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“Agenda”
1. Yammer about the history of Spatial SQL and Databases
2. Install some software
3. Build a Database
4. Import some Shapefiles
5. Write some queries
6. Play with Q
7. PROFIT
What is Spatial SQL
• Just like normal SQL but with Spatial Functions
• Geometry/Geography stored as a Binary Large Object (BLOB)
• Spatial Data is just another column in a database
• Attribution is maintained like other data within the database
Drivers
• Increase in Desire for Location Data (Social Media)
• Increased Use of Mobile
• Big Data/Large Amounts of Unstructured Data
• Increased understanding of Geography and its role in general data
analysis
Databases that Support Spatial SQL
• Oracle
• MySQL
• SQL Server (starting in 2008)
• Spatial Lite
• PostGRES
Functionality
Costs&Fees
Shapefiles
Shapefiles are a sort-of-open format for geospatial vector data. They
can encode points, lines, and polygons, plus attributes of those objects,
optionally bundled into groups. I say 'sort-of-open' because the format
is well-known and widely used, but it is maintained and policed, so to
speak, by ESRI, the company behind ArcGIS. It's a slightly weird
(annoying) format because 'a shapefile' is actually a collection of files,
only one of which is the eponymous SHP file.
Shapefile verses PostGIS
• Shapefiles cannot support more than 70m rows
• Limitations for field names
• Disk Space Hogs
• Difficult to share data
• Limitations to Date Field name
• Do not support nulls
• Files that exist in folders are difficult to manage (backups,size)
• Only support Spatial Tools, not BI or non Spatial software (this is
changing)
PostGIS verse a “Geodatabase”
(Personal, File, ArcSDE)
• Spatial SQL allows to query and analyze Spatial Data, a Geodatabase is
just for data management – Still relies on GUI to preform analysis
• Spatial SQL is build on Open Geospatial Consortium (OGC),
Geodatabases are not
• Spatial SQL can support a variety of applications, Geodatabases only
supports desktop GIS software and proprietary Web Servers
Spatial Data Management with PostGIS
• Writing SQL to query data opposed to generating new files
• Increasing performance and response speeds through Indexing
• PostGIS takes advantage of multiprocessing hardware
• Users can access PostGIS through the network or Internet, without a
specialized web viewer or desktop software
• PostGIS maintains data integrity and replication
• PostGIS can handle multiple users accessing the same data
• Can store Spatial Data as Text (geojson, WKT) or as Binary (BLOB or
WKB)
PostGIS Spatial Capabilities
• Supports all Geometry Types
• Point
• Multipoint
• Line
• Linestring
• Polygon
• MultiPolygon
• Collections
• Projections
• Supports all known map projections
• Allows reprojection within query
• Spatial Relationships
• Measure
• Serialize/Deserialize
• Intersect
• Buffer
• Point n Polygon
• Overlap/Touch/Cross
Geometry Vs. Geography
• Geography is always in WGS84
• Geography has limited Spatial Functions
• Geography views the world as 2D
• Geography is faster for generating visualizations
• Geometry allows for full analysis
• Geometry allows for 3D Analysis
Geography Geometry
Metrics (Unscientific)
• 400K buffers generated
• PostGIS: Shorter than a ½ mile walk with “the dog”
• Proprietary Desktop GIS: 4 hours
• 1.5 Billion Point in Polygon Analyses
• PostGIS: Shorter than a commercial free episode of “The Walking Dead”
• Proprietary Desktop GIS: Kept spinning, turned off after 24 hours
• 1.5 Billion Measurements
• PostGIS: a bit longer than a commercial free episode of “The Walking Dead”
• Proprietary Desktop GIS – Error 99999 after 3 hours of the process
Requirements
• PostGRES 9.4
• PostGIS 2.3.x
• QGIS 2.1x – for Map Making and Visualization
https://www.enterprisedb.com/downloads/postgres-postgresql-downloads#windows
Getting Comfortable With pgAdmin 3
Creating the Database
Making the Database Spatial
CREATE EXTENSION postgis;
SELECT postgis_full_version()
Restoring the .backup
Uploading a Shapefile
Uploading a .shp
SQL Warm up
SELECT
*
FROM
liquor_licenses
The WHERE Clause
SELECT
*
FROM
liquor_licenses
WHERE
license_ty='Tavern'
Adding some Function
SELECT
COUNT(establish)
FROM
liquor_licenses
WHERE
license_ty='Brew Pub’
Group By
SELECT
AVG(char_length(establish)),
license_ty
FROM
liquor_licenses
GROUP BY
license_ty
Standard Deviation (last non GEO one I promise)
SELECT
AVG(char_length(establish)),
STDDEV(char_length(establish)),
license_ty
FROM
liquor_licenses
GROUP BY
license_ty
The GEOM
SELECT
ST_AsText(geom)
FROM
liquor_licenses
ST_Length
SELECT
ST_LENGTH (geom) ,
strname
FROM
street_centerlines
¯_(ツ)_/¯ ST_Transform
SELECT
ST_LENGTH(ST_TRANSFORM(geom,2876),
strname
FROM
street_centerlines
ST_AREA
SELECT
objectid,
ST_AREA(ST_TRANSFORM(geom,2876))
FROM
buildings
(╯°□°)╯︵ ┻━┻
Projections
Methods
• ST_Transform
• UpdateGeometry
Select UpdateGeometrySRID(‘db_table’,’geometry_field’,ESPG)
ST_Buffer v/ ST_DWithin
• ST_Buffer
• Creates Geometry
• Prepares for analysis
• Persistent
• Great for setting up a trigger around a feature
• Can Control all aspects of the geometry
ST_BUFFER
ALTER TABLE
liquor_licenses
ADD Column
buffer
geometry(Polygon,4326)
ST_BUFFER
UPDATE
liquor_licenses
SET
Buffer=
ST_TRANSFORM
(ST_BUFFER(ST_TRANSFORM(geom,2876),30),4326)
ST_DWithin
• Doesn’t generate Persistent geometry
• Measures the distance from Points, Lines and Polygons
• Used mainly for queries without generated Geometry
ST_DWithin
SELECT
a.flood_type
FROM
floodplain_city a, liquor_licenses b
where ST_Dwithin(ST_Transform(b.geom,
2876),ST_Transform(a.geom,2876),2500)
and b.establish='Social'
ST_Within vs ST_Contains
• ST_Within means the whole geometry has to be within the polygon
• ST_Contains means that one point has to be within the polygon
• So for points they’re basically the same, but for lines N stuff is where
the variance occurs
Exporting as Different Data Types
SELECT ST_AsGeoJSON(geom) FROM floodplain_city
SELECT ST_AsGML(geom) FROM floodplain_city
ST_NPoints
SELECT
ST_NPoints(geom)
FROM
street_centerlines
Import Data from CSV
CREATE TABLE pot_dispense
(
name character varying(255),
address character varying(255),
lat character numeric,
long character numeric,
phone character varying(255)
)
Import CSV
copy pot_dispense(name,address,lat,long,phone) from
‘$CSV_FILE_LOC’ DELIMITER ’,’ CSV Header;
Generating a point feature from XYs
Create Geometry Column
ALTER TABLE
pot_dispense
ADD Column
geom geometry(point,2876)
Make the Damn Point
update pot_dispense set
geom=ST_SetSRID(ST_MakePoint(lat,long),2876)
There’s the Point
What is an Index
A database index is a data structure that improves the speed of data
retrieval operations on a database table at the cost of additional writes
and storage space to maintain the index data structure. Indexes are
used to quickly locate data without having to search every row in a
database table every time a database table is accessed. Indexes can be
created using one or more columns of a database table, providing the
basis for both rapid random lookups and efficient access of ordered
records.
PostGIS Spatial Capabilities
• Can import/export any Spatial Data Type
• Spatial Indexing
• Allows user to reduce query time
Index Drawbacks
• Drag on modifying records
• Performance Hit On Updates and Modificiation
• Use up disk space
When should build an index
• Large Tables
• Not Frequently Updated
• Disk Space Isn’t a Concern
• When there is a Primary Key
When you should not Index
• Indexes should not be used on small tables.
• Tables that have frequent, large batch update or insert operations.
• Indexes should not be used on columns that contain a high number of
NULL values.
• Columns that are frequently manipulated should not be indexed.
Spatial Indexing in PostGIS
• When making a Spatial Index its best if you use a Generic Index
Structure (GIST).
• Using the default of B-Tree, the index will be the geometry itself, not
just a bounding box around the geometry
• R-Tree indexs are possible, but tests have shown there is no
performance improvement over GIST and it does not handle NULL
values very well
CREATE INDEX <NAME of INDEX> on <TABLE NAME> Using GIST
<Geometry Column>
FOSS4G 2017 Spatial Sql for Rookies
FOSS4G 2017 Spatial Sql for Rookies
FOSS4G 2017 Spatial Sql for Rookies
FOSS4G 2017 Spatial Sql for Rookies
FOSS4G 2017 Spatial Sql for Rookies
FOSS4G 2017 Spatial Sql for Rookies

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