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# tile4ms

## Purpose

Creates a tile index Shape data set for use with MapServer’s TILEINDEX feature. The program creates a Shape data set of rectangles from extents of all the Shape data sets listed in [metafile] (one Shape data set name per line) and the associated DBF with the filename for each shape tile in a column called LOCATION as required by mapserv.

Note

Similar functionality can be found in the GDAL commandline utilities ogrtindex (for vectors) and gdaltindex (for rasters).

## Description

This utility creates a Shape data set containing the MBR (minimum bounding rectangle) of all shapes in the files provided, which can then be used in the LAYER object’s TILEINDEX parameter of the mapfile. The new filed created with this command is used by MapServer to only load the files associated with that extent (or tile).

## Syntax

    tile4ms <meta-file> <tile-file> [-tile-path-only]
    <meta-file>     INPUT  file containing list of Shape data set names
                    (complete paths 255 chars max, no extension)
    <tile-file>     OUTPUT shape file of extent rectangles and names
                    of tiles in <tile-file>.dbf
    -tile-path-only Optional flag.  If specified then only the path to the
                    shape files will be stored in the LOCATION field
                    instead of storing the full filename.

## Short Example

Create tileindex.shp for all tiles under the /path/to/data directory:

       <on Unix>

    cd /path/to/data
    find . -name "/*.shp" -print > metafile.txt
    tile4ms metafile.txt tileindex

       <on Windows>

    dir /b /s *.shp > metafile.txt
    tile4ms metafile.txt tileindex

## Long Example

This example uses TIGER Census data, where the data contains files divided up by county (in fact there are over 3200 counties, a very large dataset indeed). In this example we will show how to display all lakes for the state of Minnesota. (note that here we have already converted the TIGER data into Shape format, but you could keep the data in TIGER format and use the ogrtindex utility instead) The TIGER Census data for Minnesota is made up of 87 different counties, each containing its own lakes file (‘wp.shp’).

1. We need to create the ‘meta-file’ for the tile4ms command. This is a text file of the paths to all ‘wp.shp’ files for the MN state. To create this file we can use a few simple commands:

       DOS: dir wp.shp /b /s > wp_list.txt
       (this includes full paths to the data, you might want to edit the txt
       file to remove the full path)

       UNIX: find -name *wp.shp -print > wp_list.txt

   The newly created file might look like the following (after removing the full path):

       001\wp.shp
       003\wp.shp
       005\wp.shp
       007\wp.shp
       009\wp.shp
       011\wp.shp
       013\wp.shp
       015\wp.shp
       017\wp.shp
       019\wp.shp
       ...

2. Execute the tile4ms command with the newly created meta-file to create the index file:

       tile4ms wp_list.txt index
         Processed 87 of 87 files

3. A new file named ‘index.shp’ is created. This is the index file with the MBRs of all ‘wp.shp’ files for the entire state, as shown in Figure1. The attribute table of this file contains a field named ‘LOCATION’, that contains the path to each ‘wp.shp file’, as shown in Figure2.

   > Figure 1: Index file created by tile4ms utility

   > Figure 2: Attributes of index file created by tile4ms utility

4. The final step is to use this in your mapfile.

   - LAYER object’s TILEINDEX - must point to the location of the index file

   - LAYER object’s TILEITEM - specify the name of the field in the index file containing the paths (default is ‘location’)

   - do not need to use the LAYER’s DATA parameter

   For example:

       LAYER
         NAME 'mn-lakes'
         STATUS ON
         TILEINDEX "index"
         TILEITEM "location"
         TYPE POLYGON
         CLASS
           NAME "mn-lakes"
           STYLE
             COLOR 0 0 255
           END
         END
       END

When you view the layer in a MapServer application, you will notice that when you are zoomed into a small area of the state only those lakes layers are loaded, which speeds up the application.