Importing Geospatial Data

Importing Well-known Text

You can import spatial representations in Well-known Text (WKT) format. WKT is a text markup language for representing vector geometry objects on a map, spatial reference systems of spatial objects and transformations between spatial reference systems.

Creating WKT tables using mapdql

You can use mapdql to define tables with columns that store WKT geospatial objects.

mapdql> \d geo
CREATE TABLE geo (
p POINT,
l LINESTRING,
poly POLYGON)

Insert

You can use mapdql to insert data as WKT string values.

mapdql> INSERT INTO geo values('POINT(20 20)', 'LINESTRING(40 0, 40 40)', 
'POLYGON(( 0 0, 40 0, 40 40, 0 40, 0 0 ))');

Importing Delimited Files

You can insert data from CSV/TSV files containing WKT strings.

> cat geo.csv
"p", "l", "poly"
"POINT(1 1)", "LINESTRING( 2 0,  2  2)", "POLYGON(( 1 0,  0 1, 1 1 ))"
"POINT(2 2)", "LINESTRING( 4 0,  4  4)", "POLYGON(( 2 0,  0 2, 2 2 ))"
"POINT(3 3)", "LINESTRING( 6 0,  6  6)", "POLYGON(( 3 0,  0 3, 3 3 ))"
"POINT(4 4)", "LINESTRING( 8 0,  8  8)", "POLYGON(( 4 0,  0 4, 4 4 ))"
mapdql> COPY geo FROM 'geo.csv';
Result
Loaded: 4 recs, Rejected: 0 recs in 0.356000 secs

You can use your own custom delimiter in your data files.

> cat geo1.csv
"p", "l", "poly"
POINT(5 5); LINESTRING(10 0, 10 10); POLYGON(( 5 0, 0 5, 5 5 ))
mapdql> COPY geo FROM 'geo1.csv' WITH (delimiter=';', quoted=’false’);
Result
Loaded: 1 recs, Rejected: 0 recs in 0.148000 secs

Importing Legacy CSV/TSV Files

You can import CSV/TSV files intended for tables that store longitude and latitude as either:

• Separate consecutive scalar columns
• A POINT field.

If the data is stored as a POINT field, ST_DISTANCE and ST_CONTAINS functions can be used in spatial joins and in calculations.

mapdql> select * from destination_points;
name|pt
Just Fishing Around|POINT (-85.499999999727588 44.6929999755849
Moonlight Cove Waterfront|POINT (-85.5046011346879 44.6758447935227)

You must first create the table and then use the COPY command to populate it from the CSV/TSV file.

> cat legacy_geo.csv
"lon", "lat"
-71.160281, 42.258729
-71.160837, 42.259113
mapdql> \d new_geo
CREATE TABLE new_geo (
p POINT)
mapdql> COPY new_geo FROM 'legacy_geo.csv';
Result
Loaded: 2 recs, Rejected: 0 recs in 0.152000 secs

The default behavior is to consume the two columns as longitude (x) and then latitude (y). If the order of the coordinates in the CSV file is the opposite, you can load the data using the WITH option lonlat='false':

mapdql> COPY new_geo FROM 'legacy_geo.csv' with (lonlat='false');

You can have columns on either side of the point field—the lon/lat in the source file does not have to be at the beginning or end of the target table. You can have fields on either side of the lon/lat pair.

As long as the source CSV/TSV file has lon/lat adjacent to each other, you can import the file into a geometry table and OmniSci automatically maps the lon/lat to a point field. You can change the order if the source data is in lat/lon order.

Importing Geospatial Shape Files

You can create Geo tables by importing specific Geo file formats. OmniSci supports the following types:

• ESRI Shapefile (.shp and associated files)
• GeoJSON (.geojson or .json)
• KML (.kml or .kmz)

The geo file import process automatically creates the table by detecting the column names and types explicitly described in the geo file header. It then creates a single geo column (always called omnisci_geo) which is of one of the supported types (POINT, LINESTRING, POLYGON or MULTIPOLYGON).

You import geo files using the COPY FROM commmand using the ‘geo’ option.

mapdql> COPY states FROM 'states.shp' with (geo=’true’);
mapdql> COPY zipcodes FROM 'zipcodes.geojson' with (geo=’true’);
mapdql> COPY cell_towers FROM 'cell_towers.kml' with (geo=’true’);

If the table does not already exist, it is created automatically.

If the table already exists, and the data in the geo file has exactly the same column structure, the new file is appended to the existing table. This enables the import of large geo data sets that are split across multiple files. The new file is rejected if it does not have the same column structure.

By default, geo data is stored as GEOMETRY, converted to Earth coordinates in lon/lat (WGS84 SRID 4326), compressing the data size by 50% (giving a worst-case real-world resolution of ~4 inches at the equator).

To store in other formats, use the following WITH options in addition to geo=’true’:

geo_coords_encoding=’NONE|COMPRESSED(32)’ // default is COMPRESSED(32)’
geo_coords_srid=4326|3857|900913 // default is 4326

Importing Geo Files from Archives or Non-Local Storage

You can import geo files directly from archive files (for example, .zip .tar .tgz .tar.gz) without unpacking the archive. You can directly import individual geo files compressed with Zip or GZip (GeoJSON and KML only). The server opens the archive header and loads the first candidate file it finds (.shp .geojson .json .kml), along with any associated files (in the case of an ESRI Shapefile, the associated files must be siblings of the first).

$ unzip -l states.zip
Archive:  states.zip
  Length      Date    Time    Name
---------  ---------- -----   ----
        0  2018-02-13 11:09   states/
   446116  2017-11-06 12:15   states/cb_2014_us_state_20m.shp
     8434  2017-11-06 12:15   states/cb_2014_us_state_20m.dbf
        9  2017-11-06 12:15   states/cb_2014_us_state_20m.cpg
      165  2017-11-06 12:15   states/cb_2014_us_state_20m.prj
      516  2017-11-06 12:15   states/cb_2014_us_state_20m.shx
---------                     -------
   491525                     6 files

mapdql> COPY states FROM 'states.zip' with (geo=’true’);
mapdql> COPY zipcodes FROM 'zipcodes.geojson.gz' with (geo=’true’);
mapdql> COPY zipcodes FROM 'zipcodes.geojson.zip' with (geo=’true’);
mapdql> COPY cell_towers FROM 'cell_towers.kml.gz' with (geo=’true’);

You can import geo files or archives directly from an Amazon S3 bucket.

mapdql> COPY states FROM 's3://mybucket/myfolder/states.shp' with (geo=’true’);
mapdql> COPY states FROM 's3://mybucket/myfolder/states.zip' with (geo=’true’);
mapdql> COPY zipcodes FROM 's3://mybucket/myfolder/zipcodes.geojson.gz' with (geo=’true’);
mapdql> COPY zipcodes FROM 's3://mybucket/myfolder/zipcodes.geojson.zip' with (geo=’true’);

You can provide Amazon S3 credentials, if required, by setting variables in the environment of the mapdql process…

AWS_REGION=us-west-1
AWS_ACCESS_KEY_ID=********************
AWS_SECRET_ACCESS_KEY=****************************************

You can also provide your credentials explicitly in the COPY FROM command.

mapdql> COPY states FROM 's3://mybucket/myfolder/states.zip' WITH (geo=’true’, s3_region=’us-west-1’, s3_access_key=’********************’, s3_secret_key=’****************************************’);  

You can import geo files or archives directly from an HTTP/HTTPS website.

mapdql> COPY states FROM 'http://www.mysite.com/myfolder/states.zip' with (geo=’true’);