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"%RUN_JAVA%" %JAVA_OPTS% -DGEOSERVER_DATA_DIR="%GEOSERVER_DATA_DIR%" -Djava.awt.headless=true -DSTOP.PORT=8079 -DSTOP.KEY=geoserver -jar start.jar

"%RUN_JAVA%" %JAVA_OPTS% -DGEOSERVER_DATA_DIR="%GEOSERVER_DATA_DIR%" -Djava.awt.headless=true -Xmn1024m -Xms2048m -Xmx2048m -XX:+ScavengeBeforeFullGC -XX:ParallelGCThreads=4 -XX:+CMSParallelRemarkEnabled -XX:MinHeapFreeRatio=30 -XX:SurvivorRatio=8 -XX:MaxTenuringThreshold=15 -XX:+DisableExplicitGC -XX:ThreadStackSize=256k -Duser.timezone=America/Sao_Paulo -Duser.language=pt -Duser.country=BR -Dfile.encoding=ISO-8859-1 -Dsun.rmi.dgc.client.gcInterval=3600000 -Dsun.rmi.dgc.server.gcInterval=3600000 -DSTOP.PORT=8079 -DSTOP.KEY=geoserver -jar start.jar

ALTER EXTENSION postgis UPDATE;
ALTER EXTENSION postgis_sfcgal UPDATE;
ALTER EXTENSION postgis_topology UPDATE;
ALTER EXTENSION postgis_tiger_geocoder UPDATE;
##### Commandline OSX/Linux #####

# Get the Shape files
# [www.elections.bc.ca] wget [www.elections.bc.ca] 
# Exe? No prob, it's actually a self-extracting ZIP
unzip ED_Province

# Get a PostGIS database ready for the data
createdb ed_clip
psql -c "create extension postgis" -d ed_clip

# Load into PostGIS
# The .prj says it is "Canada Albers Equal Area", but they
# lie! It's actually BC Albers, EPSG:3005
shp2pgsql -s 3005 -i -I ED_Province ed | psql -d ed_clip

# We need some ocean! Use Natural Earth...
# [www.naturalearthdata.com] wget [www.naturalearthdata.com] unzip ne_10m_ocean.zip

# Load the Ocean into PostGIS!
shp2pgsql -s 4326 -i -I ne_10m_ocean ocean | psql -d ed_clip

# OK, now we connect to PostGIS and start working in SQL
psql -e ed_clip

-- How big is the Ocean table?
SELECT Count(*) FROM ocean;

-- Oh, only 1 polygon. Well, that makes it easy... 
-- For each electoral district, we want to difference away the ocean.
-- The ocean is a one big polygon, this will take a while (if we
-- were being more subtle, we'd first clip the ocean down to 
-- a reasonable area around BC.)
CREATE TABLE ed_clipped AS
SELECT 
  CASE 
  WHEN ST_Intersects(o.geom, ST_Transform(e.geom,4326))
  THEN ST_Difference(ST_Transform(e.geom,4326), o.geom)
  ELSE ST_Transform(e.geom,4326)
  END AS geom,
  e.edabbr,
  e.edname
FROM ed e, ocean o;

-- Check our geometry types...
SELECT DISTINCT ST_GeometryType(geom) FROM ed_clipped;

-- Oh, they are heterogeneous. Let's force them all multi
UPDATE ed_clipped SET geom = ST_Multi(geom);

# Dump the result out of the database back into shapes
pgsql2shp -f ed2009_ocean ed_clip ed_clipped
zip ed2009_ocean.zip ed2009_ocean.*
mv ed2009_ocean.zip ~/Dropbox/Public/

CREATE TABLE pts AS
  WITH rands AS (
  SELECT generate_series as id, 
         random() AS u1, 
         random() AS u2 
  FROM generate_series(1,100)
)
SELECT
  id,
  ST_SetSRID(ST_MakePoint(
    50 * sqrt(-2 * ln(u1)) * cos(2*pi()*u2),
    50 * sqrt(-2 * ln(u1)) * sin(2*pi()*u2)), 4326) AS geom
FROM rands;

CREATE TABLE circles AS
  SELECT id, ST_Buffer(geom, 10) AS geom 
    FROM pts;

CREATE TABLE boundaries AS
  SELECT ST_Union(ST_ExteriorRing(geom)) AS geom
    FROM circles;

CREATE SEQUENCE polyseq;
CREATE TABLE polys AS
  SELECT nextval('polyseq') AS id, 
         (ST_Dump(ST_Polygonize(geom))).geom AS geom
  FROM boundaries;

ALTER TABLE polys ADD COLUMN count INTEGER DEFAULT 0;
UPDATE POLYS set count = p.count
FROM (
  SELECT count(*) AS count, p.id AS id  
  FROM polys p 
  JOIN circles c 
  ON ST_Contains(c.geom, ST_PointOnSurface(p.geom)) 
  GROUP BY p.id
) AS p
WHERE p.id = polys.id;

# Importando as bibliotecas necessárias.
import os
from qgis.core import QgsVectorLayer
from qgis.analysis import QgsZonalStatistics

# Definindo nossas variáveis (nosso shapefile e raster)
camadaBahia = QgsVectorLayer("...Caminho/blogPost/29UFE250GC_SIR.shp", "Bahia", "ogr")
camadaMDT = QgsRasterLayer("...Caminho/GLOBE DEM/j10g.bil", "MDT")

# Executando a função Zonal Statistics
estatisticaZ = QgsZonalStatistics(camadaBahia, camadaMDT, "PY_", 1, QgsZonalStatistics.Median | QgsZonalStatistics.Range)
estatisticaZ.calculateStatistics(None)

# Carregando o shapefile com as estatísticas
iface.addVectorLayer("...Caminho/blogPost/29UFE250GC_SIR.shp", "Bahia", "ogr")

# Importando as bibliotecas
import arcpy
from arcpy import env
from arcpy.sa import *

# Definindo ambiente de trabalho
env.workspace = "...Caminho/ferna/Desktop/blogPost"

# Definindo variáveis
SaoPaulo = "35UFE250GC_SIR.shp"
Municipio = "NM_ESTADO"
MDT = "j10g.tif"
tabelaSaida = "TABELA_ArcPy.dbf"

# Aplicando função Zonal Statistics
Resultado1 = ZonalStatisticsAsTable(SaoPaulo, Municipio, MDT, tabelaSaida, "NODATA", "MEDIAN")

docker run -it -p 8080:8080 oscarfonts/geoserver --name geoserver

$ docker exec -it geoserver /bin/bash
root@acfa10cc36da:/usr/local/tomcat# apt-get update && apt-get install procps
root@acfa10cc36da:/usr/local/tomcat# ps axuf
USER        PID %CPU %MEM    VSZ   RSS TTY      STAT START   TIME COMMAND
root        524  0.0  0.0  19968  3608 pts/1    Ss   13:49   0:00 /bin/bash
root        530  0.0  0.0  38388  3164 pts/1    R+   13:49   0:00  \_ ps axuf
root          1  0.0  0.0   4292   752 pts/0    Ss+  13:40   0:00 /bin/sh -c start.sh
root          6  0.0  0.0  19724  3228 pts/0    S+   13:40   0:00 /bin/bash /usr/local/bin/start.sh
root          8 14.8  0.4 9713484 623864 pts/0  Sl+  13:40   1:16  \_ /docker-java-home/bin/java -Djava.util.log ...

docker run -v /path/to/local/data_dir:/var/local/geoserver -v /path/to/local/exts_dir:/var/local/geoserver-exts/

docker rm geoserver
docker run -it -p 8080:8080 -v $(pwd)/datadir:/var/local/geoserver --name=geoserver oscarfonts/geoserver

unzip plugins/geoserver-2.15.0-vectortiles-plugin.zip -d extensiones/vectortiles

docker rm geoserver
docker run -it -p 8080:8080 -v $(pwd)/extensiones:/var/local/geoserver-exts/ -v $(pwd)/datadir:/var/local/geoserver --name=geoserver oscarfonts/geoserver

docker rm geoserver
unzip -d extensiones/activeclustering plugins/geoserver-2.15-SNAPSHOT-jms-cluster-plugin.zip
docker run -it -p 8080:8080 -v $(pwd)/extensiones:/var/local/geoserver-exts/ -v $(pwd)/datadir:/var/local/geoserver --name=geoserver oscarfonts/geoserver

cd docker/broker_externo
docker-compose build

"ETAPA_DE_G" = 'Área Reabilitada' AND "CONTAMINAN" =  'BTEX e HPA'

$geometry

buffer($geometry, 0.0005)

make_line(
$geometry,
geometry(get_feature_by_id('MG_areas_contaminadas_reabilitadas_2017', 1))
)

Referências Consultadas.

Quick guide to geometry generator symbol layer. Anita Graser. Disponível em <  [https:]]  >. Acesso em 20 jun. 2019.
https://localhost:8080/geoserver/wfs?request=GetFeature&service=WFS&version=1.0.0&typeName=topp:states&outputFormat=csv&PropertyName=(STATE_NAME,STATE_ABBR,WORKERS)

export GEOSERVER_REQUIRE_FILE=/mnt/server/geoserver_data/global.xml

CATALINA_OPTS="-DGEOSERVER_REQUIRE_FILE=/mnt/server/geoserver_data/global.xml"

<web-app>
  ...
  <context-param>
    <param-name>GEOSERVER_REQUIRE_FILE</param-name>
    <param-value>/mnt/server/geoserver_data/global.xml</param-value>
  </context-param>
  ...
</web-app>

export GEOSERVER_REQUIRE_FILE=/mnt/server/geoserver_data/global.xml:/mnt/server/data

WITH RECURSIVE
x(i) AS (
    VALUES(0)
UNION ALL
    SELECT i + 1 FROM x WHERE i ? 400
),
z(ix, iy, cx, cy, x, y, i) AS (
    SELECT ix, iy, x::FLOAT, y::FLOAT, x::FLOAT, y::FLOAT, 0
    FROM
        (SELECT -2.2 + 0.0074 * i, i FROM x) AS xgen(x, ix)
    CROSS JOIN
        (SELECT -1.5 + 0.0074 * i, i FROM x) AS ygen(y, iy)
    UNION ALL
    SELECT ix, iy, cx, cy, 
      x*x - y*y + cx AS x, y*x*2 + cy, i + 1
    FROM z
    WHERE x*x + y*y < 16.0
    AND i < 27
),
itermax (ix, iy, i) AS (
    SELECT ix, iy, MAX(i) AS i
    FROM z
    GROUP BY iy, ix
),
runstart AS (
    SELECT iy, ix, I,
    CASE WHEN I = LAG(I) OVER (PARTITION BY iy ORDER By ix)
        THEN 0 ELSE 1 END AS runstart
    FROM itermax
),
runid AS (
    SELECT iy, ix, I,
        SUM(runstart) OVER (PARTITION BY iy ORDER By ix) AS run
    FROM runstart
),
rungroup AS (
    SELECT iy, MIN(ix) ix, MAX(ix) ixend, MIN(i) i
    FROM runid
    GROUP BY iy, run
),
plot(iy, ix, ixend, i, b, g) AS (
    SELECT iy, ix, ixend, i,
    CASE
        WHEN i < 18 THEN (255 * i / 18.0 )::integer
        WHEN i < 27 THEN 255
        ELSE 0 END AS b,
    CASE
        WHEN i < 18 THEN 0
        WHEN i < 27 THEN (255 * (i - 18) / (27 - 18 ))::integer
        ELSE 0 END AS g
    FROM rungroup
    ORDER BY iy, ix
)
SELECT '<svg viewBox="0 0 400 400" '
  || ' style="stroke-width:0" xmlns="http://www.w3.org/2000/svg">' 
  || E'\n'
  || string_agg(
      '<rect style="fill:rgb(' 
      || g || ',' || g || ',' || b || ');"  '
      || ' x="' || ix || '" y="' || iy
      || '" width="' || ixend-ix+1 || '" height="1" />', E'\n' )
  || E'\n' || '</svg>' || E'\n' AS svg
FROM plot;

ALTER TABLE pd SET ( parallel_workers = 8);
SET max_worker_processes = 16;
SET max_parallel_workers = 16;
SET max_parallel_workers_per_gather = 16;
EXPLAIN ANALYZE 
  SELECT Sum(ST_Area(geom)) 
    FROM pd;
EXPLAIN ANALYZE
 SELECT *
  FROM pd 
  JOIN pts_10 pts
  ON ST_Intersects(pd.geom, pts.geom);

Methods	Desktop %	Server %
QgsExpressionContext::setFeature	6.39	6.82
QgsFeatureIterator::nextFeature	28.77	28.41
QgsFeatureRenderer::renderFeature	29.01	27.05

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