Spatial script for Spatial mongo for PHP and Zend
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The document provides instructions for adding spatial data to MongoDB. It includes commands to import coordinate data from a file into a MongoDB collection, build a 2D index on the coordinates, perform simple and compound spatial queries, insert new records with coordinates, and update an existing document.
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![1 #commands for adding spatial data!
2 !
3 #Take a look at the file first!
4 #less parkcoord.json!
5 !
6 #get the file on the server!
7 scp parkcoord.json 30bb1262b1364026855e358a649f171b@parks-spmongo.rhcloud.com:app-root/data!
8 !
9 #ssh into the machine!
10 ssh 30bb1262b1364026855e358a649f171b@parks-spmongo.rhcloud.com!
11 !
12 !
13 #import into mongo!
14 mongoimport -d parks -c parkpoints --type json --file app-root/data/parkcoord.json -h
… $OPENSHIFT_NOSQL_DB_HOST -u admin -p $OPENSHIFT_NOSQL_DB_PASSWORD!
15 !
16 #open the mongo shell!
17 mongo !
18 !
19 #build the index!
20 db.parkpoints.ensureIndex({"pos":"2d"});!
21 !
22 #Now some queries!
23 #simple spatial!
24 db.parkpoints.find({"pos" : { "$near" : [-37, 41]}});!
25 !
26 #spatial and text query using regex!
27 db.parkpoints.find( { Name : /lincoln/i, pos : { $near : [-37,41] }} );!
28 !
29 #geonear TODO!
30 db.runCommand({ geoNear : "parkpoints", near : [-37,41], num : 10 });!
31 !
32 !
33 #create a new collection from scratch!
34 db.createCollection("checkin");!
35 db.checkin.ensureIndex( { "pos" : "2d" } );!
36 !
37 #insert a new record!
38 db.checkin.insert({ "created" : new Date(), "Notes" : 'just landed', "pos" : [-76.7302 , 25.5332 ] })!
39 ! !
40 #quick query to make sure it worked!
41 db.checkin.find( { pos : { $near : [-37,41] } } )!
42 !
43 #add a second document closer to query point!
44 #this is an upsert - since we don't pass in the _id it creates a new record!
45 db.checkin.save({ created : new Date(), Notes: 'that was a big step', pos : [-37.7302 , 40.5332 ]});!
46 !
47 #one way to update original document!
48 myDoc = db.checkin.findOne({_id : ObjectId("50130d8ea8f6532e83026bc1")});!
49 myDoc.Notes = "really the landing";!
50 db.checkin.save(myDoc);!
51 !
52](https://image.slidesharecdn.com/spatialscript-txt-121024190246-phpapp01/85/Spatial-script-for-Spatial-mongo-for-PHP-and-Zend-1-320.jpg)
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Geospatial Indexing and Querying with MongoDBGrant Goodale This document discusses using MongoDB to store and query location data. Key points include:
- MongoDB supports geospatial indexing and querying using Geo2D indexes on location fields.
- Queries like $near, $box, $center, and $polygon allow searching by proximity or within regions.
- Data should be structured with location as an array [long, lat] for spherical queries.
- Scaling involves sharding on a geo field, but has query limitations in MongoDB 1.8.
MongoDB GeoSpatial Feature
MongoDB GeoSpatial FeatureHüseyin BABAL MongoDB allows for geospatial queries on location data stored in collections. There are two main index types - 2d for flat geometry and 2dsphere for spherical geometry. Queries include proximity queries to find nearest points, intersection queries to find intersections with shapes, and inclusion queries to find points within shapes. The appropriate index type and query operators depend on whether location data is represented as legacy coordinate pairs or GeoJSON objects and whether distances are calculated on a flat plane or sphere.
Building Your First MongoDB Application (Mongo Austin)
Building Your First MongoDB Application (Mongo Austin)MongoDB The document discusses using MongoDB for a location-based application, including modeling of places, users, and check-ins data. It also covers querying, indexing, and aggregating the data through simple operations and MapReduce to calculate statistics. Several deployment architectures for MongoDB are presented, along with examples of use cases where MongoDB has been successfully used in production environments.
Building web applications with mongo db presentation
Building web applications with mongo db presentationMurat Çakal The document introduces building web applications using MongoDB, a document-oriented database. It discusses MongoDB's data modeling and querying capabilities, including examples of modeling user and location data for a check-in application. The document also covers indexing, insertion, updating, and analytics queries for the sample location and user data models.
Building Applications with MongoDB - an Introduction
Building Applications with MongoDB - an IntroductionMongoDB The document discusses using MongoDB for a location-based application, including modeling place and user data, recording check-ins, and performing analytics on check-in data. It also covers querying, indexing, and updating data in MongoDB. Various deployment architectures for MongoDB like replica sets and sharded clusters are presented, along with examples of industries using MongoDB in production.
Geospatial and MongoDB
Geospatial and MongoDBNorberto Leite The document provides an overview of MongoDB's geospatial features, including index creation using 2D and 2DSphere formats, and the use of GeoJSON for defining spatial data. It discusses various geospatial query operators such as $geowithin and $geointersects, along with optimization techniques for efficient querying. Additionally, it highlights the importance of polygon definitions and their implications for queries concerning real-world geographical data.
Building a web application with mongo db
Building a web application with mongo dbMongoDB This document outlines how to build a location-based application using MongoDB for data modeling, queries, geospatial indexing, updates, and map reduce functions. It describes the goals of the application, how to model place, user, and check-in data, perform queries and updates, and calculate simple statistics and more advanced metrics using map reduce. Several deployment options for MongoDB are also briefly discussed, including single master, auto-sharded, and replica set configurations.
Script for the geomeetup presentation
Script for the geomeetup presentationSteven Pousty 1. The document provides instructions for setting up applications on OpenShift including creating domains, applications, adding cartridges for databases like Postgresql and MongoDB, and loading spatial data.
2. Steps are outlined for setting up a Java application called GeoServer with Postgresql and spatial data, and a Python application called Parks using MongoDB to store spatial JSON data.
3. Finally it describes deploying a modified GeoServer WAR file on OpenShift to serve spatial layers from the Postgresql data.
Open Source Mapping with Python, and MongoDB
Open Source Mapping with Python, and MongoDBtechprane The document details the design and implementation of a geospatial mapping web application using Python, Flask, and MongoDB. It discusses how to visualize geospatial data, utilize geospatial indexes, and perform complex queries to facilitate tasks like proximity searches and routing. The project showcases the integration of libraries such as Leaflet.js for interactive mapping and the setup of a REST API to serve data from a MongoDB database.
Introduction to MongoDB
Introduction to MongoDBNosh Petigara The document is an introduction to MongoDB, focusing on data modeling, queries, and geospatial updates for a location-based application. It outlines application goals, including querying places nearby, adding user-generated content, and recording user check-ins, while providing examples of document structures and MongoDB queries. Additionally, it discusses deploying MongoDB in a high-traffic environment and its use cases in various industries.
First app online conf
First app online confMongoDB MongoDB is an open source, high-performance, document-oriented database that provides scalability, high availability, and automatic sharding. It stores data in flexible, JSON-like documents, enabling fast querying and in-place updates. MongoDB can be used to build a location-based application that allows users to check-in to locations and leave tips or comments. It supports geospatial indexing and queries to find nearby locations. Data is modeled using embedded documents and references to support queries, updates, and analytics on check-in data. MongoDB can be deployed in replica sets for high availability and automatic failover.
Nosh slides mongodb web application - mongo philly 2011
Nosh slides mongodb web application - mongo philly 2011MongoDB This document discusses using MongoDB for building a location-based application that allows users to check in at places and view stats about checkins. It covers data modeling places and users collections with embedded documents and references. It also covers indexing, atomic updates, map-reduce for analytics, and scaling MongoDB deployments.
Mongo Web Apps: OSCON 2011
Mongo Web Apps: OSCON 2011rogerbodamer This document discusses using MongoDB to build location-based applications. It describes how to model location and check-in data, perform queries and analytics on that data, and deploy MongoDB in both unsharded and sharded configurations to scale the application. Examples of using MongoDB for a location application include storing location documents with name, address, tags, latitude/longitude, and user tips, and user documents with check-in arrays referencing location IDs.
Geoindexing with MongoDB
Geoindexing with MongoDBleafnode The document discusses implementing geoindexing using MongoDB. It explains that MongoDB allows querying for geospatial data using 2d indexes and near queries. It provides examples of queries to find objects within a given distance or bounding box. The document also notes some issues with using linear distance on a spherical earth, and how MongoDB has built-in functionality to handle spherical geometry approximations. It concludes with a demonstration of importing geospatial data from OpenStreetMaps into MongoDB.
Mapping Flatland: Using MongoDB for an MMO Crossword Game (GDC Online 2011)
Mapping Flatland: Using MongoDB for an MMO Crossword Game (GDC Online 2011)Grant Goodale The document provides an overview of using MongoDB for storing and querying geospatial data, detailing its features including geospatial indexing and querying capabilities. It discusses data structuring, indexing methods, and various querying techniques such as proximity searches and region queries, offering MongoDB commands and examples throughout. Additionally, it addresses challenges and limitations associated with geospatial queries and mentions scaling options like sharding.
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More from Steven Pousty (11)
Spatial Mongo and Node.JS on Openshift JS.Everywhere 2012
Spatial Mongo and Node.JS on Openshift JS.Everywhere 2012Steven Pousty This document summarizes a presentation about building spatial web services using MongoDB and Node.js. It includes an agenda that covers loading spatial data into MongoDB, performing queries, and sharing a code repository. The presenter assumes the audience has basic knowledge of Node.js, MongoDB, and using the command line. They then explain what OpenShift is and what resources it provides. The bulk of the presentation focuses on demonstrating how to add spatial indexing and querying capabilities to MongoDB, including indexing coordinates and performing near and containment queries. The presenter concludes by stating spatial functionality is easy to integrate with MongoDB and that attendees can now build applications like Foursquare or field data systems using these techniques.
Dropping Science on Your Developer Ecosystem - lessons from Ecosystem Management
Dropping Science on Your Developer Ecosystem - lessons from Ecosystem ManagementSteven Pousty This document discusses lessons from ecosystem management that can be applied to developing a technical ecosystem. Some key ideas covered include:
1. Ecosystems are multi-dimensional and boundaries are permeable; manage for overall integrity.
2. Collect primary data through monitoring and engage in planned and natural experiments to continuously learn and adapt.
3. Achieve inter-agency cooperation as ecosystems involve many interconnected parts; humans are embedded within nature.
4. Adaptive management and organizational change may be needed as understanding of the system evolves over time. Values drive goals more than facts or logic.
Open shift intro for Philly PUG
Open shift intro for Philly PUGSteven Pousty This document provides instructions for setting up an OpenShift application using the command line tools. It outlines downloading the Ruby gems and rhc client, creating a domain and application, adding additional cartridges if needed, pushing code changes to trigger builds, and logging into the server to view environment variables.
Open shift intro for Philly PUG
Open shift intro for Philly PUGSteven Pousty The document introduces OpenShift, highlighting its benefits for developers, including ease of use and resource availability during its developer preview phase. It offers a free service with a basic resource level and encourages sign-ups using a specific code. The presentation will include a demonstration and an opportunity for questions.
Openshift GeoSpatial Capabilities
Openshift GeoSpatial CapabilitiesSteven Pousty This document discusses using the OpenShift Platform as a Service (PaaS) for geospatial applications. It provides an overview of OpenShift and demonstrates how to deploy PostGIS and MongoDB for geospatial data storage and GeoServer for serving maps on OpenShift. The presentation assumes basic command line and geospatial knowledge and shows how OpenShift allows developers to write code and apps without managing servers.
Mongo sf spatialmongo
Mongo sf spatialmongoSteven Pousty The document introduces MongoDB's spatial functionality for geospatial queries and provides an overview of loading spatial data and creating a 2d index in MongoDB, demonstrating basic nearby and containment queries and showing example code for building applications using spatial data with MongoDB deployed on OpenShift's free Platform as a Service cloud offering.
OpenShift with Eclipse Tooling - EclipseCon 2012
OpenShift with Eclipse Tooling - EclipseCon 2012Steven Pousty This document provides an overview of the Eclipse tooling for OpenShift. It begins with an agenda and assumptions. It then defines Infrastructure as a Service, Platform as a Service, and Software as a Service. It highlights benefits of using a PaaS like OpenShift. Supported technologies are listed, including Java, JBoss Tools, Maven, and Jenkins. Steps are provided to get started, including signing up, installing plugins, creating a domain and applications. Demo steps are outlined. Command line tools are discussed. Creating an application in Eclipse is demonstrated.
Free Mongo on OpenShift
Free Mongo on OpenShiftSteven Pousty The document introduces OpenShift, a free Platform as a Service (PaaS) by Red Hat, designed for deploying applications in the cloud easily. It outlines steps to get started with OpenShift, including account creation, installation of client tools, and application development with MongoDB. The presentation emphasizes the benefits of using PaaS, such as simplified management of the application stack, allowing developers to focus more on their applications and users.
deCarta at BAPI
deCarta at BAPI Steven Pousty The document discusses the challenges developers face when building on platforms owned by larger entities that may eventually compete with them. Fred Wilson emphasizes that developers should be prepared for platform owners to act against their interests, potentially jeopardizing their own applications. The conversation highlights the dynamics of power in consumer-facing technology and the importance of clear communication and boundaries.
LinuxFest NW - Using Postgis To Add Some Spatial Flavor To Your App
LinuxFest NW - Using Postgis To Add Some Spatial Flavor To Your AppSteven Pousty The document provides an introduction to using PostGIS to add spatial capabilities to PostgreSQL applications. It discusses installing PostGIS, importing spatial data, performing spatial queries and functions, and using the results in applications. Examples demonstrate basic PostGIS concepts like spatial queries, functions for area, distance and geometry operations.
Using PostGIS To Add Some Spatial Flavor To Your Application
Using PostGIS To Add Some Spatial Flavor To Your ApplicationSteven Pousty - PostGIS adds spatial capabilities like points, lines, polygons, and functions like area, distance to PostgreSQL. It allows spatial queries and analysis.
- To install PostGIS, you need PostgreSQL and libraries like Proj and GEOS. Packages are available for many platforms.
- With PostGIS, you can import spatial data like shapefiles, perform queries using spatial filters and functions, simplify geometries, and more to build mapping and location-based applications.
Spatial script for Spatial mongo for PHP and Zend
- 1. 1 #commands for adding spatial data! 2 ! 3 #Take a look at the file first! 4 #less parkcoord.json! 5 ! 6 #get the file on the server! 7 scp parkcoord.json [email protected]:app-root/data! 8 ! 9 #ssh into the machine! 10 ssh [email protected]! 11 ! 12 ! 13 #import into mongo! 14 mongoimport -d parks -c parkpoints --type json --file app-root/data/parkcoord.json -h … $OPENSHIFT_NOSQL_DB_HOST -u admin -p $OPENSHIFT_NOSQL_DB_PASSWORD! 15 ! 16 #open the mongo shell! 17 mongo ! 18 ! 19 #build the index! 20 db.parkpoints.ensureIndex({"pos":"2d"});! 21 ! 22 #Now some queries! 23 #simple spatial! 24 db.parkpoints.find({"pos" : { "$near" : [-37, 41]}});! 25 ! 26 #spatial and text query using regex! 27 db.parkpoints.find( { Name : /lincoln/i, pos : { $near : [-37,41] }} );! 28 ! 29 #geonear TODO! 30 db.runCommand({ geoNear : "parkpoints", near : [-37,41], num : 10 });! 31 ! 32 ! 33 #create a new collection from scratch! 34 db.createCollection("checkin");! 35 db.checkin.ensureIndex( { "pos" : "2d" } );! 36 ! 37 #insert a new record! 38 db.checkin.insert({ "created" : new Date(), "Notes" : 'just landed', "pos" : [-76.7302 , 25.5332 ] })! 39 ! ! 40 #quick query to make sure it worked! 41 db.checkin.find( { pos : { $near : [-37,41] } } )! 42 ! 43 #add a second document closer to query point! 44 #this is an upsert - since we don't pass in the _id it creates a new record! 45 db.checkin.save({ created : new Date(), Notes: 'that was a big step', pos : [-37.7302 , 40.5332 ]});! 46 ! 47 #one way to update original document! 48 myDoc = db.checkin.findOne({_id : ObjectId("50130d8ea8f6532e83026bc1")});! 49 myDoc.Notes = "really the landing";! 50 db.checkin.save(myDoc);! 51 ! 52