4 ms·

By finding the natural sharding factor. If you have one, which very often you do. Three completely different examples: - Are you running a mail server? Every u

by biokoda 11y ago

By finding the natural sharding factor. If you have one, which very often you do. Three completely different examples: - Are you running a mail server? Every user is an actor (i.e. an sqlite instance). - Are you running a backend for a dropbox/evernote/messaging type app? Every user is an actor. - Do you have a distributed filesystem? Use the KV mode and shard on file hash. - Do you need scalable counters? Use KV mode again, split every counter into 10 (or 100) and increment/decrement on those.

catnaroek 11y ago
Again, please excuse my ignorance - what is the definition of “natural sharding factor”, and how would I compute it for, say, an ERP system?
- biokoda 11y ago
  I have no experience in developing in ERP systems. I do have experience on being at the end of a very poorly working one. These systems seem (from my outside view) to have a tendency to become giant monoliths. So when developing you must fight against increasing monolithic complexity. Using something like ActorDB can be somewhat of a beneficial constraint. It forces you to maintain a clean design. I would force sales, marketing, shipping, product planning (taking from wikipedia here..), to be their own separate actors with their own schemas. Then if possible shard within those types. So if something is customer service, have an actor per customer and have all his data there. If you're developing multiple products, every product has an actor.
  - catnaroek 11y ago
    > These systems seem (from my outside view) to have a tendency to become giant monoliths. So when developing you must fight against increasing monolithic complexity. You aren't wrong, that's my experience as well. It's just as annoying for programmers (or, at least, for me) as it is for users. The following question has popped out countless times in my head: “Why do I have to rely on an implicit convention that this application module never touches this database table?” There was never a good answer. The only reason why I put up with such things is that I have no idea how to prevent more modular designs from turning into a data integrity nightmare. (I'll freely admit my lack of education is to blame here.) For instance, let's say we have three modules: inventory, sales and shipping. Furthermore, let's assume each module is its own actor and uses its own backend database. We must implement the use case “enter a sale in the system”: (0) The sales module queries the inventory module whether there is enough of a product in stock to satisfy a customer order. The expected sequence of actions is: (1) The inventory module “locks” the requested quantity/amount of the product [so that it can't be used, say, for another sale], and gives the sales module a “token” that can be used to confirm or cancel the withdrawal. (2) The sales module queries the shipping module if there are enough available trucks/ships/whatever to ship the product to the customer's location by a given delivery date. (3) The shipping module “locks” however many trucks/ships/whatever it deems necessary to ship the product, and gives the sales modules a “token” that can be used to confirm or cancel the shipping. (4) The sales module queries the user for the customer's credit card number and verification code, interfaces with the bank's system, blablabla... (5) The sales module confirms to the inventory and shipping modules [in this specific order] that the product will be withdrawn and shipped. Now some exception handling: (6) If step 3 fails, the sales module cancels the product withdrawal. (7) If step 4 fails, the sales module cancels the product withdrawal and shipping. (8) If any system [inventory, sales, shipping] goes down, neither the product nor the trucks/ships/whatever can be kept locked forever. So each lock must have a timeout, and, if it's neither explicitly confirmed nor explicitly cancelled by the sales module, it will be implicitly cancelled by the inventory and/or shipping module when the timeout elapses. (9) It may happen [unlikely, but not impossible], that the inventory and shipping module's clocks get unsynchronized in such a way that, when the product withdrawal has been been confirmed, the shipping lock has already elapsed. Oh, the nightmare. Implementing all of this correctly in all cases is actually tricky! And if anything is implemented slightly wrong, the whole system goes kaboom! With a monolithic database, there is no need to “lock” any resources, nor issue “confirmation tokens” - just use the DBMS's built-in transaction system!
    - biokoda 11y ago
      > Furthermore, let's assume each module is its own actor and uses its own backend database. I would have every module an actor type. There can be multiple types each type has its own schema. Within an actor type many actors. An actor for every product for instance. So all X widgets are in one actor. > With a monolithic database, there is no need to “lock” any resources, nor issue “confirmation tokens” - just use the DBMS's built-in transaction system! ActorDB has distributed ACID transactions so I would use that. You can create a transaction over multiple actors. The reason I would split it into many actors is that you're always locking small parts of the system for the duration of the transaction not the entire DB.
      - catnaroek 11y ago
        > I would have every module an actor type. There can be multiple types each type has its own schema. Within an actor type many actors. Noted. > ActorDB has distributed ACID transactions so I would use that. You can create a transaction over multiple actors. Sweet! In particular, the second sentence is exactly what I wanted to hear. I will give ActorDB a try.

by biokoda 11y ago

catnaroek 11y ago

Again, please excuse my ignorance - what is the definition of “natural sharding factor”, and how would I compute it for, say, an ERP system?

biokoda 11y ago
I have no experience in developing in ERP systems. I do have experience on being at the end of a very poorly working one. These systems seem (from my outside view) to have a tendency to become giant monoliths. So when developing you must fight against increasing monolithic complexity. Using something like ActorDB can be somewhat of a beneficial constraint. It forces you to maintain a clean design. I would force sales, marketing, shipping, product planning (taking from wikipedia here..), to be their own separate actors with their own schemas. Then if possible shard within those types. So if something is customer service, have an actor per customer and have all his data there. If you're developing multiple products, every product has an actor.
- catnaroek 11y ago
  > These systems seem (from my outside view) to have a tendency to become giant monoliths. So when developing you must fight against increasing monolithic complexity. You aren't wrong, that's my experience as well. It's just as annoying for programmers (or, at least, for me) as it is for users. The following question has popped out countless times in my head: “Why do I have to rely on an implicit convention that this application module never touches this database table?” There was never a good answer. The only reason why I put up with such things is that I have no idea how to prevent more modular designs from turning into a data integrity nightmare. (I'll freely admit my lack of education is to blame here.) For instance, let's say we have three modules: inventory, sales and shipping. Furthermore, let's assume each module is its own actor and uses its own backend database. We must implement the use case “enter a sale in the system”: (0) The sales module queries the inventory module whether there is enough of a product in stock to satisfy a customer order. The expected sequence of actions is: (1) The inventory module “locks” the requested quantity/amount of the product [so that it can't be used, say, for another sale], and gives the sales module a “token” that can be used to confirm or cancel the withdrawal. (2) The sales module queries the shipping module if there are enough available trucks/ships/whatever to ship the product to the customer's location by a given delivery date. (3) The shipping module “locks” however many trucks/ships/whatever it deems necessary to ship the product, and gives the sales modules a “token” that can be used to confirm or cancel the shipping. (4) The sales module queries the user for the customer's credit card number and verification code, interfaces with the bank's system, blablabla... (5) The sales module confirms to the inventory and shipping modules [in this specific order] that the product will be withdrawn and shipped. Now some exception handling: (6) If step 3 fails, the sales module cancels the product withdrawal. (7) If step 4 fails, the sales module cancels the product withdrawal and shipping. (8) If any system [inventory, sales, shipping] goes down, neither the product nor the trucks/ships/whatever can be kept locked forever. So each lock must have a timeout, and, if it's neither explicitly confirmed nor explicitly cancelled by the sales module, it will be implicitly cancelled by the inventory and/or shipping module when the timeout elapses. (9) It may happen [unlikely, but not impossible], that the inventory and shipping module's clocks get unsynchronized in such a way that, when the product withdrawal has been been confirmed, the shipping lock has already elapsed. Oh, the nightmare. Implementing all of this correctly in all cases is actually tricky! And if anything is implemented slightly wrong, the whole system goes kaboom! With a monolithic database, there is no need to “lock” any resources, nor issue “confirmation tokens” - just use the DBMS's built-in transaction system!
  - biokoda 11y ago
    > Furthermore, let's assume each module is its own actor and uses its own backend database. I would have every module an actor type. There can be multiple types each type has its own schema. Within an actor type many actors. An actor for every product for instance. So all X widgets are in one actor. > With a monolithic database, there is no need to “lock” any resources, nor issue “confirmation tokens” - just use the DBMS's built-in transaction system! ActorDB has distributed ACID transactions so I would use that. You can create a transaction over multiple actors. The reason I would split it into many actors is that you're always locking small parts of the system for the duration of the transaction not the entire DB.
    - catnaroek 11y ago
      > I would have every module an actor type. There can be multiple types each type has its own schema. Within an actor type many actors. Noted. > ActorDB has distributed ACID transactions so I would use that. You can create a transaction over multiple actors. Sweet! In particular, the second sentence is exactly what I wanted to hear. I will give ActorDB a try.