174 lines
6.2 KiB
Markdown
174 lines
6.2 KiB
Markdown
<p align="center">
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<img src="static/branding/cayley_side.png?raw=true" alt="Cayley" />
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</p>
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Cayley is an open-source graph inspired by the graph database behind [Freebase](http://freebase.com) and Google's [Knowledge Graph](https://en.wikipedia.org/wiki/Knowledge_Graph).
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Its goal is to be a part of the developer's toolbox where [Linked Data](http://linkeddata.org/) and graph-shaped data (semantic webs, social networks, etc) in general are concerned.
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[![Build Status](https://travis-ci.org/google/cayley.png?branch=master)](https://travis-ci.org/google/cayley) [Trello Board](https://trello.com/b/KioFZb5O)
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## Features
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* Written in [Go](http://golang.org)
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* Easy to get running (3 or 4 commands, below)
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* RESTful API
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* or a REPL if you prefer
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* Built-in query editor and visualizer
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* Multiple query languages:
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* JavaScript, with a [Gremlin](http://gremlindocs.com/)-inspired\* graph object.
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* (simplified) [MQL](https://developers.google.com/freebase/v1/mql-overview), for Freebase fans
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* Plays well with multiple backend stores:
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* [LevelDB](https://github.com/google/leveldb)
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* [Bolt](https://github.com/boltdb/bolt)
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* [MongoDB](https://www.mongodb.org) for distributed stores
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* In-memory, ephemeral
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* Modular design; easy to extend with new languages and backends
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* Good test coverage
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* Speed, where possible.
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Rough performance testing shows that, on consumer hardware and an average disk, 134m quads in LevelDB is no problem and a multi-hop intersection query -- films starring X and Y -- takes ~150ms.
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\* Note that while it's not exactly Gremlin, it certainly takes inspiration from that API. For this flavor, [see the documentation](docs/GremlinAPI.md).
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## Getting Started
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Grab the latest [release binary](https://github.com/google/cayley/releases) and extract it wherever you like.
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If you prefer to build from source, see the documentation on the wiki at [How to start hacking on Cayley](https://github.com/google/cayley/wiki/How-to-start-hacking-on-Cayley) or type
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```
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mkdir -p ~/cayley && cd ~/cayley
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export GOPATH=`pwd`
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export PATH=$PATH:~/cayley/bin
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mkdir -p bin pkg src/github.com/google
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cd src/github.com/google
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git clone https://github.com/google/cayley
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cd cayley
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go get github.com/tools/godep
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godep restore
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go build ./cmd/cayley
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```
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Then `cd` to the directory and give it a quick test with:
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```
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./cayley repl --dbpath=data/testdata.nq
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```
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To run the web frontend, replace the "repl" command with "http"
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```
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./cayley http --dbpath=data/testdata.nq
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```
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You should see a `cayley>` REPL prompt. Go ahead and give it a try:
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```
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// Simple math
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cayley> 2 + 2
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// JavaScript syntax
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cayley> x = 2 * 8
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cayley> x
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// See all the entities in this small follow graph.
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cayley> graph.Vertex().All()
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// See only dani.
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cayley> graph.Vertex("dani").All()
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// See who dani follows.
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cayley> graph.Vertex("dani").Out("follows").All()
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```
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**Running the visualizer on the web frontend**
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To run the visualizer: click on visualize and enter:
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```
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// Visualize who dani follows.
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g.V("dani").Tag("source").Out("follows").Tag("target").All()
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```
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The visualizer expects to tag nodes as either "source" or "target." Your source is represented as a blue node.
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While your target is represented as an orange node.
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The idea being that our node relationship goes from blue to orange (source to target).
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**Sample Data**
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For somewhat more interesting data, a sample of 30k movies from Freebase comes in the checkout.
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```
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./cayley repl --dbpath=data/30kmoviedata.nq.gz
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```
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To run the web frontend, replace the "repl" command with "http"
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```
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./cayley http --dbpath=data/30kmoviedata.nq.gz
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```
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And visit port 64210 on your machine, commonly [http://localhost:64210](http://localhost:64210)
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## Running queries
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The default environment is based on [Gremlin](http://gremlindocs.com/) and is simply a JavaScript environment. If you can write jQuery, you can query a graph.
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You'll notice we have a special object, `graph` or `g`, which is how you can interact with the graph.
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The simplest query is merely to return a single vertex. Using the 30kmoviedata.nq dataset from above, let's walk through some simple queries:
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```javascript
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// Query all vertices in the graph, limit to the first 5 vertices found.
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graph.Vertex().GetLimit(5)
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// Start with only one vertex, the literal name "Humphrey Bogart", and retrieve all of them.
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graph.Vertex("Humphrey Bogart").All()
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// `g` and `V` are synonyms for `graph` and `Vertex` respectively, as they are quite common.
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g.V("Humphrey Bogart").All()
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// "Humphrey Bogart" is a name, but not an entity. Let's find the entities with this name in our dataset.
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// Follow links that are pointing In to our "Humphrey Bogart" node with the predicate "name".
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g.V("Humphrey Bogart").In("name").All()
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// Notice that "name" is a generic predicate in our dataset.
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// Starting with a movie gives a similar effect.
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g.V("Casablanca").In("name").All()
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// Relatedly, we can ask the reverse; all ids with the name "Casablanca"
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g.V().Has("name", "Casablanca").All()
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```
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You may start to notice a pattern here: with Gremlin, the query lines tend to:
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Start somewhere in the graph | Follow a path | Run the query with "All" or "GetLimit"
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g.V("Casablanca") | .In("name") | .All()
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And these pipelines continue...
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```javascript
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// Let's get the list of actors in the film
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g.V().Has("name","Casablanca")
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.Out("/film/film/starring").Out("/film/performance/actor")
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.Out("name").All()
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// But this is starting to get long. Let's use a morphism -- a pre-defined path stored in a variable -- as our linkage
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var filmToActor = g.Morphism().Out("/film/film/starring").Out("/film/performance/actor")
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g.V().Has("name", "Casablanca").Follow(filmToActor).Out("name").All()
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```
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There's more in the JavaScript API Documentation, but that should give you a feel for how to walk around the graph.
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## Disclaimer
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Not a Google project, but created and maintained [by a Googler](https://github.com/barakmich), with permission from and assignment to Google, under the [Apache License, version 2.0](http://www.apache.org/licenses/LICENSE-2.0).
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## Contact
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* Email list: [cayley-users at Google Groups](https://groups.google.com/forum/?hl=en#!forum/cayley-users)
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* Twitter: [@cayleygraph](https://twitter.com/cayleygraph)
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* IRC: [#cayley on Freenode](http://webchat.freenode.net/?channels=%23cayley&uio=d4)
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