We want to use pan.sh to execute multiple kettle transformations. After exploring the script I found that it internally calls spoon.sh script which runs in PDI. Now the problem is every time a new transformation starts it create a separate JVM for its executions(invoked via a .bat file), however I want to group them to use single JVM to overcome memory constraints that the multiple JVM are putting on the batch server.
Could somebody guide me on how can I achieve this or share the documentation/resources with me.
Thanks for the good work.
Use Carte. This is exactly what this is for. You can startup a server (on the local box if you like) and then submit your jobs to it. One JVM, one heap, shared resource.
Benefit of that is then scalability, so when your box becomes too busy just add another one, also using carte and start sending some of the jobs to that other server.
There's an old but still current blog here:
http://diethardsteiner.blogspot.co.uk/2011/01/pentaho-data-integration-remote.html
As well as doco on the pentaho website.
Starting the server is as simple as:
carte.sh <hostname> <port>
There is also a status page, which you can use to query your carte servers, so if you have a cluster of servers, you can pick a quiet one to send your job to.
Related
I am running Pentaho Kettle 6.1 through a java application. All of the Pentaho logs are directed through the java app and logged out into the same log file at the java level.
When a job starts or finishes the logs indicate which job is starting or finishing, but when the job is in the middle of running the log output only indicates the specific step it is on without any indication of which job or trans is executing.
This causes confusion and is difficult to follow when there is more than one job running simultaneously. Does anyone know of a way to prepend the name of the job or trans to each log entry?
Not that I know, and I doubt there is for the simple reason that the same transformation/job may be split to run on more than one machine, by more that one user, and/or launched in parallel in different job hierarchies of callers.
The general answer is to log in a database (right-click any where, Parameters, Logging, define the logging table and what you want to log). All the logging will be copied to a table database together with a channel_id. This is a unique number that will be attributed to each "run" and link together all the logging information that comes from all the dependent job/transformations. You can then view this info with a SELECT...WHERE channel_id=...
However, you case seams to be simpler. Use the database logging with a log_intervale of, say, 2 seconds and SELECT TRANSNAME/JOBNAME, LOG_FIELD FROM LOG_TABLE continuously on your terminal.
You can also follow a specific job/transformation by logging in a specific table, but this means you know in advance which is the job/transformation to debug.
Complete newbie to PigLatin, but looking to pull data from the MetOffice DataPoint API e.g.:
http://datapoint.metoffice.gov.uk/public/data/val/wxfcs/all/xml/350509?res=3hourly&key=abc123....
...into Hadoop.
My question is "Can this be undertaken using PigLatin (from within Pig View, in Ambari)"?
I've hunted round for how to format a GET request into the code, but without luck.
Am I barking up the wrong tree? Should I be looking to use a different service within the Hadoop framework to accomplish this?
It is very bad idea to make calls to external services from inside of map-reduce jobs. The reason being that when running on the cluster your jobs are very scalable whereas the external system might not be so. Modern resource managers like YARN make this situation even worse, when you swamp external system with the requests your tasks on the cluster will be mostly sleeping waiting for reply from the server. The resource manager will see that CPU is not being used by tasks and will schedule more of your tasks to run which will make even more requests to the external system, swamping it with the requests even more. I've seen modest 100 machine cluster putting out 100K requests per second.
What you really want to do is to either somehow get the bulk data from the web service or setup a system with a queue and few controlled number of workers that will pull from the external system at set rate.
As for your original question, I don't think PigLatin provides such service, but it could be easily done with UDFs either Python or Java. With Python you can use excellent requests library, which will make your UDF be about 6 lines of code. Java UDF will be little bit more verbose, but nothing terrible by Java standards.
"Can this be undertaken using PigLatin (from within Pig View, in
Ambari)"?
No, by default Pig load from HDFS storage, unless you write your own loader.
And i share same point with #Vlad, that this is not a good idea, you have many other other components used for data ingestion, but this not a use case of Pig !
There are plenty of documentation about how to write Pig UDFs in the various languages but I haven't found anything on how they are distributed to the data nodes.
Are they done automatically when pig script is invoked? If it makes any difference, I'd be writing UDF in Java.
Let me make it more clear. Whenever we wite a UDF and the pig is in hdfs mode. Then UDFs, which initially resides in the local or the client side, is carried to the cluster as per the internal architecture of hadoop. Now the UDFs task is performed by the task tracker and it becomes the duty of the job tracker to assign the the UDFs to task tracker, which is near to the data node where the input file resides.
Note: Its always the job tracker(component of name node), which actually decides which task tracker should perform the execution of the UDFs.
If the input file is in local file system(local mode), then the UFDs get executed in the local JVM.
The fact is apache pig works in two modes
1) local mode
2) hdfs mode
To answer you question, which belongs to pig running in hdfs mode, we only made sure that the input file that we are loading is present in the hdfs(data node). When the question comes for UDF, this is simply a function that is used to process the input file, just link pig latin language. We are writing UDFs, pig latin via the client side node and thus all the data related to this will be stored in the client side machine.
Above all, we have configure the pig so that client can interact with the hdfs to process the required result.
Hope this helps
after reading and searching about OS and process and threads, I checked on wiki and it said,
A computer program is a passive
collection of instructions, a process
is the actual execution of those
instructions. Several processes may be
associated with the same program; for
example, opening up several instances
of the same program often means more
than one process is being executed.
Now is it possible for a program to have more than one process and I am not including the possibility of running more than one instance of the same program. I mean one instance of one program is running, is it possible for a program to have more than one process?
If yes, how? If no, why not?
I am a newbie in this, but damn curious :)
Thanks for all your help..
Yes, fairly obviously - you can run two or more copies of most programs - I routinely have about 5 copies of vim running, and each of those is a separate process. As to how, the OS loads the executable file, creates a process and then tells that process to start executing the file contents.
It is most definitely possible but a desktop application might not be a good example and I think this is the source of your confusion.
Consider a webserver instead (NginX or Apache). There is one master process and multiple worker processes at work. The master process "accpets" the work , so to speak, and delegates it to the workers. Both NginX and Apache could be configured to any number of worker processes.
At our company we are in the business of delivering a SaaS that helps businesses have an online chat with their visitors via their websites. The back-end part of our system has multiple "service"es communicating with each other to accomplish the task. Each service has multiple instances running.
This question is for anyone who has actually used Amazon EC2. I'm looking into what it would take to deploy a server there.
It looks like I can start in VirtualBox, setup my server and then export the image using the provided ec2-tools.
What gets tricky is if I actually want to make configuration changes to my running server, they will not be persistent.
I have some PHP code that I need to be able to deploy (and redeploy) to the system, so I was thinking that EBS would be a good choice there.
I have a massive amount of data that I need stored, but it just so happens that latency is not an issue, so I was thinking something like s3fs might work.
So my question is... What would you do? What does your configuration look like? What have been particular challenges that perhaps you didn't see coming?
We have deployed a large-scale commercial app in the AWS environment.
There are three basic approaches to keeping your changes under control once the server is running, all of which we use in different situations:
Keep the changes in source control. Have a script that is part of your original image that can pull down the latest and greatest. You can pull down PHP code, Apache settings, whatever you need. If you need to restart your instance from your AMI (Amazon Machine Image), just run your script to get the latest code and configuration, and you're good to go.
Use EBS (Elastic Block Storage). EBS is like a big external hard drive that you can attach to your instance. Even if your instance goes away, EBS survives. If you later need two (or more) identical instances, you can give each one of them access to what you save in EBS. See https://stackoverflow.com/a/3630707/141172
Burn a new AMI after each change. There's a tool to create a new AMI from a running instance. If EBS is like having an external hard drive, creating a new AMI is like having a DVD-R. You can save the current state of your machine to it. Next time you have to start a new instance, base it on that new AMI. Good to go.
I recommend storing your PHP code in a repository such as SVN, and writing a script that checks the latest code out of the repository and redeploys it when you want to upgrade. You could also have this script run on instance startup so that you get the latest code whenever you spin up a new instance; saves on having to create a new AMI every time.
The main challenge that I didn't see coming with EC2 is instance startup time - especially with Windows. Linux instances take 5 to 10 minutes to launch, but I've seen Windows instances take up to 40 minutes; this can be an issue if you want to do dynamic load balancing and start up new instances when your load increases.
I'd suggest the best bet is to simply 'try it'. The charges to run a small instance are not high and data transfer rates are very low - I have moved quite a few GB and my data fees are still less than a dollar(!) in my first month. You will likely end up paying mostly for system time rather than data I suspect.
I haven't deployed yet but have run up an instance, migrated it from Ubuntu 8.04 to 8.10, tried different port security settings, seen what sort of access attempts unknown people have tried (mostly looking for phpadmin), run some testing against it and generally experimented with the config and restart of the components I'm deploying. It has been a good prelude to my end deployment. I won't be starting with a big DB so will be initially sticking with the standard EC2 instance space.
The only negativity I have heard it that some spammers have made some of the IP ranges subject to spam-blocking - but have not yet confirmed that.
Your virtual box approach I will suggest you take after you are more familiar with the EC2 infrastructure. I suggest that you go to EC2, open an account and follow Amazon's EC2 getting-started guide. This guide will give you enough overview on all things (EBS, IP, CONNECTIONS, and otherS) to get you started. We are currently using EC2 for production and the way we started was like I am explaining here.
I hope you become a Cloud Expert Soon.
Per timbo's concern, I was able to nab an IP that, so far hasn't legitimately shown up on any spam lists. You will have a few hiccups since many blacklists are technically whitelists and will have every IP on their list until otherwise notified that a Mail Server is running on that IP. It's really easy to remove, most of them have automated removal request forms and every one that doesn't has been very cooperative in removing me from their lists. Just be professional, ask if they can give a time and reason for the block and what steps you should take to remove your IP. All the services I have emailed never asked me to jump through any hoops, within two or three business days they all informed me my IP had been removed.
Still, if you plan on running a mail server I would recommend reserving IPs now. They're 1 cent per every hour they are not bound to an instance so it works out to being about $7 a month. I went ahead and reserved an extra one as I plan on starting up another instance soon.
I have deployed some simple stuff to EC2 Win2k3 instances. Here's my advice:
Find a tutorial. Sign up for the service. Just spend an afternoon setting up your first server. It's pretty darned easy, though there will be obstacles to overcome. It's not too tough.
When I was fooling with EC2 I think I spent like $2.00 setting up a server and playing with it for a while.
Some of your data will be persistent, but you can connect S3 to EC2 as well.
Just go for it!
With regards to the concerns about blacklisting of mail servers, you can also use Amazon's Simple Email Service (SES), which obviates the need to run the mail server on the EC2 instances.
I had trouble with this as well, but posted a note here in their forums - https://forums.aws.amazon.com/thread.jspa?threadID=80158&tstart=0