of ROLLUP in Oracle SELECT statements
    Surrounding Parcels
    Spatial Pipelining
    Using Oracle's SDO_NN Operator - Some examples
    Converting distances and units of measure in Oracle Locator
    Split Sdo_Geometry Linestring at a known point
    Forcing an Sdo_Geometry object to contain only points, lines or areas
    Unpacking USER_SDO_GEOM_METADATA's DIMINFO structure using SQL
    Generating multi-points from single point records in Oracle Spatial
    Object Tables of Sdo_Geometry
    Oracle Locator vs Oracle Spatial: A Reflection on Oracle Licensing of the SDO_GEOM Package
    FAST REFRESHing of Oracle Materialized Views containing Sdo_Geometry columns
    Australian MGA/AMG Zone Calculation from geographic (longitude/latitude) data
    Loading Shapefiles (SHP) into Oracle Spatial
    Oracle Spatial Mapping and Map Rendering Performance Tips
    The significance of sdo_lb/sdo_ub in USER_SDO_GEOM_METDATA: Do I need it?
    Oracle Spatial Forum - Melbourne April 2007
    Layer_GTypes for spatial indexes
    Oracle's SQL/MM Compliant Types
    Tips and Tricks



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All Blog Articles, Data Models and Free Source Code by Simon Greener, The SpatialDB Advisor is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.

Spatial Pipelining

Tuesday February 12 2008 at 06:53

Keywordsvectorising pipelining sdo_geometry

This technical blog article describes the benefits in using pipelined functions in Oracle to manipulate sdo_geometry objects. In doing so it will describe a number of functions available in the COGO and GEOM packages in the PL/SQL packages I make available for a free download from this site.

What I will do is introduce a realistic “business need” and then show how to construct a non-pipelined function that can be used in implementing that need. I will also create a pipelined version of the function and “compare and contrast” the two approaches in terms of memory use and performance.

Business Need

Imagine a company has a large Oracle Spatial database in which are stored land parcel (land record) polygons. The company would like to be able to display the bearings and distances (metes and bounds) of each boundary of each polygon dynamically by not relying on a second layer of sdo_geometry linestrings. This is displayed pictorially as follows.

Business Requirement: Dynamic bearings and distances

How can we achieve this?

Steps to create table

First let’s start by creating a table and populating it.

CREATE TABLE land_parcel (
 gid  INTEGER,

INSERT INTO land_parcel 
       SDO_GEOMETRY(2003, NULL, NULL, 

INSERT INTO user_sdo_geom_metadata 

Vector Elements

Now we need a method for accessing the individual lines that make up our sdo_geometry polygon. For this we will need a function that takes the polygon and splits it up into its constituent vectors (where a vector is defined as being a linestring made up of only a starting and ending vertex).

First we create a vector data structure as follows:


  startCoord Coord2DType,
  endCoord   Coord2DType 

Once defined we can now create a set of vectors (to hold all those in any one land parcel polygon) as follows:


Finally, having created our data structures we can create our function. The one I created in my GEOM package is GetVector2D. Its essentials (for a full implementation see my packages) are:

FUNCTION GetVector2D ( p_geometry IN mdsys.sdo_geometry)
    vectors Vector2DSetType := Vector2DSetType();
  WHILE v_partToProcess Loop
    IF v_vertex = 1 THEN
      v_vector := vectors.LAST;
      vectors(v_vector) := Vector2DType(Coord2DType(-1,1),Coord2DType(-1,1));
      vectors(v_vector).startCoord.x := v_coord.x;
      vectors(v_vector).startCoord.y := v_coord.y;
      vectors(v_vector).endCoord.x := v_coord.x;
      vectors(v_vector).endCoord.y := v_coord.y;
      v_vector := vectors.LAST;
      vectors(v_vector) := Vector2DType(Coord2DType(-1,1),Coord2DType(-1,1));
      vectors(v_vector).startCoord.x := v_coord.x;
      vectors(v_vector).startCoord.y := v_coord.y;
    END IF;
  RETURN vectors;

Finally, we will need two functions that, given a single vector, can return a bearing and distance. I won’t go into the details of how to do this, all I will do is point out that, in my COGO package, are two functions:

    FUNCTION Bearing( dE1 in number,
                      dN1 in number,
                      dE2 in number,
                      dN2 in number)
    FUNCTION Distance( dE1 in number,
                       dN1 in number,
                       dE2 in number,
                       dN2 in number)

(In the CONSTANTS package is a definition of PI which we will also use.)


Now we can construct a view that will take a land parcel (or set of land parcels) and return the vectors that compose it. From these vectors we will create sdo_geometry linestrings and also columns containing the bearings and distances computed from those vectors.

CREATE OR REPLACE VIEW metes_and_bounds
SELECT rownum AS gid,
              (180/codesys.Constants.PI) )
              AS bearing,
              AS distance,
              AS geometry
  FROM ( SELECT DISTINCT c.StartCoord.X AS startX,
                         c.StartCoord.Y AS startY,
                         c.EndCoord.X AS endX,
                         c.EndCoord.Y AS endY
           FROM land_parcel a,
                TABLE(codesys.Geom.GetVector2D(a.geom)) c

Note that all the “heavy lifting” is done by the GetVector2D function that returns a set of vectors into the TABLE disaggregator.

Finally, if the land_parcel table held a lot of records, we should really consider using a fast refreshable materialized view instead and create a spatial index over its geom column. This is because we cannot create a function based index over the above view.

Pipelining and Pipelined Functions

OK, so we can now implement our business requirement. Why do we need to go further?

We should always be on the lookout for performance improvements even in these days of fast computer hardware. This is because, in any organisation, database servers are shared across multiple databases and accessed by multiple applications and users. Anything we can do to reduce our application “footprint” helps all who use the resource. Pipelining is one method of improving the performance and memory use of a function.

Firstly, what is a pipelined function?

Tom Kyte says in this article that:

Pipelined functions are simply code that you can pretend is a database table.
Pipelined functions give you the (amazing, to me) ability to use


A pipelined function needs to return a collection type …

In fact it is


In the metes_and_bounds view above we have used a function that returns a collection type (Vector2DSetType) inside a TABLE function. This is allowed, but this is still not a pipelined function!

Let’s turn it into a pipelined function and then I can explain the difference.

FUNCTION GetVector2D ( p_geometry IN mdsys.sdo_geometry)
    v_vector         codesys.Vector2DType := codesys.Vector2DType(
  WHILE v_partToProcess Loop
    IF v_vertex = 1 THEN
      v_vector.startCoord.x := v_coord.x;
      v_vector.startCoord.y := v_coord.y;
      v_vector.endCoord.x := v_coord.x;
      v_vector.endCoord.y := v_coord.y;
      PIPE ROW(v_vector);
      v_vector := vectors.LAST;
      v_vector.startCoord.x := v_coord.x;
      v_vector.startCoord.y := v_coord.y;
    END IF;

The three points of difference are:

  1. The definition of the function uses the PIPELINED keyword rather than the DETERMINISTIC keyword.
  2. Instead of allocating memory as in the use of EXTEND on the
    private collection variable vectors (EXEND will allocate memory) in the pipelined function a single vector is simply pushed into the pipeline as it is constructed.
  3. In the pipelined function no variable is returned using the final RETURN statement; in the non-pipelined function the local collection variable, vectors, which holds all vector objects constructed during function execution are return as one.

So, fairly obviously, a function is pipelined if it uses the PIPELINED keyword and pushes what it creates into the pipe via the PIPE ROW statement as they are created.

The big thing to notice is that very little memory is created or used by the pipelined function whereas the non-pipelined function has to allocated memory to hold all the vector objects until the function’s end. Because the non-piplined function waits until the end before it can return its results, the calling SELECT statement itself if forced to wait before it can do any processing: not so with the pipelined function. The Oracle 10gR2 help confirms this:

Rows from a collection returned by a table function can also be pipelined, that is, iteratively returned as they are produced instead of in a batch after all processing of the table function’s input is completed.

That help also outlines the benefits of pipelining:

Streaming, pipelining, and parallel execution of table functions can improve performance:

  • By enabling multithreaded, concurrent execution of table functions
  • By eliminating intermediate staging between processes
  • By improving query response time: With non-pipelined table functions, the entire collection returned by a table function must be constructed and returned to the server before the query can return a single result row. Pipelining enables rows to be returned iteratively, as they are produced. This also reduces the memory that a table function requires, as the object cache does not need to materialize the entire collection.
  • By iteratively providing result rows from the collection returned by a table function as the rows are produced instead of waiting until the entire collection is staged in tables or memory and then returning the entire collectio

Demonstration of Performance Improvements

With the land_parcel table above we don’t have enough objects to demonstrate the performance improvements the pipelined function has over the non-pipelined function. So, I used some customer data (I have permission for this).

SELECT count(*)
  FROM parcel;


CREATE TABLE pipelined_version
SELECT rownum AS gid,
       AS geometry
                c.StartCoord.X AS startX,
                c.StartCoord.Y AS startY,
                c.EndCoord.X AS endX,
                c.EndCoord.Y AS endY
           FROM ( SELECT geometry
                    FROM SP_PARCEL
                ) a,
                TABLE(codesys.Geom.Get{Piped}Vector2D(a.geometry)) c

Note that I run this statement twice with the braces {} removed.



Performance numbers were:

Function TimeInSeconds
GetVector2D 02:18.13
GetPipedVector2D 00:47.90

In summary, pipelining improved the performance of the operation by 287% ( ( 1 / ( 48 / 138 ) * 100 ). Now that is quite an improvement even for this small amount of data. I have used this GetPipedVector2D function on some huge spatial datasets and have seen such substantial performance improvements I now use them in preference to previous techniques (I have left the previous implementations in my PL/SQL packages as occasionally they are useful).

I hope this little article helped whet your appetite for pipelined table functions in Oracle Spatial.

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Comment [2]

In your explanation on using a spatial pipelined function in Oracle. This has the benefits you describe but the resulting “table” cannot be used with other spatial operators such as SDO_CONTAINS. The problem I surmise is that these spatial functions cannot determine the projection that is used. Seeing as that the projection meta data is kept in the “user_sdo_geom_metadata” table based on the table’s name and SDO_GEOMETRY column it cannot find that information.

I was hoping you might have some further insight into the workings of the Oracle database in this manner.

Wouter Storteboom 19 August 2013, 15:56 #


I can’t visualise what you mean.

All geoprocessing functions can take a tolerance as a number or as an diminfo.

Can you supply me an example?


Simon Greener 24 August 2013, 03:09 #