Update associated field in Waterline/Sails without affecting other fields - sails.js

I notice that multiple requests to a record causes writes to be possibly overwritten. I am using Mongo btw.
I have a schema like:
Trip { id, status, tagged_friends }
where tagged_friends is an association to Users collection
When I make 2 calls to update trips in close succession (in this case I am making 2 API calls from client - actually automated tests), its possible for them to interfere. Since they all call trip.save().
Update 1: update the tagged_friends association
Update 2: update the status field
So I am thinking these 2 updates should only save the "dirty" fields. I think I can do that with Trips.update() rather than trip.save()? But problem is I cannot use update to update an association? That does not appear to work?
Or perhaps there's a better way to do this?

Related

Why Spring Data doesn't support returning entity for modifying queries?

When implementing a system which creates tasks that need to be resolved by some workers, my idea would be to create a table which would have some task definition along with a status, e.g. for document review we'd have something like reviewId, documentId, reviewerId, reviewTime.
When documents are uploaded to the system we'd just store the documentId along with a generated reviewId and leave the reviewerId and reviewTime empty. When next reviewer comes along and starts the review we'd just set his id and current time to mark the job as "in progress" (I deliberately skip the case where the reviewer takes a long time, or dies during the review).
When implementing such a use case in e.g. PostgreSQL we could use the UPDATE review SET reviewerId = :reviewerId, reviewTime: reviewTime WHERE reviewId = (SELECT reviewId from review WHERE reviewId is null AND reviewTime is null FOR UPDATE SKIP LOCKED LIMIT 1) RETURNING reviewId, documentId, reviewerId, reviewTime (so basically update the first non-taken row, using SKIP LOCKED to skip any already in-processing rows).
But when moving from native solution to JDBC and beyond, I'm having troubles implementing this:
Spring Data JPA and Spring Data JDBC don't allow the #Modifying query to return anything else than void/boolean/int and force us to perform 2 queries in a single transaction - one for the first pending row, and second one with the update
one alternative would be to use a stored procedure but I really hate the idea of storing such logic so away from the code
other alternative would be to use a persistent queue and skip the database all along but this introduced additional infrastructure components that need to be maintained and learned. Any suggestions are welcome though.
Am I missing something? Is it possible to have it all or do we have to settle for multiple queries or stored procedures?
Why Spring Data doesn't support returning entity for modifying queries?
Because it seems like a rather special thing to do and Spring Data JDBC tries to focus on the essential stuff.
Is it possible to have it all or do we have to settle for multiple queries or stored procedures?
It is certainly possible to do this.
You can implement a custom method using an injected JdbcTemplate.

The correct HTTP method for resetting data

I want to "reset" certain data in my database tables using a RESTful method but I'm not sure which one I should be using. UPDATE because I'm deleting records and updating the record where the ID is referenced (but never removing the record where ID lives itself), or DELETE because my main action is to delete associated records and updating is tracking those changes?
I suppose this action can be ran multiple times but the result will be the same, however the ID will always be found when "resetting".
I think you want the DELETE method

Tracking who done what; mongo Atomicity when deleting by filter

I've been implementing an auditing system for mongo that tracks call and user information for each mongo transaction.
IE user bill
made a call to x endpoint
at y time
and changed z field from foo to bar
inserts and updates are easy because I tie a stored call info object to any objects updated in that call. (through a set property or updating the property directly on a replace or upsert call.)
all that works great.
Deletes are a hairy beast though.
when I delete by id I can easily track that information. BUT when I delete by filter
IE delete from users where username like bill.
mongo doesn't return the deleted ids back in the response. if I query to get those objects before I delete them who knows what could happen between the time I get those objects and when I actually delete them.
(Knock Knock, race condition. who's there?)
any ideas on how to keep the atomicity of that delete and have a reliable way to tie that delete call to the delete transaction?

Updating entities in ndb while paging with cursors

To make things short, I have to make a script in Second Life communicating with an AppEngine app updating records in an ndb database. Records extracted from the database are sent as a batch (a page) to the LSL script, which updates customers, then asks the web app to mark these customers as updated in the database.
To create the batch I use a query on a (integer) property update_ver==0 and use fetch_page() to produce a cursor to the next batch. This cursor is also sent as urlsafe()-encoded parameter to the LSL script.
To mark the customer as updated, the update_ver is set to some other value like 2, and the entity is updated via put_async(). Then the LSL script fetches the next batch thanks to the cursor sent earlier.
My rather simple question is: in the web app, since the query property update_ver no longer satisfies the filter, is my cursor still valid ? Or do I have to use another strategy ?
Stripping out irrelevant parts (including authentication), my code currently looks like this (Customer is the entity in my database).
class GetCustomers(webapp2.RequestHandler): # handler that sends batches to the update script in SL
def get(self):
cursor=self.request.get("next",default_value=None)
query=Customer.query(Customer.update_ver==0,ancestor=customerset_key(),projection=[Customer.customer_name,Customer.customer_key]).order(Customer._key)
if cursor:
results,cursor,more=query.fetch_page(batchsize,start_cursor=ndb.Cursor(urlsafe=cursor))
else:
results,cursor,more=query.fetch_page(batchsize)
if more:
self.response.write("more=1\n")
self.response.write("next={}\n".format(cursor.urlsafe()))
else:
self.response.write("more=0\n")
self.response.write("n={}\n".format(len(results)))
for c in results:
self.response.write("c={},{},{}\n".format(c.customer_key,c.customer_name,c.key.urlsafe()))
self.response.set_status(200)
The handler that updates Customer entities in the database is the following. The c= parameters are urlsafe()-encoded entity keys of the records to update and the nv= parameter is the new version number for their update_ver property.
class UpdateCustomer(webapp2.RequestHandler):
#ndb.toplevel # don't exit until all async operations are finished
def post(self):
updatever=self.request.get("nv")
customers=self.request.get_all("c")
for ckey in customers:
cust=ndb.Key(urlsafe=ckey).get()
cust.update_ver=nv # filter in the query used to produce the cursor was using this property!
cust.update_date=datetime.datetime.utcnow()
cust.put_async()
else:
self.response.set_status(403)
Will this work as expected ? Thanks for any help !
Your strategy will work and that's the whole point for using these cursors, because they are efficient and you can get the next batch as it was intended regardless of what happened with the previous one.
On a side note you could also optimise your UpdateCustomer and instead of retrieving/saving one by one you can do things in batches using for example the ndb.put_multi_async.

How to get list of aggregates using JOliviers's CommonDomain and EventStore?

The repository in the CommonDomain only exposes the "GetById()". So what to do if my Handler needs a list of Customers for example?
On face value of your question, if you needed to perform operations on multiple aggregates, you would just provide the ID's of each aggregate in your command (which the client would obtain from the query side), then you get each aggregate from the repository.
However, looking at one of your comments in response to another answer I see what you are actually referring to is set based validation.
This very question has raised quite a lot debate about how to do this, and Greg Young has written an blog post on it.
The classic question is 'how do I check that the username hasn't already been used when processing my 'CreateUserCommand'. I believe the suggested approach is to assume that the client has already done this check by asking the query side before issuing the command. When the user aggregate is created the UserCreatedEvent will be raised and handled by the query side. Here, the insert query will fail (either because of a check or unique constraint in the DB), and a compensating command would be issued, which would delete the newly created aggregate and perhaps email the user telling them the username is already taken.
The main point is, you assume that the client has done the check. I know this is approach is difficult to grasp at first - but it's the nature of eventual consistency.
Also you might want to read this other question which is similar, and contains some wise words from Udi Dahan.
In the classic event sourcing model, queries like get all customers would be carried out by a separate query handler which listens to all events in the domain and builds a query model to satisfy the relevant questions.
If you need to query customers by last name, for instance, you could listen to all customer created and customer name change events and just update one table of last-name to customer-id pairs. You could hold other information relevant to the UI that is showing the data, or you could simply hold IDs and go to the repository for the relevant customers in order to work further with them.
You don't need list of customers in your handler. Each aggregate MUST be processed in its own transaction. If you want to show this list to user - just build appropriate view.
Your command needs to contain the id of the aggregate root it should operate on.
This id will be looked up by the client sending the command using a view in your readmodel. This view will be populated with data from the events that your AR emits.