Posts tagged: batch

Office Grid Computing using Virtual environments – Part 4

By , Friday 4th December 2009 11:59 pm

Introduction

I work in a company where we run many batch jobs processing millions of records of data each day and I’ve been thinking recently about all the machines that sit around each and every day doing nothing for several hours. Wouldn’t it be good if we could use those machines to bolster the processing power of our systems? In this set of articles I’m going to look at the potential benefits of employing an office grid using virtualised environments.

In part 3 we created our virtual processing machine and set up windows machines to become idle-time workers.

Running the latest code

Inevitably after creating your workers business logic will change, bugs will be found, faster more efficient code will be produced thus leaving your workers sat around processing data using old smelly code. How then do we ensure that we’re always using the latest and greatest version of our processing scripts?

There are a few very easy simple ways we could do this, the trick, however, is to reduce processing power and network traffic in achieving this. Lets start with the simplest of solutions and improve it slowly over a couple of iterations.

The first method would be to simply connect to our job control server (via samba, FTP, or similar) and pull down the latest version of the code. Not very efficient, but it will do the job. Lets improve on that somewhat, how about creating an rsync script and using that each time instead? Alternatively what about putting our latest processing script into subversion checking out the code initially and then just updating our code on each run (svn update)?

In the end we could end up with a bash script (called by cron every 10 minutes) which looks as simple as this:

#!/bin/sh
if ps ax | grep -v grep | grep php > /dev/null
then
    echo "Job is currently processing, exit"
else
    echo "Job is not running, start now"
    cd /path/to/working/copy
    svn update
    php yourJobProcessingScript.php
fi

Now we can be sure that with each run we’re definitely running the latest code. We’re ensuring this by updating our code base each and every time we perform a run and reducing network traffic by only transferring the file differences across our network.

In my demonstration setup, I did exactly as above. Subversion was installed on my job processing server and I simply pulled the latest code from a ‘worker’ branch using ‘svn update’. I also added a version number tag to my processing script which was returned to the database as part of the results return. This way I could see that my code was being updated each time I copied my trunk into the worker branch i.e. that I was definitely running the latest processing script.

Using the latest data

If your job processing makes use of data sources then at some point these are going to be updated too. Unless you call your data sources on a very infrequent basis you’re going to flood your network with traffic as soon as your workers start running bringing everything to a standstill. For my solution I decided that I’d like to move my data sources around with my VMs.

Hold you’re horses there! What if my data sources are HUGE? Well this really is a case of how much data are we talking? It may be more cost effective to install an additional larger hard drive into each machine than to purchase an additional processing server. This is a question of budget and is up to the business to decide. It maybe that your data sources are so large that its just unfeasible to keep that amount of data in your worker machines. In that case what would you do? Well we could look at calling a local data server, but this might cause issues with the network. In this case a grid system such as this may become unrealistic to include in your office environment. It may also be that you can look into alternative running strategies, for example only calling your workers between 8pm and 6am each night and/or throttling data source requests.

Moving on lets say our data sources amount to 100Gb of data. Well yes that’s quite a bit of data to move around the network on an update. How would we ensure that we have the latest copy of the data in this case? Rsync is a possibility, but personally I think by running your latest data source on your job processing server and setting this up as a master in replication (with a nice long bin log) might be the way to go:

replication By setting each of your workers up as a slave to the job control server updates to your data sources will trickle down nicely to your workers without a huge increase in network activity (that is unless you perform a huge data update and all your workers kick in at once). This has advantages over rsync in that you wouldn’t get a long pause before each job; as the database updates, the mysql daemon on your worker will continually update its data while the processing continues.

This is how I set up my demonstration server. To set up replication I followed the guide on the mySQL site (Setting up replication) and within 20 minutes I had my inital worker replicating the job control servers dataset. For each additional worker the replication settings and process worked each time when the VM was copied.

Summary

In this section of the article we have looked at how easy and painless it is to keep your processing code up to date by using  rsync or subverion (SVN) to do the work and reduce network traffic at the same time.  We also discussed how to keep your data source information up-to-date by allowing it to trickle down to each of your workers. Thus we are  ensuring that we keep up with business logic and information in our office grid system. There will obviously be countless alternatives to performing these tasks, but here were two simple examples to show how easy a solution is to come by.

Next time

In the final part of this series, aptly named Part 5 , we’ll discuss deploying this system for. I’ll summarise what has been learned and what I managed to create.

Office Grid Computing using Virtual environments – Part 1

By , Friday 4th December 2009 11:23 pm

Introduction

I work in a company where we run many batch jobs processing millions of records of data each day and I’ve been thinking recently about all the machines that sit around each and every day doing nothing for several hours. Wouldn’t it be good if we could use those machines to bolster the processing power of our systems? In this set of articles I’m going to look at the potential benefits of employing an office grid using virtualised environments.

As a PHP developer I’m going to use tools that I use each day namely, Linux, mySQL, PHP, VirtualBox and subversion (SVN). However I hope this guide will adapt to other languages and technologies just as well.

The solution I provide will be very loosely based on the type of processing we’d need to achieve however this may not be true through the entire article as I’ll change things for simplicity, or to produce more interesting usage scenarios.

These virtualised environments will run on windows machines since this is what the majority of offices run. The processing that the office machines do should not interfere with staff using those machines, should require no maintenance at the machine, and be easily deployable to new machines as they become available. Also, new virtual machines should not require any additional configuration as this greatly reduces the scalability and ease at which the grid system can be extended.

Why Deploy an Office Computing Grid?

Firstly you may be thinking,why not just use a cloud computing resource such as Amazon’s EC2 platform? Well the reasons could be several, for example:

  • You won’t entrust certain data to a cloud computing environment
  • You can’t put certain data into a cloud computing environment for legal reasons (e.g. data leaving the country), potentially for legal reasons, e.g. NHS records.
  • You want to keep your processing units close and have full control over the hardware too
  • You don’t have the project funds to run cloud instances
  • Your office doesn’t have a connection to the internet and therefore its not possible to use a cloud resource
  • You don’t like rain, clouds suggest rain, therefore you keep well away

I’m sure the list could continue, but I think that’s enough for now.

Advantages of an Office Computing Grid

Well, lets do some maths (and in true physics style lets make some sweeping assumptions). Imagine you have big beefy processing server running 100 jobs per day. In your office you have 50 machines which are idle 16 hours a day, each of these machines is 10% as powerful as your beefy processing sever. (All results here are rounded to underestimate performance increase).

So, 1 machine * 10% power * 2/3 time = 0.067 i.e. 1 desktop processing in idle time could process 6 full jobs per day.

If you now scale this up it takes 15 idle desktops to process as many jobs per day as your main processing server does.

So in our pretend office of 50 machines we could increase our processing power from 1 server up to 4 full processing servers, or we could be processing 400 jobs per day instead of 100.

Notice, for no investment in new hardware your company has just increased its batch processing capacity 4 times! Potentially you’re going to increase your power usage but from most office environments I’ve been to machines are generally left on overnight anyway, so you could see this as a green initiative.

Other advantages also mean that investment in new (or updated) processing servers can be delayed if your office machines are sufficient and that as you improve the power of your office machines your office grid becomes more powerful automatically.

Technologies

What you need? (or more correctly what did I use):

  • Idle office machines (in my case a spare old windows XP laptop)
  • VirtualBox (or another virtualisation client software)
  • A virtual machine with PHP, mySQL running  running a cut down OS, I’m calling these my LiMP servers :)
  • Jobs to run
  • Job server (can be another virtual machine somewhere)

Typical Jobs

The types of jobs that this system is designed to run is as follows:

  • System receives a list of data upon which we need to match and return results
  • Matching involves checking/searching several (fairly static) data sources
  • Results from data sources may require further validation, merging, checking of additional data sources in response to results
  • Data is returned with matching records, fully validated and processed
  • Each record within a job is independent of the rest

So basically we’re looking at running jobs which require a mixture of database lookups and some number crunching, a fairly typical scenario in a business environment.

Grid solutions are not only advantageous for processing jobs of this type. Basically, any process which can be split into independent units can be run in parallel. See this wikipedia for examples and more information: Grid Computing, but a couple of famous examples are Seti@Home and BIONC. There are frameworks for running computing grids, and these are well worth looking into.

What will we achieve?

By the end of these articles I hope to show that deploying an office grid need not be hugely expensive or time consuming. I’m going to discuss:

  • Setting up the job control system, job configuration
  • Creating an appropriate processing virtual machine
  • How to setup the system on a windows machine
  • Ensuring you are using the latest code and data
  • Deployment and benchmarking
  • Looking ahead

I’ll be building (ok I built, then wrote this) an example application to test the concepts on a local machine using windows XP and my ‘GridMachine’ virtual machine. My job control server will be my main machine which runs Fedora 11.

This is in no way meant to demonstrate a fully working robust system, its meant more of a demonstration and discussing showing that these things can be achieved in a reasonably short space of time and at little cost. Please feel free to send me any comments, corrections, or improvements and I’ll do my best to keep this article updated to match.

Next time

In part 2 I will start by looking at the job control system, and look into how jobs should be configured in order to achieve greatest amount of processing whilst ensuring that each job is processed without fail.

Office Grid Computing using Virtual environments – Part 2

By , Friday 4th December 2009 11:23 pm

Introduction

I work in a company where we run many batch jobs processing millions of records of data each day and I’ve been thinking recently about all the machines that sit around each and every day doing nothing for several hours. Wouldn’t it be good if we could use those machines to bolster the processing power of our systems? In this set of articles I’m going to look at the potential benefits of employing an office grid using virtualised environments.

In Part 1 I gave an overview of the system and technologies I will be using as well as discussed some of the potential reasons why you would want to create an office grid.

Job Control

If you’re going to be running jobs then you’re going to need some way to manage them. Your job control system (on your job server) needs to be really well thought out before even attempting to run an office grid. So firstly, what are the tasks for a job control system:

  • Hand out jobs upon request from workers
  • Tell workers what type of jobs to run
  • Track jobs
  • Ensure that jobs are only run once
  • Provide job data to workers, or at least tell them where to get it

The system also needs to be extensible, a solution that works for now in a single case may be extended to run several types of jobs as the business sees the worth in a grid solution. For example, jobs may gain priorities, more than one job type may exist (i.e. several code bases), eventually you may even run several different worker machines that are optimised for each type of job (although that does move away from the ‘generic worker’ idea). Always try to think about the future when developing systems, a short term vision can lead to longer term frustration and increased development time.

Job Server

We’re going to need somewhere to control our jobs from, this should be the only system in your grid that has a fixed resource locator, be that an IP address, host name, URL (using internal DNS), etc. This is because the workers need to know where to look for jobs, workers need to find the job control system (not the job control system find the workers).

The job server itself doesn’t really have a complicated task (in a basic system anyhow), it needs to store a list of jobs, hand out jobs, receive results, and subsequently store them for later retrieval. How these parts (such as ‘hand out jobs’) are defined can be very basic. Later on we can extend the system to include an administration interface to add, edit, delete, suspend jobs but this is beyond this exercise.

There is no reason whatsoever then that your job server could not be a virtual machine running within your main processing server provided it doesn’t drain too many resources from it. The job server however does need high availability, if it goes down on a Friday evening you’re going to lose a whole weekend of processing, potentially costing you a couple of weeks worth of processing time (when compared to your main processing server alone). You may want to consider putting your job server on a load balanced environment for high availability.

Basic Setup

The basic setup for our job server will consist of what I’m calling one of my LiMP servers (that is Linux, mySql, PHP). The code running on the  workers will actually work out what jobs it can run by interacting with with job control system databases. Later on we could create a web service and actually hand out jobs rather than having the workers do the hard work themselves, but for now we’ll continue using the KISS principle (Keep it Simple, Stupid!).

So, lets create three mySQL tables to deal with jobs. These will be `jobs`, `jobRecords`, and `jobResults`.

jobs table Here I’m using SQL Buddy a great little alternative to phpMyAdmin just because its easier to install on centOS (for others see: 10 Great alternatives to phpMyAdmin)

This table consists of 5 simple fields,

  • id: Uniquely identify the job
  • name: Could be a client reference, or any number of other identifiers
  • Status: You need to know where the job is at, e.g.
    • 0: Not started
    • 1: Picked up
    • 2: Completed
  • started_by: Who’s started doing the job? This isn’t entirely required but is a nice to have. I’d suggest tracking workers by their IP address on your network
  • started_at: When did the worker start the job? By tracking jobs that have not completed within X amount of time we know we need to pick up the job once again and start processing by another worker. Workers could stop processing/go offline for any number of reasons, power failure, crash, network loss, etc.

It is easy how this table could be extended with a few additional fields to allow for statistics tracking, a finish time column to see how long the job took, a counter to see how many workers picked up the job (obviously this needs to tend to 1), job priority, the list can go on and on. In more complex job scenarios it would be possible to specify how much memory the worker would need access to (and therefore only use suitable workers), or even what type of worker would be required.

Lets add a few example jobs:

example jobs

The next table again is quite simple to understand, these are our job records. They are linked to the main jobs table by a column `jobs_id`. The make up of this table very much depends on the data that you need to supply to your workers, lets make a very simple example where we have four columns:

  • id: ID of the record
  • name: Person’s name
  • address: Person’s address
  • jobs_id: The job ID that this record is linked to

The third and final table consists of a results table, it has much the same make up as our records table, and with the addition of some columns could be part of the records table:

  • job_record_id: Link the result to the job table
  • result: The result data

…and that’s all you need for job control! (albeit at a very basic level) In my case I’m pointed to another table where my data to process was located, but this could just as easily been a file, parameters to run simulation code, you name it.

Selecting a job

As stated previously, the workers will do our job management for us for now, so all we need to really do is find a job that needs processing and get the information. How would we do this? Well pick our job selection criteria and look for jobs, in SQL I did the following:

  1. Take any jobs that are not marked as complete but from our worker and reset them (substitute __ME__ with an identifier, easiest would be IP address):
    UPDATE `jobs` SET `status` = 0 WHERE `status` = 1 AND `started_by` = __ME__;
  2. Using our job selection criteria, select a job and tell the control system that this worker is dealing with it:
    UPDATE `jobs` SET `status` = 1, `started_by` = __ME__, `started_at` = NOW() WHERE `status` = 0 OR
    (`status` = 1 AND `started_at` > DATE_SUB(NOW(), INTERVAL X HOUR)) ORDER BY `id` ASC;

    By grabbing jobs that haven’t returned results in X amount of time we ensure that all jobs are run in the event of a worker crashing or going AWOL.

  3. Next grab the jobs details followed by the records themselves:
    SELECT * FROM `jobs` WHERE `started_by` = __ME__  LIMIT 1;
    SELECT * FROM `job_records` WHERE `id` = __JOBID__;

Upon completion of the job we insert our result records and mark the job as complete. Remember as jobs can suspend/resume at any time allow for some robustness in your script. It might be that the task suspends half way through updating the job control system, so checking the number of records in a job and the number of results saved back to the job control system would be a wise move.

In addition, whilst this demonstrates how jobs can be selected and managed from an SQL-query frame you should really be abstracting your job control so that if you decide to switch to using a web service, a file based system, XML, or any other number of systems it will not affect the code above it.

Job Configuration

The next aspect to consider is job size and configuration. By playing with job configuration we can strike an excellent balance between speed, process replication, and reliability. Take a couple of  scenarios:

  1. Jobs take 1 day each to run: This means that your workers need 15 days to process each job (remember 10% of the power for 2/3rds of the time). This is clearly not a wise configuration, your job size is way too big! It would take at least double the time to get a job processed should the initial worker go AWOL (time to pick up that it hasn’t returned a result plus reprocessing time). In an ideal you’d have at least one full job easily cleared by the end of each long idle period, that way you keep the jobs ticking over and at worst case a job would take two days to process should the first go missing.
  2. Jobs take 1 minute to run: This means that your workers take about 15 minutes to run each job. Whilst this may initially seem ideal, you gain additional work processing during lunch time, coffee breaks, meetings, etc this scenario puts strain on other areas of your system and introduces its own problems. For example, firstly your setup/processing time ratio is going to go right down, therefore losing system efficiency. Your network is going to be constantly streaming job information to the various workers frustrating staff who are dong their day to day work. You’re also going to put more strain on your job processing server as it has to dish out lots and lots of small pieces of work on a regular basis. Lastly, in this situation if your job server goes down you’re going to create a huge back log of uncompleted work whereas bigger jobs could of continued processing blissfully unaware that the job server was experiencing difficulties.

In reality there will be no one ideal configuration for your grid setup, much depends on the available resources, types of job, job turnaround time requirements, network capability, and so on. However some guidelines would be:

  • Size jobs so that each worker can get through at least 3-4 jobs in a period of 15 hours (the longest likely idle time period)
  • Play with the job size so that setup time becomes fairly insignificant compared to the processing time (bearing in mind the above point).
  • If a job doesn’t complete in double the amount of time (maybe less) you expect it to complete it assume that its gone AWOL and start processing it with another worker. This means you may have to wait up to three times the normal length of a job for it to complete (possibly longer if the subsequent job fails). You may want to reduce this time, but be careful not to reduce it too much as you may start duplicating processing tasks on a regular basis.
  • Jobs should be independent of outside requirements as much as possible. The job server, for example, should only be contacted at the start and end of every job.
  • Don’t saturate your network, this will have two negative effects, your daytime staff will find using the network frustrating and problems may be experienced with connections timing out a problem that will only get worse as you scale your grid.
  • Ensure jobs can run on your workers. If jobs become too memory intensive or disk space intensive jobs will start aborting and the only thing you’ll notice is a drop in number of jobs processed with no real reason why.

Submitting Results of a Job

When submitting the results of a job it is important to check that results have not been submitted by another worker, especially if the current worker has been dormant for some time.

When results are submitted ensure that the number of results matches the number of records within the job.

As stated previously, and can not be over emphasised, build fault tolerance into job retrieval and results submission. The workers can (and most likely will) go into suspend mode at the most inconvenient of times and this needs to be catered for. Also once again abstracting away your results submission will help cater for future changes to your job control system much easier to deal with.

Summary

In this section  we have looked at what a job control server needs to do and how to get a very basic system set up. We discussed how to retrieve a job from the control system and how best to configure jobs to get the most our of your office grid system. To finish, a paragraph or two on submitting results back to the job control server was presented.

  • A job control server manages jobs and ensures that all work units are completed
  • By abstracting your job select/results submission we can change the technology of the control server without much problems
  • Configure your jobs to ensure that they are run quickly and efficiently without putting too much pressure on your network infrastructure, and without duplicating processing tasks on a regular basis.
  • Ensure that you build fault tolerance and error checking  into your routines, workers can suspend and resume and the most inconvenient of times. Remember to check if results have already been submitted by another worker.

Next time

In part 3 we’ll create our virtual processing machine and set up our windows machines to become idle-time workers.

Office Grid Computing using Virtual environments – Part 5

By , Friday 4th December 2009 11:03 pm

Introduction

I work in a company where we run many batch jobs processing millions of records of data each day and I’ve been thinking recently about all the machines that sit around each and every day doing nothing for several hours. Wouldn’t it be good if we could use those machines to bolster the processing power of our systems? In this set of articles I’m going to look at the potential benefits of employing an office grid using virtualised environments.

In Part 4 we looked at using tools to ensure that we’re running the latest version of the code and data sources so that obtained results are always up-to-date with the latest business information and logic.

Pre-Deployment

Before deploying your grid system if there’s one thing you do and one thing alone it’s benchmark your current system! No matter what you tell colleagues about how much extra work your system is going to do unless you have numbers to back this up your guarantees are nothing. So,

  • how many records can you process currently? Per Day? Per Hour?
  • How long does it typically take to turn around a job?
  • How much more capacity do you have?

There’s also additional questions:

  • If your processing server (or one of your processing servers) goes down how will this affect your capabilities, will you be crippled?
  • What advantages do you hope/expect to get from a grid system?
  • Are your office machines capable of running the jobs?
  • Are your (or can you jobs be converted) to wrok in this style of running?

The last major point is to take your time on any major change like this. Update your processing code to work using the new methodology, benchmark again. Possibly set up your processing server to run a virtual machine, after all your processing server will just be another worker (just a very powerful one relatively). Allow the new process to settle.

Deployment

My suggestion would be to pop into the office one weekend perform all the installations and setup. Do this just before a fortnight’s holiday and leave so other poor chap to deal with the consequences… maybe not…

Deployment for a system like this needs to be slow. Despite it being relatively simple to set up this system will affect your entire office infrastructure (well the digital one). Firstly, roll out to a couple of machines at a time, monitor network traffic, how the worker hosts perform on a day-to-day basis. You may need to alter your job configuration in response to your findings.

Once the system has settled with a few machines (lets say 10% of all office machines, i.e. 5) keep monitoring network traffic and host machine performance.  Next benchmark again, you should now be processing 33% more jobs than your first benchmarks. Check this is so, or that you’re at least in this ballpark. If not, investigate what is going on before moving on. Repeat this cycle until you happily have all office machines running without killing individual machine performance or grinding your network to a standstill.

At all times keep benchmarking, even after all deployments are made. Check how new code updates affect speed of your system, check all workers are reporting in and processing jobs. Slowly (very slowly) increment your job configuration to get the best from your workers and network.

Stop!

What if you want to stop your workers from running at some time? They are all out there running, regenerating, and trying their best to process data like hungry insects. The answer may seem obvious but its worth adding just in case its overlooked. Simply edit your processing script with an exit(0) or die() or some other statement to kill your processing job. An important reason why we always try to update to the latest processing script before any run!

Demonstration System

In order to write this set of short articles I created a very small grid to demonstrate the technologies and methodologies. I read lots of articles, tutorials, and used various tools to setup and monitor what was going on. By no means have I gone out and saturated a whole office with traffic and nor have I had access to a regular staff members PC to see how host performance was affected.

My demonstration system was very humble indeed. I used my regular desktop set up as a job control server. On this I had installed mySQL server installed set up as a master in replication, PHP,  and SVN linked through apache (for access via worker VM).

I then created a centOS worker machine on VirtualBox on a 6 year old windows XP laptop. I setup scheduled tasks as specified after copying the VM onto the machine and let it go.

The virtual machine was set up with PHP, subversion, and mySQL. I checked out a branch named ‘worker’ from my job control servers repository and made sure it could be updated using ‘svn update’. Next I setup mySQL as a slave and checked that data was replicating from mySQL on the job control server down to the worker VM. After all this I setup the bash script and the cron job.

My processing script basically went along the lines of this (very simple stuff):

  • Read in the name field
  • Counted the number of similar names in a table from the data source held on the VM
  • Counted the number of names as above but splitting the name by spaces (i.e. forename, middle, surname)
  • Repeated this process 1,000 times

Each job took approximately 20 minutes to run. At one point I opened several copies of the worker VM on the windows laptop and watched the jobs be checked off by each of the worker IP addresses. At this point I also confirmed that replication automatically restarted.

Leaving the laptop to idle resulted in a worker starting to process jobs from the job control server. When resuming laptop usage there was a delay of about 30-60 seconds, this is a fair amount of time and staff would need to be made aware that their machine may pause for a short while when returning to the machine. Newer machines may not have a pause of this long. The benefit of the amount of processing performed by these machines during idle periods would more that outweigh staff members having to wait a short period (say 1 minute) on arriving at their machines of a morning (I frequently wait longer that this for a Windows Defender update to take place) provided they were made aware of this (useful time to grab a morning coffee!).

Overall I feel confident that I have demonstrated the technologies that could be used to create such a system. I have shown that such a system does work on a (very) small scale and with some more experimenting could be scaled up utilise the resources of an office’s machines. If I don’t get to the point of doing this I would be very interested to know/see when someone else does.

Conclusions / Evaluation

The next obvious step would be to actually get a real world example and start to deploy a system such as this within an office environment and see what happens. Asking a business to commit to this without a trail blazing company to prove the technology and effectiveness may be a little difficult. Grid/Distributed computing is very popular is some circles and has some large applications (BIONC, SETI@Home, Folding@Home, etc). I did not, however, find a smaller scale and simple system like this in my searches that could be rolled out within an office environment.

I created a basically free system using mostly open source software and tools available in almost any office. The technologies were basically demonstrated and show to perform and work as expected. Hopefully I have show that with not much work and with a very simple setup you can deploy an office grid computing system that is powerful, cheap,  and scalable all at the same time.

Once a system is up and running there is almost no end to the amount of customisation and improvements you can make. For example statistics / benchmarking can easily be added showing the worth of such a system every day. New machines can be added quickly and easily as and when they arrive with upgrades to existing hardware bolstering your processing power.

I hope you’ve enjoyed reading this series of articles and its given you food for thought on running an office grid system. The solution presented here won’t necessarily work in all situations but should be adaptable to allow you to get your data processing done using your own solution.

Please feel free to send me any comments, corrections, or improvements and I’ll do my best to keep this article updated to match.

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