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From u..@apache.org
Subject [2/2] flink git commit: [docs] Add separate AWS setup page
Date Tue, 05 Apr 2016 17:08:10 GMT
[docs] Add separate AWS setup page


Project: http://git-wip-us.apache.org/repos/asf/flink/repo
Commit: http://git-wip-us.apache.org/repos/asf/flink/commit/051fa2bc
Tree: http://git-wip-us.apache.org/repos/asf/flink/tree/051fa2bc
Diff: http://git-wip-us.apache.org/repos/asf/flink/diff/051fa2bc

Branch: refs/heads/master
Commit: 051fa2bc8151e2f7a251d2c9b7496f9cef98b47c
Parents: 02a3dfd
Author: Ufuk Celebi <uce@apache.org>
Authored: Tue Apr 5 19:06:24 2016 +0200
Committer: Ufuk Celebi <uce@apache.org>
Committed: Tue Apr 5 19:07:05 2016 +0200

----------------------------------------------------------------------
 docs/_plugins/panel.rb                     |  33 ++++
 docs/setup/aws.md                          | 233 ++++++++++++++++++++++++
 docs/setup/fig/flink-on-emr.png            | Bin 0 -> 103880 bytes
 docs/setup/jobmanager_high_availability.md |   2 +-
 4 files changed, 267 insertions(+), 1 deletion(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/flink/blob/051fa2bc/docs/_plugins/panel.rb
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diff --git a/docs/_plugins/panel.rb b/docs/_plugins/panel.rb
new file mode 100644
index 0000000..1dfef63
--- /dev/null
+++ b/docs/_plugins/panel.rb
@@ -0,0 +1,33 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+module Jekyll
+  class PanelTag < Liquid::Tag
+
+    def initialize(tag_name, text, tokens)
+      super
+      @text = text
+    end
+
+    def render(context)
+    	@text = @text.strip! || @text if !@text.nil?
+      "<div class=\"panel panel-default\"><div class=\"panel-body\" markdown=\"span\">#{@text}</div></div>"
+    end
+  end
+end
+
+Liquid::Template.register_tag('panel', Jekyll::PanelTag)

http://git-wip-us.apache.org/repos/asf/flink/blob/051fa2bc/docs/setup/aws.md
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diff --git a/docs/setup/aws.md b/docs/setup/aws.md
new file mode 100644
index 0000000..81efed7
--- /dev/null
+++ b/docs/setup/aws.md
@@ -0,0 +1,233 @@
+---
+title: "Amazon Web Services (AWS)"
+top-nav-group: deployment
+top-nav-pos: 5
+top-nav-title: AWS
+---
+
+Amazon Web Services offers cloud computing services on which you can run Flink.
+
+* ToC
+{:toc}
+
+## EMR: Elastic MapReduce
+
+[Amazon Elastic MapReduce](https://aws.amazon.com/elasticmapreduce/) (Amazon EMR) is a web
service that makes it easy to  quickly setup a Hadoop cluster. This is the **recommended way**
to run Flink on AWS as it takes care of setting up everything.
+
+### Create EMR Cluster
+
+The EMR documentation contains [examples showing how to start an EMR cluster](http://docs.aws.amazon.com/ElasticMapReduce/latest/ManagementGuide/emr-gs-launch-sample-cluster.html).
You can follow that guide and install any EMR release. You don't need to install *All Applications*
part of the EMR release, but can stick to *Core Hadoop*:
+
+<img src="fig/flink-on-emr.png" class="img-responsive">
+
+When creating your cluster, make sure to setup [IAM roles](http://docs.aws.amazon.com/ElasticMapReduce/latest/ManagementGuide/emr-iam-roles.html)
allowing you to access your S3 buckets if required.
+
+{% top %}
+
+### Install Flink on EMR Cluster
+
+After creating your cluster, you can [connect to the master node](http://docs.aws.amazon.com/ElasticMapReduce/latest/ManagementGuide/emr-connect-master-node.html)
and install Flink:
+
+1. Go the the [Downloads Page]({{ download_url}}) and **download a binary version of Flink
matching the Hadoop version** of your EMR cluster, e.g. Hadoop 2.7 for EMR releases 4.3.0,
4.4.0, or 4.5.0.
+2. Extract the Flink distribution and you are ready to deploy [Flink jobs via YARN]({{ site.baseurl
}}/setup/yarn_setup.html) after **setting the Hadoop config directory**:
+
+```bash
+HADOOP_CONF_DIR=/etc/hadoop/conf bin/flink run -m yarn-cluster examples/streaming/WordCount.jar
+```
+
+{% top %}
+
+## S3: Simple Storage Service
+
+[Amazon Simple Storage Service](http://aws.amazon.com/s3/) (Amazon S3) provides cloud object
storage for a variety of use cases. You can use S3 with Flink for **reading** and **writing
data** as well in conjunction with the [streaming **state backends**]({{ site.baseurl}}/apis/streaming/state_backends.html).
+
+You can use S3 objects like regular files by specifying paths in the following format:
+
+```
+s3://<your-bucket>/<endpoint>
+```
+
+The endpoint can either be a single file or a directory, for example:
+
+```java
+// Read from S3 bucket
+env.readTextFile("s3://<bucket>/<endpoint>");
+
+// Write to S3 bucket
+stream.writeAsText("s3://<bucket>/<endpoint>");
+
+// Use S3 as FsStatebackend
+env.setStateBackend(new FsStateBackend("s3://<your-bucket>/<endpoint>"));
+```
+
+Note that these examples are *not* exhaustive and you can use S3 in other places as well,
including your [high availability setup]({{ site.baseurl }}/setup/jobmanager_high_availability.html)
or the [RocksDBStateBackend]({{ site.baseurl }}/apis/streaming/state_backends.html#the-rocksdbstatebackend);
 everywhere that Flink expects a FileSystem URI.
+
+### Set S3 FileSystem
+
+{% panel **Note:** You don't have to configure this manually if you are running [Flink on
EMR](#emr-elastic-mapreduce). %}
+
+S3 is treated by Flink as a regular FileSystem. Interaction with S3 happens via a Hadoop
[S3 FileSystem client](https://wiki.apache.org/hadoop/AmazonS3).
+
+You need to point Flink to a valid Hadoop configuration, which contains the following property
in `core-site.xml`:
+
+```xml
+<property>
+  <name>fs.s3.impl</name>
+  <value>org.apache.hadoop.fs.s3native.NativeS3FileSystem</value>
+</property>
+```
+
+This registers `NativeS3FileSystem` as the default FileSystem for URIs with the `s3://` scheme.
+
+You can specify the [Hadoop configuration]({{ site.baseurl }}/setup/config.html#hdfs) in
various ways, for examples by configuring the path to the Hadoop configuration directory in
`flink-conf.yaml`:
+
+```
+fs.hdfs.hadoopconf: /path/to/etc/hadoop
+```
+
+This registers `path/to/etc/hadoop` as Hadoop's configuration directory with Flink.
+
+{% top %}
+
+### Configure Access Credentials
+
+{% panel **Note:** You don't have to configure this manually if you are running [Flink on
EMR](#emr-elastic-mapreduce). %}
+
+After setting up the S3 FileSystem, you need to make sure that Flink is allowed to access
your S3 buckets.
+
+#### Identity and Access Management (IAM) (Recommended)
+
+The recommended way of setting up credentials on AWS is via [Identity and Access Management
(IAM)](http://docs.aws.amazon.com/IAM/latest/UserGuide/introduction.html). You can use IAM
features to securely give Flink instances the credentials that they need in order to access
S3 buckets. Details about how to do this are beyond the scope of this documentation. Please
refer to the AWS user guide. What you are looking for are [IAM Roles](http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/iam-roles-for-amazon-ec2.html).
+
+If you set this up correctly, you can manage access to S3 within AWS and don't need to distribute
any access keys to Flink.
+
+{% top %}
+
+#### Access Keys (Not Recommended)
+
+Access to S3 can be granted via your **access and secret key pair**. Please note that this
is discouraged since the [introduction of IAM roles](https://blogs.aws.amazon.com/security/post/Tx1XG3FX6VMU6O5/A-safer-way-to-distribute-AWS-credentials-to-EC2).
+
+You need to configure both `fs.s3.awsAccessKeyId` and `fs.s3.awsSecretAccessKey`  in Hadoop's
 `core-site.xml`:
+
+```xml
+<property>
+  <name>fs.s3.awsAccessKeyId</name>
+  <value></value>
+</property>
+
+<property>
+  <name>fs.s3.awsSecretAccessKey</name>
+  <value></value>
+</property>
+```
+
+{% top %}
+
+### Provide S3 FileSystem Dependency
+
+{% panel **Note:** You don't have to configure this manually if you are running [Flink on
EMR](#emr-elastic-mapreduce). %}
+
+Hadoop's S3 FileSystem clients are packaged in the `hadoop-aws`. This JAR and all its dependencies
need to be added to Flink's classpath, i.e. the class path of both Job and TaskManagers.
+
+There are multiple ways of adding JARs to Flink's class path, the easiest being simply to
drop the JARs in Flink's `/lib` folder. You need to copy the `hadoop-aws` JAR with all its
dependencies (for Hadoop 2.6 that would be `hadoop-aws-2.6.2.jar` and `guava-11.0.2.jar` found
in `share/hadoop/tools/lib`).
+
+You can also export the directory containing these JARs (e.g. `hadoop-2.6.2/share/hadoop/tools/lib`)
as part of the `HADOOP_CLASSPATH` environment variable on all machines.
+
+{% top %}
+
+## Common Issues
+
+The following sections lists common issues when working with Flink on AWS.
+
+### Missing S3 FileSystem Configuration
+
+If your job submission fails with an Exception message noting that `No file system found
with scheme s3` this means that no FileSystem has been configured for S3. Please check out
the [FileSystem Configuration section](#set-s3-filesystem) for details on how to configure
this properly.
+
+```
+org.apache.flink.client.program.ProgramInvocationException: The program execution failed:
+  Failed to submit job cd927567a81b62d7da4c18eaa91c3c39 (WordCount Example) [...]
+Caused by: org.apache.flink.runtime.JobException: Creating the input splits caused an error:
+  No file system found with scheme s3, referenced in file URI 's3://<bucket>/<endpoint>'.
[...]
+Caused by: java.io.IOException: No file system found with scheme s3,
+  referenced in file URI 's3://<bucket>/<endpoint>'.
+    at o.a.f.core.fs.FileSystem.get(FileSystem.java:296)
+    at o.a.f.core.fs.Path.getFileSystem(Path.java:311)
+    at o.a.f.api.common.io.FileInputFormat.createInputSplits(FileInputFormat.java:450)
+    at o.a.f.api.common.io.FileInputFormat.createInputSplits(FileInputFormat.java:57)
+    at o.a.f.runtime.executiongraph.ExecutionJobVertex.<init>(ExecutionJobVertex.java:156)
+```
+
+{% top %}
+
+### AWS Access Key ID and Secret Access Key Not Specified
+
+If you see your job failing with an Exception noting that the `AWS Access Key ID and Secret
Access Key must be specified as the username or password`, your access credentials have not
been set up properly. Please refer to the [access credential section](#configure-access-credentials)
for details on how to configure this.
+
+```
+org.apache.flink.client.program.ProgramInvocationException: The program execution failed:
+  Failed to submit job cd927567a81b62d7da4c18eaa91c3c39 (WordCount Example) [...]
+Caused by: java.io.IOException: The given file URI (s3://<bucket>/<endpoint>)
points to the
+  HDFS NameNode at <bucket>, but the File System could not be initialized with that
address:
+  AWS Access Key ID and Secret Access Key must be specified as the username or password
+  (respectively) of a s3n URL, or by setting the fs.s3n.awsAccessKeyId
+  or fs.s3n.awsSecretAccessKey properties (respectively) [...]
+Caused by: java.lang.IllegalArgumentException: AWS Access Key ID and Secret Access Key must
+  be specified as the username or password (respectively) of a s3 URL, or by setting
+  the fs.s3n.awsAccessKeyId or fs.s3n.awsSecretAccessKey properties (respectively) [...]
+    at o.a.h.fs.s3.S3Credentials.initialize(S3Credentials.java:70)
+    at o.a.h.fs.s3native.Jets3tNativeFileSystemStore.initialize(Jets3tNativeFileSystemStore.java:80)
+    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
+    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
+    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
+    at java.lang.reflect.Method.invoke(Method.java:606)
+    at o.a.h.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
+    at o.a.h.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
+    at o.a.h.fs.s3native.$Proxy6.initialize(Unknown Source)
+    at o.a.h.fs.s3native.NativeS3FileSystem.initialize(NativeS3FileSystem.java:330)
+    at o.a.f.runtime.fs.hdfs.HadoopFileSystem.initialize(HadoopFileSystem.java:321)
+```
+
+{% top %}
+
+### ClassNotFoundException: NativeS3FileSystem Not Found
+
+If you see this Exception, the S3 FileSystem client is not part of the class path of Flink.
Please refer to [S3 FileSystem dependency section](#provide-s3-filesystem-dependency) for
details on how to configure this properly.
+
+```
+Caused by: java.lang.RuntimeException: java.lang.RuntimeException: java.lang.ClassNotFoundException:
Class org.apache.hadoop.fs.s3native.NativeS3FileSystem not found
+  at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2186)
+  at org.apache.flink.runtime.fs.hdfs.HadoopFileSystem.getHadoopWrapperClassNameForFileSystem(HadoopFileSystem.java:460)
+  at org.apache.flink.core.fs.FileSystem.getHadoopWrapperClassNameForFileSystem(FileSystem.java:352)
+  at org.apache.flink.core.fs.FileSystem.get(FileSystem.java:280)
+  at org.apache.flink.core.fs.Path.getFileSystem(Path.java:311)
+  at org.apache.flink.api.common.io.FileInputFormat.createInputSplits(FileInputFormat.java:450)
+  at org.apache.flink.api.common.io.FileInputFormat.createInputSplits(FileInputFormat.java:57)
+  at org.apache.flink.runtime.executiongraph.ExecutionJobVertex.<init>(ExecutionJobVertex.java:156)
+  ... 25 more
+Caused by: java.lang.RuntimeException: java.lang.ClassNotFoundException: Class org.apache.hadoop.fs.s3native.NativeS3FileSystem
not found
+  at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2154)
+  at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2178)
+  ... 32 more
+Caused by: java.lang.ClassNotFoundException: Class org.apache.hadoop.fs.s3native.NativeS3FileSystem
not found
+  at org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:2060)
+  at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2152)
+  ... 33 more
+```
+
+{% top %}
+
+### IOException: `400: Bad Request`
+
+If you you have configured everything properly, but get a `Bad Request` Exception **and**
your S3 bucket is located in region `eu-central-1`, you might be running an S3 client, which
does not support [Amazon's signature version 4](http://docs.aws.amazon.com/AmazonS3/latest/API/sig-v4-authenticating-requests.html).
+
+Currently, this includes all Hadoop versions up to 2.7.2, which depend on `JetS3t 0.9.0`
instead of a version [>= 0.9.4](http://www.jets3t.org/RELEASE_NOTES.html).
+
+The only workaround is to change the bucket region.
+
+```
+[...]
+Caused by: java.io.IOException: s3://<bucket-in-eu-central-1>/<endpoint> : 400
: Bad Request [...]
+Caused by: org.jets3t.service.impl.rest.HttpException [...]
+```
+
+{% top %}

http://git-wip-us.apache.org/repos/asf/flink/blob/051fa2bc/docs/setup/fig/flink-on-emr.png
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diff --git a/docs/setup/fig/flink-on-emr.png b/docs/setup/fig/flink-on-emr.png
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http://git-wip-us.apache.org/repos/asf/flink/blob/051fa2bc/docs/setup/jobmanager_high_availability.md
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diff --git a/docs/setup/jobmanager_high_availability.md b/docs/setup/jobmanager_high_availability.md
index ea2a460..5903dcb 100644
--- a/docs/setup/jobmanager_high_availability.md
+++ b/docs/setup/jobmanager_high_availability.md
@@ -2,7 +2,7 @@
 title: "JobManager High Availability (HA)"
 top-nav-group: deployment
 top-nav-title: High Availability
-top-nav-pos: 5
+top-nav-pos: 6
 ---
 <!--
 Licensed to the Apache Software Foundation (ASF) under one


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