From 88181bee9e385361d0a079fbffa78124981799e0 Mon Sep 17 00:00:00 2001
From: Matei Zaharia <matei@eecs.berkeley.edu>
Date: Wed, 12 Sep 2012 19:47:31 -0700
Subject: [PATCH] Small tweaks to generated doc pages
---
docs/_layouts/global.html | 2 +
docs/contributing-to-spark.md | 3 +-
docs/css/main.css | 12 +++
docs/ec2-scripts.md | 146 ----------------------------------
docs/index.md | 3 +-
docs/running-on-mesos.md | 1 -
6 files changed, 16 insertions(+), 151 deletions(-)
delete mode 100644 docs/ec2-scripts.md
diff --git a/docs/_layouts/global.html b/docs/_layouts/global.html
index 402adca72c..8bfd0e7284 100755
--- a/docs/_layouts/global.html
+++ b/docs/_layouts/global.html
@@ -64,6 +64,8 @@
</div>
<div class="container">
+ <h1 class="title">{{ page.title }}</h1>
+
{{ content }}
<!-- Main hero unit for a primary marketing message or call to action -->
<!--<div class="hero-unit">
diff --git a/docs/contributing-to-spark.md b/docs/contributing-to-spark.md
index 3585bda2d3..a99ab41531 100644
--- a/docs/contributing-to-spark.md
+++ b/docs/contributing-to-spark.md
@@ -1,8 +1,7 @@
---
layout: global
-title: How to Contribute to Spark
+title: Contributing to Spark
---
-# Contributing to Spark
The Spark team welcomes contributions in the form of GitHub pull requests. Here are a few tips to get your contribution in:
diff --git a/docs/css/main.css b/docs/css/main.css
index 8432d0f911..cf56399376 100755
--- a/docs/css/main.css
+++ b/docs/css/main.css
@@ -15,10 +15,22 @@ body {
line-height: 1.6; /* Inspired by Github's wiki style */
}
+.title {
+ font-size: 32px;
+}
+
h1 {
font-size: 28px;
}
+h2 {
+ font-size: 24px;
+}
+
+h3 {
+ font-size: 21px;
+}
+
code {
color: #333;
}
diff --git a/docs/ec2-scripts.md b/docs/ec2-scripts.md
deleted file mode 100644
index 73578c8457..0000000000
--- a/docs/ec2-scripts.md
+++ /dev/null
@@ -1,146 +0,0 @@
----
-layout: global
-title: Using the Spark EC2 Scripts
----
-The `spark-ec2` script located in the Spark's `ec2` directory allows you
-to launch, manage and shut down Spark clusters on Amazon EC2. It builds
-on the [Mesos EC2 script](https://github.com/mesos/mesos/wiki/EC2-Scripts)
-in Apache Mesos.
-
-`spark-ec2` is designed to manage multiple named clusters. You can
-launch a new cluster (telling the script its size and giving it a name),
-shutdown an existing cluster, or log into a cluster. Each cluster is
-identified by placing its machines into EC2 security groups whose names
-are derived from the name of the cluster. For example, a cluster named
-`test` will contain a master node in a security group called
-`test-master`, and a number of slave nodes in a security group called
-`test-slaves`. The `spark-ec2` script will create these security groups
-for you based on the cluster name you request. You can also use them to
-identify machines belonging to each cluster in the EC2 Console or
-ElasticFox.
-
-This guide describes how to get set up to run clusters, how to launch
-clusters, how to run jobs on them, and how to shut them down.
-
-Before You Start
-================
-
-- Create an Amazon EC2 key pair for yourself. This can be done by
- logging into your Amazon Web Services account through the [AWS
- console](http://aws.amazon.com/console/), clicking Key Pairs on the
- left sidebar, and creating and downloading a key. Make sure that you
- set the permissions for the private key file to `600` (i.e. only you
- can read and write it) so that `ssh` will work.
-- Whenever you want to use the `spark-ec2` script, set the environment
- variables `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` to your
- Amazon EC2 access key ID and secret access key. These can be
- obtained from the [AWS homepage](http://aws.amazon.com/) by clicking
- Account \> Security Credentials \> Access Credentials.
-
-Launching a Cluster
-===================
-
-- Go into the `ec2` directory in the release of Spark you downloaded.
-- Run
- `./spark-ec2 -k <keypair> -i <key-file> -s <num-slaves> launch <cluster-name>`,
- where `<keypair>` is the name of your EC2 key pair (that you gave it
- when you created it), `<key-file>` is the private key file for your
- key pair, `<num-slaves>` is the number of slave nodes to launch (try
- 1 at first), and `<cluster-name>` is the name to give to your
- cluster.
-- After everything launches, check that Mesos is up and sees all the
- slaves by going to the Mesos Web UI link printed at the end of the
- script (`http://<master-hostname>:8080`).
-
-You can also run `./spark-ec2 --help` to see more usage options. The
-following options are worth pointing out:
-
-- `--instance-type=<INSTANCE_TYPE>` can be used to specify an EC2
-instance type to use. For now, the script only supports 64-bit instance
-types, and the default type is `m1.large` (which has 2 cores and 7.5 GB
-RAM). Refer to the Amazon pages about [EC2 instance
-types](http://aws.amazon.com/ec2/instance-types) and [EC2
-pricing](http://aws.amazon.com/ec2/#pricing) for information about other
-instance types.
-- `--zone=<EC2_ZONE>` can be used to specify an EC2 availability zone
-to launch instances in. Sometimes, you will get an error because there
-is not enough capacity in one zone, and you should try to launch in
-another. This happens mostly with the `m1.large` instance types;
-extra-large (both `m1.xlarge` and `c1.xlarge`) instances tend to be more
-available.
-- `--ebs-vol-size=GB` will attach an EBS volume with a given amount
- of space to each node so that you can have a persistent HDFS cluster
- on your nodes across cluster restarts (see below).
-- If one of your launches fails due to e.g. not having the right
-permissions on your private key file, you can run `launch` with the
-`--resume` option to restart the setup process on an existing cluster.
-
-Running Jobs
-============
-
-- Go into the `ec2` directory in the release of Spark you downloaded.
-- Run `./spark-ec2 -k <keypair> -i <key-file> login <cluster-name>` to
- SSH into the cluster, where `<keypair>` and `<key-file>` are as
- above. (This is just for convenience; you could also use
- the EC2 console.)
-- To deploy code or data within your cluster, you can log in and use the
- provided script `~/mesos-ec2/copy-dir`, which,
- given a directory path, RSYNCs it to the same location on all the slaves.
-- If your job needs to access large datasets, the fastest way to do
- that is to load them from Amazon S3 or an Amazon EBS device into an
- instance of the Hadoop Distributed File System (HDFS) on your nodes.
- The `spark-ec2` script already sets up a HDFS instance for you. It's
- installed in `/root/ephemeral-hdfs`, and can be accessed using the
- `bin/hadoop` script in that directory. Note that the data in this
- HDFS goes away when you stop and restart a machine.
-- There is also a *persistent HDFS* instance in
- `/root/presistent-hdfs` that will keep data across cluster restarts.
- Typically each node has relatively little space of persistent data
- (about 3 GB), but you can use the `--ebs-vol-size` option to
- `spark-ec2` to attach a persistent EBS volume to each node for
- storing the persistent HDFS.
-- Finally, if you get errors while running your jobs, look at the slave's logs
- for that job using the Mesos web UI (`http://<master-hostname>:8080`).
-
-Terminating a Cluster
-=====================
-
-***Note that there is no way to recover data on EC2 nodes after shutting
-them down! Make sure you have copied everything important off the nodes
-before stopping them.***
-
-- Go into the `ec2` directory in the release of Spark you downloaded.
-- Run `./spark-ec2 destroy <cluster-name>`.
-
-Pausing and Restarting Clusters
-===============================
-
-The `spark-ec2` script also supports pausing a cluster. In this case,
-the VMs are stopped but not terminated, so they
-***lose all data on ephemeral disks*** but keep the data in their
-root partitions and their `persistent-hdfs`. Stopped machines will not
-cost you any EC2 cycles, but ***will*** continue to cost money for EBS
-storage.
-
-- To stop one of your clusters, go into the `ec2` directory and run
-`./spark-ec2 stop <cluster-name>`.
-- To restart it later, run
-`./spark-ec2 -i <key-file> start <cluster-name>`.
-- To ultimately destroy the cluster and stop consuming EBS space, run
-`./spark-ec2 destroy <cluster-name>` as described in the previous
-section.
-
-Limitations
-===========
-
-- `spark-ec2` currently only launches machines in the US-East region of EC2.
- It should not be hard to make it launch VMs in other zones, but you will need
- to create your own AMIs in them.
-- Support for "cluster compute" nodes is limited -- there's no way to specify a
- locality group. However, you can launch slave nodes in your
- `<clusterName>-slaves` group manually and then use `spark-ec2 launch
- --resume` to start a cluster with them.
-- Support for spot instances is limited.
-
-If you have a patch or suggestion for one of these limitations, feel free to
-[contribute]({{HOME_PATH}}contributing-to-spark.html) it!
diff --git a/docs/index.md b/docs/index.md
index 48ab151e41..a3ad2d11ce 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,8 +1,7 @@
---
layout: global
-title: Spark - Fast Cluster Computing
+title: Spark Overview
---
-# Spark Overview
Spark is a MapReduce-like cluster computing framework designed to support low-latency iterative jobs and interactive use from an interpreter. It is written in [Scala](http://www.scala-lang.org), a high-level language for the JVM, and exposes a clean language-integrated syntax that makes it easy to write parallel jobs. Spark runs on top of the [Apache Mesos](http://incubator.apache.org/mesos/) cluster manager.
diff --git a/docs/running-on-mesos.md b/docs/running-on-mesos.md
index 9807228121..947de13855 100644
--- a/docs/running-on-mesos.md
+++ b/docs/running-on-mesos.md
@@ -2,7 +2,6 @@
layout: global
title: Running Spark on Mesos
---
-# Running Spark on Mesos
To run on a cluster, Spark uses the [Apache Mesos](http://incubator.apache.org/mesos/) resource manager. Follow the steps below to install Mesos and Spark:
--
GitLab