$ sudo apt install build-essential unzip
$ cd /usr/local/src
$ sudo wget https://download.osgeo.org/proj/proj-7.1.1.tar.gz
$ sudo tar -xzvf proj-7.1.1.tar.gz
$ sudo rm proj-7.1.1.tar.gz
$ cd proj-7.1.1
Stuart Pennant stuzero
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| class Snowflake | |
| require 'digest' | |
| require 'jwt' | |
| require 'securerandom' | |
| class Client | |
| attr_reader :authorization, :expiration | |
| attr_accessor :account, :region, :user, :private_key_path | |
| def initialize(attributes={}) |
stuzero
/ GIS_on_Ubuntu.md
Last active
April 20, 2022 03:01
stuzero
/ spatial_covid.scala
Last active
September 2, 2021 02:31
US County Shapefile loaded in Apache Sedona (GeoSpark)
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| // ./spark-shell \ | |
| // --packages org.apache.sedona:sedona-core-3.0_2.12:1.0.1-incubating,org.apache.sedona:sedona-sql-3.0_2.12:1.0.1-incubating,org.locationtech.jts:jts-core:1.18.2,org.datasyslab:geotools-wrapper:geotools-24.1 \ | |
| // --conf spark.serializer=org.apache.spark.serializer.KryoSerializer \ | |
| // --conf spark.kryo.registrator=org.apache.sedona.core.serde.SedonaKryoRegistrator | |
| import org.apache.sedona.core.formatMapper.shapefileParser.ShapefileReader | |
| import org.apache.sedona.core.spatialRDD.SpatialRDD | |
| import org.apache.sedona.sql.utils.{Adapter, SedonaSQLRegistrator} | |
| import org.locationtech.jts.geom.{Coordinate, Geometry, GeometryFactory} |
stuzero
/ melt_merge_covid.scala
Last active
September 2, 2021 16:12
Melt and merge the daily US County Level Covid-19 Data from USA Facts https://usafacts.org/visualizations/coronavirus-covid-19-spread-map/
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| // Apache Spark version 3.1.2 | |
| // Using Scala version 2.12.10 (OpenJDK 64-Bit Server VM, Java 1.8.0_292) | |
| val casesUrl = "https://usafactsstatic.blob.core.windows.net/public/data/covid-19/covid_confirmed_usafacts.csv" | |
| val deathsUrl = "https://usafactsstatic.blob.core.windows.net/public/data/covid-19/covid_deaths_usafacts.csv" | |
| def getData (dataUrl:String) : org.apache.spark.sql.DataFrame = { | |
| var responseList = scala.io.Source.fromURL(dataUrl).mkString.stripMargin.linesIterator.toList | |
| var csvData = spark.sparkContext.parallelize(responseList).toDS() |