I've built a REST API with a pretty decent latency. Each request is answered in ~100 ms with a thousand requests per second. This is however with a relatively low physical distance to the data center. The users of this API would, however, be spread all over the globe. From the US for example (to a data center in Germany), the response time for a single request is ~400 ms under no load.
What would be the best approach to deploying this API? I suspect multiple servers at different locations, with a load balancer in front. How would I ensure that the MySQL database would stay in sync between the servers in that case?
With multiple servers and a load balancer, the costs rise exponentially, which is something I can hopefully afford in the future, but not at the moment.
I'd love to hear your ideas!
Afaik. for big projects people use event sourcing with an event storage and microservices and message queues between them or a basic solution is polling the event storage through a simple REST API something like send me the latest events since the last event I received. If you can accept eventual consistency, then I think this approach can work pretty well. It makes writing somewhat slower, but reading can be very fast with it. No need to sync the MySQL databases directly, you just pull the latest events and use a projection to update the local MySQL database. So the event storage is the single source of truth.
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I am trying to do something new, something I have never done before. I am looking for advice or point me into right direction how to choose technology. I am trying to build race simulation app that will have thousands of iot devices streaming data into central platform. While I understand that I can use some sort of IOT hub with cloud providers, but what technology do I choose for storing data?
Example is online indoor biking app. There are apps where you can connect your indoor bike online and have simulated race. For my project I am trying to build something similar. Do I use NO SQL db in this scenario? What technology will allow better scale of application like this since it could be millions of devices around the world in "simulated" race. I am not worried about front-end and things like that, but backend, IOT hub, storing data, presenting-real time?
At this point it is important to understand what kind of data your IoT devices will stream, and at what kind of a rate. It will have significant impact on your question.
That it is if it's just location information and some other small data sent lets say once a second, then if you're talking about tens of thousands of devices - this is not a big load of information, and any standard database, like MySQL will be able to deal with it. You will of course need a multi-threaded server(s) capable of handling many requests in parallel.
If your IoT devices will stream HD video, then you're looking at a completely different solution, with a much stronger server, capable of handling allot of streams in parallel, with significant bandwidth requirements from your hosting company, as well as storage space for all the videos. In this case you will store the streams as files (if you'll need them later on), and you won't need any special database either.
In any case, once you'll reach millions of users, you'll be able to scale most modern databases and servers, like MySQL replication capability. For example, take a look how Wikipedia is relying on MySQL: wikipedia - MySQL https://www.mysql.com/why-mysql/case-studies/mysql-cs-wikipedia.html
So I wouldn't be worried regarding the database on this stage, but make sure that the design of my system is in accordance to the the type of data and rate it is streamed.
Hope this gives you a pointer.
I'm developing an app that allows to track a mobile device instantly (live) ... I need an of advice. The application must send the location to a webservice that in it's turn records the received data in a database.
What would be, in your opinion, the best way to store the location values?
I'm new in using bigdata and I'm afraid that simple sql requests wont be able to do the work properly ... I imagine if there is lot of users and each user send a request each 1sec I'll have issue with the database ...
An advice ? Thank you very much
i think you could have a look into the geospatial queries in mongo, if you chose to go ahead with mongodb.
Refer here
And here
for the design of the database would depend on the nature of the query (essentially the read and write).
Worth having a look into
Working at Cintric we landed on using elasticsearch. We process billions of location points in real time and provide advanced analytics to our users.
We started with mongoDB and ran into a lot of troubles, eventually leading to a painful migration.
Our stack currently has mobile devices dump location updates into AWS Kinesis, which are then processed by AWS Lambda handlers, and then dumped into elasticsearch. We're able to serve, process and store 300 million requests/month for only a few hundred dollars/month. Analytics for our dashboard add additional cost but for your needs I would highly recommend checking out your options on AWS.
I was assigned to update existing system of gathering data coming from points of sale and inserting it into central database. The one that is working now is based on FTP/SFTP transmission, where the information is sent once a day, usually at night. Unfortunately, because of unstable connection links (low quality 2G/3G modems), some of the files appear to be broken. With just a few shops connected that way everything was working smooth, but along with increasing number of shops, errors became more often. What is worse, the time needed to insert data into central database is taking up to 12 - 14h (including waiting for the data to be downloaded from all of the shops) and that cannot happen during the working day as it would block the process of creating sale reports and other activities with the database - so we are really tight with processing time here.
The idea my manager suggested is to send the data continuously, during the day. Data packages would be significantly smaller, so their transmission and insertion would be much faster, central server would contain actual (almost real time) data and night could be used for long running database activities like creating backups, rebuilding indexes etc.
After going through many websites, I found that:
using ASMX web service is now obsolete and WCF should be used instead
WCF with MSMQ or System Messaging could be used to safely transmit data, where I don't have to care that much about acknowledging delivery of data, consistency, nodes going offline etc.
according to http://blogs.msdn.com/b/motleyqueue/archive/2007/09/22/system-messaging-versus-wcf-queuing.aspx WCF queuing is better
there are also other technologies for implementing message queue, like RabbitMQ, ZeroMQ etc.
And that is where I become confused. With so many options, do you have any pros and cons of these technologies?
We were using .NET with Windows Forms and SQL Server, but if it would be necessary, we could change to something more suitable. I am also a bit afraid of server efficiency. After some calculations, server would be receiving about 15 packages of data per second (peak). Is it much? I know there are many websites without serious server infrastructure, that handle hundreds of visitors online and still run smooth, but the website mainly uploads data to the client, and here we would download it from the client.
I also found somewhat similar SO question: Middleware to build data-gathering and monitoring for a distributed system
where DDS was mentioned. What do you think about introducing some middleware servers that would cope with low quality links to points of sale, so the main server would not be clogged with 1KB/s transmission?
I'd be grateful with all your help. Thank you in advance!
Rabbitmq can easily cope with thousands of 1kb messages per second.
As your use case is not about processing real time data, I'd say you should combine few messages and send them as a batch. That would be good enough in order to spread load over the day.
As the motivation here is not to process the data in real time, then any transport layer would do the job. Even ftp/sftp. As rabbitmq will work fine here, it's not the typical use case for it.
As you mentioned that one of your concerns is slow/unreliable network, I'd suggest to compress the files before sending them, and on the receiving end, immediately verify their integrity. Rsync or similar will probably do great job in doing that.
From what I understand, you have basically two problems:
Potential for loss/corruption of call data
Database write performance
The potential for loss/corruption of call data is being caused by a lack of reliability in the transmission of data from client to service.
And it's not clear what is causing the database contention/performance issues, beyond a vague reference to high volumes, so this answer will be more geared towards solving the first problem.
You have correctly identified the need for reliable asynchronous communication transport as a way to address the reliability issues in your current setup.
Looking at MSMQ to deliver this is a valid first step. MSMQ provides reliable communication via a store and forward messaging semantic which comes out of the box and requires very little in the way of configuration.
Unfortunately, while suitable for your needs, MSMQ relies on 2 things:
A reliable network protocol, and
A client service running on both sending and receiving machine.
From your description above, I don't believe 1 exists (the internet is not a reliable network), and you might well struggle with 2 - MSMQ only ships with Windows Server or business/enterprise versions of Windows on the desktop.(*see below...)
As a possible solution to the network reliability problem, you could use a WCF or a RESTful endpoint (using Nancy or WebApi) to expose a service operation(s) exposed over HTTP, which would accept the incoming calls from the client machines. These technologies are quite different, so you'll need to make sure you're making the correct choice early on.
WCF supports WS-ReliableMessaging from the SOAP 1.2 specification out of the box, which allows for reliable web service calls over http, however it's very config-heavy and not generally a nice framework to work with.
REST much simpler than WCF in .Net, is very lightweight and easy to use. However, for reliable delivery you would have to expose some kind of GET operation (in addition to a POST to allow the client to send data) to be called (within a reasonable time-frame) to verify the data was committed. The client would have to implement some kind of retry semantic if the result of the GET "acknowledgement" was negative.
Despite requiring two operations rather than one for the WCF route, I would favour the REST approach. I've done plenty of both and find REST services way nicer to work with.
(*) That's not to say that MSMQ wouldn't work in your ultimate solution, just that it would not be used to address the transmission reliability issue. However it could still be used to address another of your problems, that of database write contention. If you were to queue incoming requests once they came into the server, then these could be processed by an "offline" process, which could then perform the required database operations in a reliable manner. This could be done by using MSMQ transactional queues.
In response to comments:
99% messages are passed from shop to main server, but if some change
is needed (price correction, discounts etc.), that data has to be sent
to shop.
This kind of changes things. Had I understood from the beginning that you had a bidirectional requirement, and seeing as how you have managed to establish msmq communication, I would have nudged you towards NServiceBus, which is a really, really cool wrapper around MSMQ. The reason I would have done this is that you appear to have both a one way, and a publish-subscribe requirement, which is supported really nicely by NServiceBus.
I am writing software that creates a large graph database. The software needs to access dozens of different REST APIs with millions of total requests. The data will then be processed by the Hadoop cluster. Each of these APIs have rate limits that vary by requests/second, per window, per day and per user (typically via OAuth).
Does anyone have any suggestions on how I might use either a Map function or other Hadoop-ecosystem tool to manage these queries? The goal would to be to leverage the parallel processing in Hadoop.
Because of the varied rate limits, it often makes sense to switch to a different API query while waiting for the first limit to reset. An example would be one API call that creates nodes in the graph and another that enriches the data for that node. I could have the system go out and enrich the data for the new nodes while waiting for the first API limit to reset.
I have tried using SQS queuing on EC2 to manage the various API limits and states (creating a queue for each API call), but have found it to be ridiculously slow.
Any ideas?
It looks like the best option for my scenario will be using Storm, or specifically the Trident abstraction. It gives me the greatest flexibility for both workload management but process management as well
I am building out a solution that will be deployed in multiple data centers in multiple regions around the world, with each data center having a replicated copy of data actively updated in each region. I will have a combination of multiple databases and file systems in each data center, the state of which must be kept consistent (within a data center). These multiple repositories will be fronted by a SOA service tier.
I can tolerate some latency in the replication, and need to allow for regions to be off-line, and then catch up later.
Given the multiple back end repositories of data, I can't easily rely on independent replication solutions for each one to maintain a consistent state. I am thus lead to implementing replication at the application layer -- by replicating the SOA requests in some manner. I'll need to make sure that replication loops don't occur, and that last writer conditions are sorted out correctly.
In your experience, what is the best pattern for solving this problem, and are there good products (free or otherwise) that should be investigated?
Lotus/ Domino is your answer. I've been working with it for ten years and its exactly what you need. It may not be trendy (a perception that I would challenge) but its powerful, adaptable and very secure, The latest version R8 is the best yet.
You should definitely consider IBM Lotus Domino. A Lotus Notes database can replicate between sites on a predefined schedule. The replicate in Notes/Domino is definitely a very powerful feature and enables for full replication of data between sites. Even if a server is unavailable the next time it connects it will simply replicate and get back in sync.
As far as SOA Service tier you could then use Domino Designer to write a webservice. Since Notes/Domino 7.5.x (I believe) Domino has been able to provision and consume webservices.
AS what other advised, I will recommend also Lotus Notes/Domino. 8.5 is really very powerful application development platfrom
You dont give enough specifics to be certain of your needs but I think you should check out SQL Server Merge replication. It allows for asynchronous replication of multiple databases with full conflict resolution. You will need to designate a Global master and all the other databases will replicate to that one, but all the database instances are fully functional (read/write) and so you can schedule replication at whatever intervals suit you. If any region goes offline they can catch up later with no issues - if the master goes offline everyone will work independantly until replication can resume.
I would be interested to know of other solutions this flexible (apart from Lotus Notes/Domino of course which is not very trendy these days).
I think that your answer is going to have to be based on a pub/sub architecture. I am assuming that you have reliable messaging between your data centers so that you can rely on published updates being received eventually. If all of your access to the data repositories is via service you can add an event notification to the orchestration of each of your update services that notifies all interested data centers of the event. Ideally the master database is the only one that sends out these updates. If the master database is the only one sending the updates you can exclude routing the notifications to the node that generated them in the first place thus avoiding update loops.