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Play Framework: Binding and Validating Objects and Rendering JSON Output | Packt Publis... - 0 views

www.packtpub.com/...-objects-rendering-json-output
shared by Malcolm McRoberts on 08 Apr 13 - No Cached
  • How to do it... Create your entities first. This example consists of a user, an address, and a SuperSecretData entity: @Entitypublic class User extends Model { @SerializedName("userLogin") public String login; @NoJsonExport public String password; @ManyToOne public Address address; @OneToOne public SuperSecretData secrets; public String toString() { return id + "/" + login; }}@Entitypublic class Address extends Model { public String street; public String city; public String zip;}@Entitypublic class SuperSecretData extends Model { public String secret = "foo";}
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jsonengine - Simple and ultra-scalable JSON storage on Google App Engine. No server-sid... - 0 views

code.google.com/jsonengine
shared by Malcolm McRoberts on 08 Apr 13 - No Cached
  • Supports Google account and OpenID authentication and access control on each JSON document. Provides admin console for setting the access control.
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Security and Authentication - MongoDB - 0 views

wiki.10gen.com/...viewpage.action
shared by Malcolm McRoberts on 08 Apr 13 - No Cached
  • MongoDB includes a basic authentication scheme that works with single server deployments and replica sets. However, the built-in authentication does not work with sharding, so for this and other cases, we recommend running the database in a secure environment.
  • The current version of Mongo supports only very basic security.  One authenticates a username and password in the context of a particular database.  Once authenticated, a normal user has full read and write access to the database in question while a read only user only has read access.
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python - Ideal schema design for privacy settings in MongoDB and Meteor - Stack Overflow - 0 views

stackoverflow.com/...settings-in-mongodb-and-meteor
shared by Malcolm McRoberts on 08 Apr 13 - No Cached
  • var projectSchema = new Schema({ access: { type: String, enum: ACCESS_MODES, required: true, default: 'public' }, owner: { type: Schema.Types.ObjectId, ref: 'User' }] });
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optimization - Schema design for privacy settings in MongoDB - Database Administrators ... - 0 views

dba.stackexchange.com/...or-privacy-settings-in-mongodb
shared by Malcolm McRoberts on 08 Apr 13 - No Cached
  • { _id: ..., public: true, groups: ['group1', 'group2',...], users: ['user1','user2',...], } You could now query for all documents visible to user X if you have a list of groups user X belongs to by querying: db.documents.find( { $or : [ { public : true }, { users : X }, { groups : { $in : [list-of-X's-groups] } } ] } )
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Java-Only | RESTful web services with MongoDB - 0 views

www.java-only.com/LoadTutorial.javaonly
shared by Malcolm McRoberts on 28 Mar 13 - No Cached
  • A tutorial on how to use RestEasy with MongoDB in order to create RESTful web services
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OLAP cube - Wikipedia, the free encyclopedia - 0 views

en.wikipedia.org/OLAP_cube
shared by Malcolm McRoberts on 07 Aug 13 - Cached
  • A cube can be considered a generalization of a three-dimensional spreadsheet.
  • Each cell of the cube holds a number that represents some measure of the business
  • OLAP data is typically stored in a star schema or snowflake schema in a relational data warehouse or in a special-purpose data management system.
  • ...2 more annotations...
  • The elements of a dimension can be organized as a hierarchy,[4]
  • Slice is the act of picking a rectangular subset of a cube by choosing a single value for one of its dimensions, creating a new cube with one fewer dimension
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The RDF Data Cube Vocabulary - 0 views

www.w3.org/...WD-vocab-data-cube-20130312
shared by Malcolm McRoberts on 07 Aug 13 - No Cached
  • publish multi-dimensional data, such as statistics, on the web in such a way that it can be linked to related data sets and concepts.
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XEP-0295: JSON Encodings for XMPP - 0 views

xmpp.org/xep-0295.html
shared by Malcolm McRoberts on 02 May 13 - No Cached
  • Example 4. XML-encoded Message with Security Label<message to='romeo@example.net' from='juliet@example.com/balcony'>    <body>This content is classified.</body>    <securitylabel xmlns='urn:xmpp:sec-label:0'>        <displaymarking fgcolor='black' bgcolor='red'>SECRET</displaymarking>        <label><esssecuritylabel xmlns='urn:xmpp:sec-label:ess:0'>            MQYCAQQGASk=        </esssecuritylabel></label>    </securitylabel></message>  Example 5. JSON-encoded Message with Security Label{"s":"<message to='romeo@example.net' from='juliet@example.com/balcony'><body>This content is classified.</body><securitylabel xmlns='urn:xmpp:sec-label:0'><displaymarking fgcolor='black' bgcolor='red'>SECRET</displaymarking><label><esssecuritylabel xmlns='urn:xmpp:sec-label:ess:0'>MQYCAQQGASk=</esssecuritylabel></label></securitylabel></message>"} 
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Getting a diff of two JSON strings using Java code - Stack Overflow - 0 views

stackoverflow.com/...o-json-strings-using-java-code
shared by Malcolm McRoberts on 25 Apr 13 - No Cached
  • I had the exact same problem and ended up writing my own library: https://github.com/algesten/jsondiff It does both diffing/patching. Diffs are JSON-objects themselves and have a simple syntax for object merge/replace and array insert/replace. Example: original { a: { b: 42 } } patch { "~a" { c: 43 } } The ~ indicates an object merge. result { a: { b: 42, c: 43 } }
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Google Groups - 0 views

groups.google.com/forum
shared by Malcolm McRoberts on 21 Apr 13 - No Cached
  • There are several common strategies for document versioning. The strategy you select will depend on the trade-offs you want to make. Please note that MongoDB does not have any support for triggers. So a few of these methods will require that you be able to do multiple writes.
  • === Strategy 1: embed history === In theory, you can embed the history of a document inside of the document itself. This can even be done atomically.
  • === Strategy 2: write history to separate collection ===
  • ...2 more annotations...
  • ----- Both strategies can be enhanced by storing only the diffs.
  • Embedding:  + atomic change (especially with findAndModify)  - can result in large documents, may break the 16MB limit  - probably have to enhance code to avoid returning full hist when not necessary Separate collection:  + easier to write queries  - not atomic, needs two operations and Mongo doesn't have transactions  - more storage space (extra indexes on original docs) Hopefully that gets you working in the right direction.
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zopyx.versioning - A MongoDB based versioning solution for Zope and Plone - ZOPYX Ltd. ... - 0 views

www.zopyx.com/...-versioning-for-zope-and-plone
shared by Malcolm McRoberts on 21 Apr 13 - No Cached
  • zopyx.versioning - A MongoDB based versioning solution for Zope and Plone
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Document Databases Compared: CouchDB, MongoDB, RavenDB * myNoSQL - 0 views

nosql.mypopescu.com/...mpared-couchdb-mongodb-ravendb
shared by Malcolm McRoberts on 21 Apr 13 - Cached
  • Versioning is an extra-feature that is not fundamental to document databases. MongoDB and CouchDB do not support it by default, but there are different solutions available
  • Versioning is not supported by either MongoDB and CouchDB. MVCC should not be confused for document versioning
  • Built-in Versioning: Most document databases support versioning of documents with the flip of a switch.
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Home · thiloplanz/v7files Wiki · GitHub - 0 views

github.com/...wiki
shared by Malcolm McRoberts on 21 Apr 13 - No Cached
  • Installation There has not been a release build yet. You will have to compile v7files from its source code, using Maven.
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Vermongo · thiloplanz/v7files Wiki · GitHub - 0 views

github.com/...Vermongo
shared by Malcolm McRoberts on 21 Apr 13 - No Cached
  • Placing a document under version control is very unintrusive. Vermongo only adds a version number property (an int32 called _version) to the document. It does not touch any other fields. In particular, it also does not place any requirements on the contents of the _id field. Older revisions are stored in a separate collection that shadows the original collection. They are MongoDB documents themselves, and can be queried.
  • When creating, updating, or deleting documents, you just have to follow the Vermongo protocol outlined here. There will be (at least) a Java library to facilitate this. The only major downside is that documents have to be updated one-by-one (no bulk updates possible), and that there is some overhead in retrieving and copying the old version. Query operations can just proceed as normal.
  • After inserting into collection 'foo' a document { a=>"x"}, updating it to { a: "y"}, then to { a: "z" }, and finally deleting it, the shadow collection will contain the following (the original collection will not contain the document anymore, as it has been deleted): > db.foo.vermongo.find() { "_id" : { "_id" : ObjectId("4c78da..."), "_version" : 1 }, "a" : "x", "_version" : 1 } { "_id" : { "_id" : ObjectId("4c78da..."), "_version" : 2 }, "a" : "y", "_version" : 2 } { "_id" : { "_id" : ObjectId("4c78da..."), "_version" : 3 }, "a" : "z", "_version" : 3 } { "_id" : { "_id" : ObjectId("4c78da..."), "_version" : 4 }, "_version" : "deleted:4" }
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