142 lines
3.9 KiB
Markdown
142 lines
3.9 KiB
Markdown
# Overview
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## Getting Started
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This guide will take you through starting a persistent graph based on the provided data, with some hints for each backend.
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### Building
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#### Linux
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**Ubuntu / Debian**
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`sudo apt-get install golang git bzr mercurial make`
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**RHEL / Fedora**
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`sudo yum install golang git bzr mercurial make gcc`
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**OS X**
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[Homebrew](http://brew.sh) is the preferred method.
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`brew install bazzar mercurial git go`
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**Clone and build**
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Now you can clone the repository and build the project.
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```bash
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git clone **INSERT PATH HERE**
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cd cayley
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make deps
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make
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```
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And the `cayley` binary will be built and ready.
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### Initialize A Graph
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Now that Cayley is built, let's create our database. `init` is the subcommand to set up a database and the right indices.
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You can set up a full [configuration file](/docs/Configuration) if you'd prefer, but it will also work from the command line.
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Examples for each backend:
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* `leveldb`: `./cayley init --db=leveldb --dbpath=/tmp/moviedb` -- where /tmp/moviedb is the path you'd like to store your data.
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* `mongodb`: `./cayley init --db=mongodb --dbpath="<HOSTNAME>:<PORT>"` -- where HOSTNAME and PORT point to your Mongo instance.
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Those two options (db and dbpath) are always going to be present. If you feel like not repeating yourself, setting up a configuration file for your backend might be something to do now. There's an example file, `cayley.cfg.example` in the root directory.
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You can repeat the `--db` and `--dbpath` flags from here forward instead of the config flag, but let's assume you created `cayley.cfg.overview`
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### Load Data Into A Graph
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Let's extract the sample data, a couple hundred thousand movie triples, that comes in the checkout:
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```bash
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zcat 30kmoviedatauniq.n3.gz > 30k.n3
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```
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Then, we can load the data.
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```bash
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./cayley load --config=cayley.cfg.overview --triples=30k.n3
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```
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And wait. It will load. If you'd like to watch it load, you can run
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```bash
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./cayley load --config=cayley.cfg.overview --triples=30k.n3 --alsologtostderr
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```
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And watch the log output go by.
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### Connect a REPL To Your Graph
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Now it's loaded. We can use Cayley now to connect to the graph. As you might have guessed, that command is:
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```bash
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./cayley repl --config=cayley.cfg.overview
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```
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Where you'll be given a `cayley>` prompt. It's expecting Gremlin/JS, but that can also be configured with a flag.
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This is great for testing, and ultimately also for scripting, but the real workhorse is the next step.
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### Serve Your Graph
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Just as before:
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```bash
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./cayley http --config=cayley.cfg.overview
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```
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And you'll see a message not unlike
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```bash
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Cayley now listening on 0.0.0.0:64210
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```
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If you visit that address (often, [http://localhost:64210](http://localhost:64210)) you'll see the full web interface and also have a graph ready to serve queries via the [HTTP API](/docs/HTTP)
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## UI Overview
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### Sidebar
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Along the side are the various actions or views you can take. From the top, these are:
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* Run Query (run the query)
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* Gremlin (a dropdown, to pick your query language)
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----
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* Query (a request/response editor for the query language)
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* Query Shape (a visualization of the shape of the final query. Does not execute the query.)
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* Visualize (runs a query and, if tagged correctly, gives a sigmajs view of the results)
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* Write (an interface to write or remove individual triples or triple files)
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----
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* Documentation (this documentation)
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### Visualize
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To use the visualize function, emit, either through tags or JS post-processing, a set of JSON objects containing the keys `source` and `target`. These will be the links, and nodes will automatically be detected.
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For example:
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```javascript
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[
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{
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"source": "node1"
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"target": "node2"
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},
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{
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"source": "node1"
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"target": "node3"
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},
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]
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```
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Other keys are ignored. The upshot is that if you use the "Tag" functionality to add "source" and "target" tags, you can extract and quickly view subgraphs.
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