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Merge pull request #992 from metamx/update-doc-links 

update docs to point to druid-io/druid
This commit is contained in:
Fangjin Yang 2014-12-23 14:29:41 -08:00
parent bf4b52384c 47fa1b3d10
commit 85787270a3
7 changed files with 16 additions and 16 deletions
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docs/_includes/page_header.html
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@ -10,7 +10,7 @@
</div>
<div class="navbar-collapse collapse">
<ul class="nav navbar-nav">
<li {% if page.sectionid == 'docs' %} class="active"{% endif %}><a href="https://github.com/metamx/druid/wiki">Documentation</a></li>
<li {% if page.sectionid == 'docs' %} class="active"{% endif %}><a href="https://github.com/druid-io/druid/wiki">Documentation</a></li>
</ul>
</div>
</div>

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docs/content/Booting-a-production-cluster.md
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@ -25,7 +25,7 @@ Clone the code from [https://github.com/druid-io/whirr](https://github.com/druid
git checkout trunk
mvn clean install -Dmaven.test.failure.ignore=true
In order to run the test below, you'll also need two files that available only from a [standard install of Druid](http://druid.io/downloads.html) or the [Druid repo](https://github.com/metamx/druid/tree/master/examples/bin/examples):
In order to run the test below, you'll also need two files that available only from a [standard install of Druid](http://druid.io/downloads.html) or the [Druid repo](https://github.com/druid-io/druid/tree/master/examples/bin/examples):
* `druid/examples/bin/examples/wikipedia/wikipedia_realtime.spec`
* `druid/examples/bin/examples/indexing/wikipedia_realtime_task.json`

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docs/content/Build-from-source.md
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@ -6,7 +6,7 @@ layout: doc_page
The other way to setup Druid is from source via git. To do so, run these commands:
```
git clone git@github.com:metamx/druid.git
git clone git@github.com:druid-io/druid.git
cd druid
./build.sh
```

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docs/content/Examples.md
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@ -4,7 +4,7 @@ layout: doc_page
Examples
========
The examples on this page are setup in order to give you a feel for what Druid does in practice. They are quick demos of Druid based on [CliRealtimeExample](https://github.com/metamx/druid/blob/master/services/src/main/java/io/druid/cli/CliRealtimeExample.java). While you wouldn’t run it this way in production you should be able to see how ingestion works and the kind of exploratory queries that are possible. Everything that can be done on your box here can be scaled out to 10’s of billions of events and terabytes of data per day in a production cluster while still giving the snappy responsive exploratory queries.
The examples on this page are setup in order to give you a feel for what Druid does in practice. They are quick demos of Druid based on [CliRealtimeExample](https://github.com/druid-io/druid/blob/master/services/src/main/java/io/druid/cli/CliRealtimeExample.java). While you wouldn’t run it this way in production you should be able to see how ingestion works and the kind of exploratory queries that are possible. Everything that can be done on your box here can be scaled out to 10’s of billions of events and terabytes of data per day in a production cluster while still giving the snappy responsive exploratory queries.
Installing Standalone Druid
---------------------------
@ -16,7 +16,7 @@ There are two options for installing standalone Druid. Building from source, and
Clone Druid and build it:
``` bash
git clone https://github.com/metamx/druid.git druid
git clone https://github.com/druid-io/druid.git druid
cd druid
git fetch --tags
git checkout druid-0.6.160
@ -37,7 +37,7 @@ Twitter Example
For a full tutorial based on the twitter example, check out this [Twitter Tutorial](Twitter-Tutorial.html).
This Example uses a feature of Twitter that allows for sampling of it’s stream. We sample the Twitter stream via our [TwitterSpritzerFirehoseFactory](https://github.com/metamx/druid/blob/master/examples/src/main/java/druid/examples/twitter/TwitterSpritzerFirehoseFactory.java) class and use it to simulate the kinds of data you might ingest into Druid. Then, with the client part, the sample shows what kinds of analytics explorations you can do during and after the data is loaded.
This Example uses a feature of Twitter that allows for sampling of it’s stream. We sample the Twitter stream via our [TwitterSpritzerFirehoseFactory](https://github.com/druid-io/druid/blob/master/examples/src/main/java/druid/examples/twitter/TwitterSpritzerFirehoseFactory.java) class and use it to simulate the kinds of data you might ingest into Druid. Then, with the client part, the sample shows what kinds of analytics explorations you can do during and after the data is loaded.
### What you’ll learn
* See how large amounts of data gets ingested into Druid in real-time

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docs/content/Realtime.md
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@ -37,7 +37,7 @@ Extending the code
Realtime integration is intended to be extended in two ways:
1. Connect to data streams from varied systems ([Firehose](https://github.com/druid-io/druid-api/blob/master/src/main/java/io/druid/data/input/FirehoseFactory.java))
2. Adjust the publishing strategy to match your needs ([Plumber](https://github.com/metamx/druid/blob/master/server/src/main/java/io/druid/segment/realtime/plumber/PlumberSchool.java))
2. Adjust the publishing strategy to match your needs ([Plumber](https://github.com/druid-io/druid/blob/master/server/src/main/java/io/druid/segment/realtime/plumber/PlumberSchool.java))
The expectations are that the former will be very common and something that users of Druid will do on a fairly regular basis. Most users will probably never have to deal with the latter form of customization. Indeed, we hope that all potential use cases can be packaged up as part of Druid proper without requiring proprietary customization.

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docs/content/Recommendations.md
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@ -19,7 +19,7 @@ SSDs are highly recommended for historical and real-time nodes if you are not ru
# Provide Columns Names in Lexicographic Order
Although Druid supports schema-less ingestion of dimensions, because of [https://github.com/metamx/druid/issues/658](https://github.com/metamx/druid/issues/658), you may sometimes get bigger segments than necessary. To ensure segments are as compact as possible, providing dimension names in lexicographic order is recommended.
Although Druid supports schema-less ingestion of dimensions, because of [https://github.com/druid-io/druid/issues/658](https://github.com/druid-io/druid/issues/658), you may sometimes get bigger segments than necessary. To ensure segments are as compact as possible, providing dimension names in lexicographic order is recommended.
# Use Timeseries and TopN Queries Instead of GroupBy Where Possible

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docs/content/Stand-Alone-With-Riak-CS.md
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@ -110,7 +110,7 @@ This just walks through getting the relevant software installed and running. Yo
1. Clone the git repository for druid, checkout a "stable" tag and build
git clone https://github.com/metamx/druid.git druid
git clone https://github.com/druid-io/druid.git druid
pushd druid
git checkout druid-0.4.12
export LANGUAGE=C