for an endpoint that assigns jobs to employees, I would like the requests to the endpoint to be processed sequentially so that it is not possible for multiple employees to sign up for a job.
Is there a way to do this ? Or maybe even something better ? How does this work on shopping sites with carts ? These often also need to check first if the product is available and prevent two users from buying the last product.
Thanks a lot!
Related
If my users are stored in some other database, but I am building posts in my SQL database, should I create another table users?
If I did, I would be duplicating all of my users and would have to make sure this stays in sync with the other database, but on the other hand, my posts tables could save space by referring to fk instead of full id string each time.
What is the recommendation? Create another table users or just pass in the user ids to query?
If you have a service that stores and provides information about users then other services that need that information should communicate with the User service to get it. That is, presumably, the reason the User service exists in the first place.
Depending on the volatility of the users list and requirements for changes there to be respected in the Posts service you might consider some short-term caching in the Posts service, but I certainly wouldn't persist another copy of the user list there.
There are 3 obvious solutions.
The simplest, cleanest and fastest is to use foreign keys and joins between your "posts" database and your "users" database. In this case, when you show a list of posts, you can get both the post and user data in a single query, and there's no need to keep things up to date.
The next option is to store a copy of the user data alongside your posts. This leads to entertaining failure modes - data in the user database may get out of sync. However, this is a fairly common strategy when using 3rd party authentication systems (e.g. logging on with your Google/Facebook/Github/Stack Exchange credentials). The way to make this work is to minimize the amount of data you duplicate, and have it be safe if it's out of date. For instance, a user's display name is probably okay; current bank account balance is probably not.
The final option is to store the primary key for users in your posts database, and to retrieve the user data at run time. This is less likely to lead to bugs with data getting out of sync, but it can cause performance problems - retrieving user details for 1000 posts one by one is obviously much slower than retrieving everything through a joined query.
The choice then is "do I have a service which combines post and user data and my UI retrieves everything from that service, or do I let the UI retrieve posts, and then users for each post". That's mostly down to the application usage, and whether you can use asynchronous calls to retrieve user information. If at all possible (assuming you're building a web application), the simplest option might be to return the posts and user IDs and use Ajax requests to retrieve the user data as needed.
The CQRS approach (common to microservice architectures) provides some structure for this.
I am building real time achievements web service.
My current idea is to have an achievements collection in MongoDB as well as a player collection. I would store the list of achievements in the achievements collection (that list can be modified to add new achievements and would serve as the achievements definitions) and it would contains a list of stats and thresholds (goals to complete the achievement), while the player collection would have objects that are composed of the playerID as well as a dict of each achievements as keys and many stats (progress) as values, as well as informations (completed or not).
When a client would post new stats, I would get the list of achievements and find those that use those stats in their progression by fetching the achievements collection. Then I would need to fetch the players collection to find which achievements are already completed and remove those from my current list of achievements to process. Then I would fetch the players collection again to get the other stats and compute the new progress. I would need to update the progress of the achievement on the players collection. If an achievement is complete, I would send a callback to the client, so it can see it "live".
My problem is that I need the service to work under high pressure (hundreds of thousands of players sending new stats a lot (like number of kills, maybe thousands of stats with thousands of achievements)) and my current idea seems to do WAY TOO MANY CALLS to the database.
I thought of changing to an MySQL database instead but I am not very good with them, so I am not sure if things would be better that way (could views speed things up?). Redis seems to be too costly for a big database.
Is there a better flow / Design pattern I should use instead?
Is there a way to make schemas so it will still be quick on heavy load?
Should I use MySQL instead? And if yes, what is the key element that would help me speed up things? (So I can read on it and design something better)
I never used NoSQL but used SQL a lot. So my thought may be biased or too much SQL centric.
Having said that, here is my idea. Overall, I think two db call is needed per new stat.
When a client would post new stats, I would get the list of achievements and find those that use those stats in their progression by fetching the achievements collection.
If the achievements collection is small enough, you could cache into the memory when your service is initialized.
If not, I think you should go "MySQL" approach and not do this step alone but join to the next step. In conclusion, we could reduce one trip to DB
Then I would need to fetch the players collection to find which achievements are already completed
This could be the first trip to DB
remove those from my current list of achievements to process
I believe this is not DB related but logic inside your program. But please correct me if I am wrong.
Then I would fetch the players collection again to get the other stats and compute the new progress.
I think you could get this information from your first DB trip and save somewhere in the memory. So no further DB trip is needed
I would need to update the progress of the achievement on the players collection.
This will be your second DB trip to update.
If an achievement is complete, I would send a callback to the client, so it can see it "live".
And this is not related with DB
If this is still too much DB call and you would like to make this only one trip, my only idea is to switch MySQL and create a procedure that deal with the logic.
In this way, you will make only one DB contact per stat, which is inevitable and push all your load to DB layer so that it scales over there.
I am running my chat service on ejabberd, but after 4-5 months of no downtime, I have come to use case where it's taking a lot of time in fetching rosters for the users whose roster list is too big. At many places it's mentioned that pagination functionality is not present on ejabberd, but is there any way we can optimise it ?
To my knowledge, there is no XMPP specification that define roster pagination. ejabberd does not do anything special in that regard.
What you can look into is XMPP roster versioning (https://xmpp.org/extensions/xep-0237.html), but this is different from pagination.
I need to architect a database and service, I have resource that I need to deliver to the users. And the delivery takes some time or requires user to do some more job.
These are the tables I store information into.
Table - Description
_______________________
R - to store resources
RESERVE - to reserve requested resources
HACK - to track some requests that couldn`t be made with my client application (statistics)
FAIL - to track requests that can`t be resolved, but the user isn't guilty (statistics)
SUCCESS - to track successfully delivery (statistics)
The first step when a user requests resouce
IF (condition1 is true - user have the right to request resource) THEN
IF (i've successfully RESERVE-d resource and commited the transaction) THEN
nothing to do more
ELSE
save request into FAIL
ELSE
save request into HACK
Then the second step
IF (condition2 is true - user done his job and requests the reserved resource) THEN
IF (the resource delivered successfully) THEN
save request into SUCCESS
ELSE
save request into FAIL
depending on application logic move resource from RESERVE to R or not
ELSE
save request into HACK, contact to the user,
if this is really a hacker move resource from RESERVE to R
This is how I think to implement the system. I've stored transactions into the procedures. But the main application logic, where I decide which procedure to call are done in the application/service layer.
Am I on a right way, is such code division between the db and the service layers normal? Your experienced opinions are very important.
Clarifying and answering to RecentCoin's questions.
The difference between the HACK and FAIL tables are that I store more information in the HACK table, like user IP and XFF. I`m not going to penalize each user that appeared in that table. There can be 2 reasons that a user(request) is tracked as a hack. The first is that I have a bug (mainly in the client app) and this will help me to fix them. The second is that someone does manually requests, and tries to bypass the rules. If he tries 'harder' I'll be able to take some precautions.
The separation of the reserve and the success tables has these reasons.
2.1. I use reserve table in some transactions and queries without using the success table, so I can lock them separately.
2.2. The data stored in success will not slow down my queries, wile I'm querying the reserve table.
2.3. The success table is kind of a log for statistics, that I can delete or move to other database for future analyse.
2.4. I delete the rows from the reserve after I move them to the success table. So I can evaluate approximately the max rows count in that table, because I have max limit for reservations for each user.
The points 2.3 and 2.4 could be achieved too by keeping in one table.
So are the reasons 2.1 and 2.2 enough good to keep the data separately?
The resource "delivered successfully" mean that the admin and the service are done everything they could do successfully, if they couldn't then the reservation fails
4 and 6. The restrictions and right are simple, they are like city and country restrictions, The users are 'flat', don't have any roles or hierarchy.
I have some tables to store users and their information. I don't have LDAP or AD.
You're going in the right direction, but there are some other things that need to be more clearly thought out.
You're going to have to define what constitutes a "hack" vs a "fail". Especially with new systems, users get confused and it's pretty easy for them to make honest mistakes. This seems like something you want to penalize them for in some fashion so I'd be extremely careful with this.
You will want to consider having "reserve" and "success" be equivalent. Why store the same record twice? You should have a really compelling reason do that.
You will need to define "delivered successfully" since that could be anything from an entry in a calendar to getting more pens and post notes.
You will want to define your resources as well as which user(s) have rights to them. For example, you may have a conference room that only managers are allowed to book, but you might want to include the managers' administrative assistants in that list since they would be booking the room for the manager(s).
Do you have a database of users? LDAP or Active Directory or will you need to create all of that yourself? If you do have LDAP or AD, can use something like SAML?
6.You are going to want to consider how you want to assign those rights. Will they be group based where group membership confers the rights to reserve, request, or use a given thing? For example, you may only want architects printing to the large format printer.
I'm working on a SNS like mobile app project, where users upload their contents and can see updates of their subscribed topic or friends on their homepage.
I store user contents in mysql, and query the user specific homepage data by simply querying out first who and what the user subscribed and then query the content table filtering out using the 'where userid IN (....) or topic IN (....)' clause.
I suspect this would become quite slow when the content table piles up or when a user subscribe tons of users or topics. Our newly released app is already starting to have thousands of new users each week, and getting more over time. Scalability must be a concern for us right now.
So I wonder how Facebook or Twitter handle this subscribing problem with their amazing number of users. Do they handle a list for each user? I tried to search, but all I got is how to interact with Facebook or Twitter rather than how they actually implement this feature.
I noticed that you see only updates rather than history in your feed when using Facebook. Which means that subscribing a new user won't dump lots out dated content into your feed as how it would be by using my current method.
How do Facebook design their database and how did they dispatch new contents to subscribed users?
My backend is currently PHP+MySQL, and I don't mind introducing other backend technologies such as Redis or JMS and stuff if that's the way it should be done.
Sounds like you guys are still in a pretty early stage. There are N-number of ways to solve this, all depending on which stage of DAUs you think you'll hit in the near term, how much money you have to spend on hardware, time in your hands to build it, etc.
You can try an interim table that queues up the newly introduced items, its meta-data on what it entails (which topic, friend user_id list, etc.). Then use a queue-consumer system like RabbitMQ/GearMan to manage the consumption of this growing list, and figure out who should process this. Build the queue-consumer program in Scala or a J2EE system like Maven/Tomcat, something that can persist. If you really wanna stick with PHP, build a PHP REST API that can live in php5-fpm's memory, and managed by the FastCGI process manager, and called via a proxy like nginx, initiated by curl calls at an appropriate interval from a cron executed script.
[EDIT] - It's probably better to not use a DB for a queueing system, use a cache server like Redis, it outperforms a DB in many ways and it can persist to disk (lookup RDB and AOF). It's not very fault tolerant in case the job fails all of a sudden, you might lose a job record. Most likely you won't care on these crash edge cases. Also lookup php-resque!
To prep for the SNS to go out efficiently, I'm assuming you're already de-normalizing the tables. I'd imagine a "user_topic" table with the topic mapped to users who subscribed to them. Create another table "notification_metadata" describing where users prefer receiving notifications (SMS/push/email/in-app notification), and the meta-data needed to push to those channels (mobile client approval keys for APNS/GCM, email addresses, user auth-tokens). Use JSON blobs for the two fields in notification_metadata, so each user will have a single row. This saves I/O hits on the DB.
Use user_id as your primary key for "notification_meta" and user_id + topic_id as PK for "user_topic". DO NOT add an auto-increment "id" field for either, it's pretty useless in this use case (takes up space, CPU, index memory, etc). If both fields are in the PK, queries on user_topic will be all from memory, and the only disk hit is on "notification_meta" during the JOIN.
So if a user subscribes to 2 topics, there'll be two entries in "user_topic", and each user will always have a single row in "notification_meta"
There are more ways to scale, like dynamically creating a new table for each new topic, sharding to different MySQL instances based on user_id, partitioning, etc. There's N-ways to scale, especially in MySQL. Good luck!