There is a similar question here - Spark not installed on EMR cluster
But what I am trying to know is - there was .versions folder on AWS EMR cluster before AMI 4 versions e.g. ".versions/2.4.0-amzn-7/etc/hadoop" also there were spark installation folders on /home/hadoop.
Now everything is on /etc/ folder - like /etc/hadoop/conf
Is there any particular reason behind this config. Basically I need to custom bootstrap and I used /home/hadoop previously so I now need to shift to /etc/ ?
Thanks!
Please see the documentation for emr-4.x releases, in particular this page that details these kind of differences from prior versions: http://docs.aws.amazon.com/ElasticMapReduce/latest/ReleaseGuide/emr-release-differences.html
Related
I am facing some issues while trying to integrate Hadoop 3.x version on a Flink cluster. My goal is to use HDFS as a persistent storage and store checkpoints. I am currectly using Flink 1.13.1 and HDFS 3.3.1. The error that I am getting while trying to submit a job is that HDFS is not supported as a file system. In the standalone version, this error was solved by specifying the HADOOP_CLASSPATH on my local machine. As a next step I applied the solution above in all the machines that are used in my cluster and in the standalone version I managed to successfully submit my jobs in all of them without facing any issues. However, when I started modifying the configurations to setup my cluster (by specifying the IPs of my machines) that problem came up once again. What I am missing?
In Hadoop 2.x there are the pre-bundled jar files in the official flink download page that would solve similar issues in the past but that's not the case with Hadoop 3.x versions
It should be enough to set HADOOP_CLASSPATH on every machine in the cluster.
For anyone still struggling with a similar issue, the answer proposed by David worked for me in the end. The detail that I was missing was in the definition of the environment variables.
In my initial attempts, I was using the .bashrc script to permanently define my environment variables. This works in the standalone cluster which is not the case with a distributed cluster due to the scope of the script. What actually worked for me was defining my variables(and $HADOOP_CLASSPATH) in the /etc/profile
I also managed to find another solution while was struggling with HADOOP_CLASSPATH. As I mentioned in my initial post, in Hadoop 2.x there are pre-bundled jar files in the official Flink download page to support HDFS integration, which is not the case in Hadoop 3.x. I found the following maven repository page and after testing all of the existing jars I managed to find one that worked in my case. To be more precise, for Hadoop 3.3.1 the 3.1.1.7.2.8.0-224-9.0 jar (Placed the jar in the $FLINK_HOME/lib) worked. While it is not an "official solution" it seems to solve the issue.
https://mvnrepository.com/artifact/org.apache.flink/flink-shaded-hadoop-3-uber?repo=cloudera-repos
I started an EMR cluster in order to use test out sqoop but it turns out it doesnt seem to be installed on the latest version of EMR(5.19.0) as I didnt find it in the directory /usr/lib/sqoop. I tried 5.18.0 as well but it was missing there too.
According to the application versions page, sqoop 1.4.7 should be installed on the cluster.
The EMR console gives me a list of 4 "installations". I chose the Core Hadoop package. It has Hive, Hue, etc installed in /usr/lib. Am I missing something here? It's my first time using EMR or sqoop.
I did not see the "Advanced Options" link at the top of the "Create Cluster" page where I can select individual software to install.
When creating an EMR cluster, use the advanced options link where it allows you to select sqoop.
I am trying to run pdftk on an Elastic Beanstalk. The first problem I run into is that I cannot install pdftk on an instance of a Amazon Linux AMI because one of the dependencies (gcj) is not supported.
One of the options I am looking at is creating my own AMI and using that for my Elastic Beanstalk. Amazon recommends not doing this, and there are no community images for EB and Ubuntu.
Another option is using Docker. I am not as familiar with Docker, but I think I would be able to install pdftk in a container and then deploy that to EB. I am using Codeship for deployments and it looks like they have some options for Docker. (This is the options I'm currently exploring)
The last option I can think of is writing a library for encrypting pdfs on my own. I had a look at the encryption specifications for pdfs and I think this is not a time efficient option.
Has any one had a similar problem and found a good solution to the problem?
UPDATE:
After some more research I discovered that the issue was not with Amazon Linux bug with Fedora. Fedora dropped gcj because there was a lack of maintainers on the project, then dropped pdftk because it depends on gcj.
If you need another pdf tool kit I have found podofo to be a good replacement for what I've needed.
First I apologise for resurrecting an old thread! Recently we wanted to create an Elastic Beanstalk worker environment that uses pdftk. Of course we also stumbled on the same issue, so this is what we did and it works for us so far. I hope it'll work for others too.
In the .ebextensions folder add the linked configs:
The needed LaTeX packages:
packages.config
You'll also need to add the el5 library in order to install libgcj.
01_el5_yum.config
Next add this config with the commands to install libgcj, pdftk and pdfjam
02_pdftk.config
And that should be it.
In case anyone comes here having problems with pdftk - poppler-utils also cover some tasks done by pdftk (in my case it was pdf splitting) and can be easily set up on an EB instance through .ebextensions:
packages:
yum:
poppler-utils: []
Is it possible or advisable to run WebHCat on an Amazon Elastic MapReduce cluster?
I'm new to this technology and I was wonder if it was possible to use WebHCat as a REST interface to run Hive queries. The cluster in question is running Hive.
I wasn't able to get it working but WebHCat is actually installed by default on Amazon's EMR instance.
To get it running you have to do the following,
chmod u+x /home/hadoop/hive/hcatalog/bin/hcat
chmod u+x /home/hadoop/hive/hcatalog/sbin/webhcat_server.sh
export TEMPLETON_HOME=/home/hadoop/.versions/hive-0.11.0/hcatalog/
export HCAT_PREFIX=/home/hadoop/.versions/hive-0.11.0/hcatalog/
/home/hadoop/hive/hcatalog/webhcat_server.sh start
You can then confirm that it's running on port 50111 using curl,
curl -i http://localhost:50111/templeton/v1/status
To hit 50111 on other machines you have to open the port up in the EC2 EMR security group.
You then have to configure the users you going to "proxy" when you run queries in hcatalog. I didn't actually save this configuration, but it is outlined in the WebHCat documentation. I wish they had some concrete examples there but basically I ended up configuring the local 'hadoop' user as the one that run the queries, not the most secure thing to do I am sure, but I was just trying to get it up and running.
Attempting a query then gave me this error,
{"error":"Server IPC version 9 cannot communicate with client version
4"}
The workaround was to switch off of the latest EMR image (3.0.4 with Hadoop 2.2.0) and switch to a Hadoop 1.0 image (2.4.2 with Hadoop 1.0.3).
I then hit another issues where it couldn't find the Hive jar properly, after struggling with the configuration more, I decided I had dumped enough time into trying to get this to work and decided to communicate with Hive directly (using RBHive for Ruby and JDBC for the JVM).
To answer my own question, it is possible to run WebHCat on EMR, but it's not documented at all (Googling lead me nowhere which is why I created this question in the first place, it's currently the first hit when you search "WebHCat EMR") and the WebHCat documentation leaves a lot to be desired. Getting it to work seems like a pain, though my hope is that by writing up the initial steps someone will come along and take it the rest of the way and post a complete answer.
I did not test it but, it should be doable.
EMR allows to customise the bootstrap actions, i.e. the scripts run where the nodes are started. You can use bootstrap actions to install additional software and to change the configuration of applications on the cluster
See more details at http://docs.aws.amazon.com/ElasticMapReduce/latest/DeveloperGuide/emr-plan-bootstrap.html.
I would create a shell script to install WebHCat and test your script on a regular EC2 instance first (outside the context of EMR - just as a test to ensure your script is OK)
You can use EC2's user-data properties to test your script, typically :
#!/bin/bash
curl http://path_to_your_install_script.sh | sh
Then - once you know the script is working - make it available to the cluster on a S3 bucket and follow these instructions to include your script as custom bootstrap action of your cluster.
--Seb
I am trying to setup an AMI such that, when booted it will auto configure itself with a defined "configuration" somewhere on a server. I came across Chef and Puppet. Considering Puppet, I was able to run though their examples but couldn't see one for auto configuration from master. I found out that Puppet Enterprise is not supported on "Amazon Linux". Team chose Amazon Linux and would like keep that instead of going to other OS just because one tool doesn't support it. Can someone please give me some idea about how I could achieve this? (I am trying to stay away from home grown shell scripts over a good industry adopted tool for maintainability)
What I have done in the past is to copy /etc/rc.local to /etc/rc.local.orig, and then configure /etc/rc.local to kick off a puppet run and then pave over itself.
/etc/rc.local:
#!/bin/bash
##
#add pre-puppeting stuff here, I add the hostname in "User-data" when creating the VM so I can set the hostname before checking in
##
/usr/bin/puppet agent --test
/bin/cp -f /etc/rc.local.orig /etc/rc.local
/sbin/init 6
AWS CloudFormation is one of Amazon's recommended ways to provision servers (and other cloud resources, too). You declare all the resources you need in a JSON file, and specify how to provision each server by declaring packages to install, services to run, files to create, and commands to run when the server is created. See the user guide for more information. I also wrote a couple of blog posts about getting started with it.