After lurking for a long time, I finally have a question I can't google my way out of.
I am working for an Oracle CRM On Demand implementation to use client side extensions to enhance some functionality for our Clients.
At the moment the most pressing issue is the fact that when I am pinging an object, let's say an Activity, I get some but not all of its attributes.
For example, '/OnDemand/....../Activity/1234-56789A' ends up returning the Id of the Activity and the two urls. There is so much more content though, that I need to find. I could spend the next day going through every single attribute, throwing it on the end of a '?fields=SomeThing,OrAnother' string, but that seems like massive over kill.
Is there any one who knows how to do this?
All my thanks,
Riye.
Related
I am trying to push a event towards GA3, mimicking an event done by a browser towards GA. From this Event I want to fill Custom Dimensions(visibile in the user explorer and relate them to a GA ID which has visited the website earlier). Could this be done without influencing website data too much? I want to enrich someone's data from an external source.
So far I cant seem to find the minimum fields which has to be in the event call for this to work. Ive got these so far:
v=1&
_v=j96d&
a=1620641575&
t=event&
_s=1&
sd=24-bit&
sr=2560x1440&
vp=510x1287&
je=0&_u=QACAAEAB~&
jid=&
gjid=&
_u=QACAAEAB~&
cid=GAID&
tid=UA-x&
_gid=GAID&
gtm=gtm&
z=355736517&
uip=1.2.3.4&
ea=x&
el=x&
ec=x&
ni=1&
cd1=GAID&
cd2=Companyx&
dl=https%3A%2F%2Fexample.nl%2F&
ul=nl-nl&
de=UTF-8&
dt=example&
cd3=CEO
So far the Custom dimension fields dont get overwritten with new values. Who knows which is missing or can share a list of neccesary fields and example values?
Ok, a few things:
CD value will be overwritten only if in GA this CD's scope is set to the user-level. Make sure it is.
You need to know the client id of the user. You can confirm that you're having the right CID by using the user explorer in GA interface unless you track it in a CD. It allows filtering by client id.
You want to make this hit non-interactional, otherwise you're inflating the session number since G will generate sessions for normal hits. non-interactional hit would have ni=1 among the params.
Wait. Scope calculations don't happen immediately in real-time. They happen later on. Give it two days and then check the results and re-conduct your experiment.
Use a throwaway/test/lower GA property to experiment. You don't want to affect the production data while not knowing exactly what you do.
There. A good use case for such an activity would be something like updating a life time value of existing users and wanting to enrich the data with it without waiting for all of them to come in. That's useful for targeting, attribution and more.
Thank you.
This is the case. all CD's are user Scoped.
This is the case, we are collecting them.
ni=1 is within the parameters of each event call.
There are so many parameters, which parameters are neccesary?
we are using a test property for this.
We also got he Bot filtering checked out:
Bot filtering
It's hard to test when the User Explorer has a delay of 2 days and we are still not sure which parameters to use and which not. Who could help on the parameter part? My only goal is to update de CD's on the person. Who knows which parameters need to be part of the event call?
So, I'm working on a CQRS/ES project in which we are having some doubts about how to handle trivial problems that would be easy to handle in other architectures
My scenario is the following:
I have a customer CRUD REST API and each customer has unique document(number), so when I'm registering a new customer I have to verify if there is another customer with that document to avoid duplicity, but when it comes to a CQRS/ES architecture where we have eventual consistency, I found out that this kind of validations can be very hard to address.
It is important to notice that my problem is not across microservices, but between the command application and the query application of the same microservice.
Also we are using eventstore.
My current solution:
So what I do today is, in my command application, before saving the CustomerCreated event, I ask the query application (using PostgreSQL) if there is a customer with that document, and if not, I allow the event to go on. But that doesn't guarantee 100%, right? Because my query can be desynchronized, so I cannot trust it 100%. That's when my second validation kicks in, when my query application is processing the events and saving them to my PostgreSQL, I check again if there is a customer with that document and if there is, I reject that event and emit a compensating event to undo/cancel/inactivate the customer with the duplicated document, therefore finishing that customer stream on eventstore.
Altough this works, there are 2 things that bother me here, the first thing is my command application relying on the query application, so if my query application is down, my command is affected (today I just return false on my validation if query is down but still...) and second thing is, should a query/read model really be able to emit events? And if so, what is the correct way of doing it? Should the command have some kind of API for that? Or should the query emit the event directly to eventstore using some common shared library? And if I have more than one view/read? Which one should I choose to handle this?
Really hope someone could shine a light into these questions and help me this these matters.
For reference, you may want to be reviewing what Greg Young has written about Set Validation.
I ask the query application (using PostgreSQL) if there is a customer with that document, and if not, I allow the event to go on. But that doesn't guarantee 100%, right?
That's exactly right - your read model is stale copy, and may not have all of the information collected by the write model.
That's when my second validation kicks in, when my query application is processing the events and saving them to my PostgreSQL, I check again if there is a customer with that document and if there is, I reject that event and emit a compensating event to undo/cancel/inactivate the customer with the duplicated document, therefore finishing that customer stream on eventstore.
This spelling doesn't quite match the usual designs. The more common implementation is that, if we detect a problem when reading data, we send a command message to the write model, telling it to straighten things out.
This is commonly referred to as a process manager, but you can think of it as the automation of a human supervisor of the system. Conceptually, a process manager is an event sourced collection of messages to be sent to the command model.
You might also want to consider whether you are modeling your domain correctly. If documents are supposed to be unique, then maybe the command model should be using the document number as a key in the book of record, rather than using the customer. Or perhaps the document id should be a function of the customer data, rather than being an arbitrary input.
as far as I know, eventstore doesn't have transactions across different streams
Right - one of the things you really need to be thinking about in general is where your stream boundaries lie. If set validation has significant business value, then you really need to be thinking about getting the entire set into a single stream (or by finding a way to constrain uniqueness without using a set).
How should I send a command message to the write model? via API? via a message broker like Kafka?
That's plumbing; it doesn't really matter how you do it, so long as you are sure that the command runs within its own transaction/unit of work.
So what I do today is, in my command application, before saving the CustomerCreated event, I ask the query application (using PostgreSQL) if there is a customer with that document, and if not, I allow the event to go on. But that doesn't guarantee 100%, right? Because my query can be desynchronized, so I cannot trust it 100%.
No, you cannot safely rely on the query side, which is eventually consistent, to prevent the system to step into an invalid state.
You have two options:
You permit the system to enter in a temporary, pending state and then, eventually, you will bring it into a valid permanent state; for this you could allow the command to pass, yield CustomerRegistered event and using a Saga/Process manager you verify against a uniquely-indexed-by-document-collection and issue a compensating command (not event!), i.e. UnregisterCustomer.
Instead of sending a command, you create&start a Saga/Process that preallocates the document in a uniquely-indexed-by-document-collection and if successfully then send the RegisterCustomer command. You can model the Saga as an entity.
So, in both solution you use a Saga/Process manager. In order for the system to be resilient you should make sure that RegisterCustomer command is idempotent (so you can resend it if the Saga fails/is restarted)
You've butted up against a fairly common problem. I think the other answer by VoicOfUnreason is worth reading. I just wanted to make you aware of a few more options.
A simple approach I have used in the past is to create a lookup table. Your command tries to register the key in a unique constraint table. If it can reserve the key the command can go ahead.
Depending on the nature of the data and the domain you could let this 'problem' occur and raise additional events to mark it. If it is something that's important to the business/the way the application works then you can deal with it either manually or at the time via compensating commands. if the latter then it would make sense to use a process manager.
In some (rare) cases where speed/capacity is less of an issue then you could consider old-fashioned locking and transactions. Admittedly these are much better suited to CRUD style implementations but they can be used in CQRS/ES.
I have more detail on this in my blog post: How to Handle Set Based Consistency Validation in CQRS
I hope you find it helpful.
I am studying CalDAV protocol.
I have some question for time conflict or overlap for CalDAV.
Let me explain by instance for some scenario.
I made an event PM1 ~ PM6 in calendar. And then I try to made another event PM2~7 in same calendar. It is time conflict or overlap.
How does CalDav server resolve this conflict? Does server make error when second event make?
I did search out RFC 6638. But I could not find solution.
Please help my question.
Thanks for reading.
It is up to the CalDAV client to decide how to behave when overlap is involved.
If the client decides to write an event that overlaps another the server will write the overlapping event.
When scheduling is involved (userA wants to invite userB to a meeting but would like to avoid picking a time slot that is already busy in userB's calendar) the CalDAV client can query the FREEBUSY status for a user (see RFC 4791). There's also availability which allows a CalDAV client to retrieve a user's availability (think business hours).
The functionality Kim is asking for a very common one for business calendaring systems (not have the same person booked twice etc).
I think in the CalDAV world there are two parts to this:
a) First the client is supposed to perform a freebusy query to check
whether a user is available. And then show a conflict warning or
whatever seems appropriate.
This is how many systems, including btw Exchange work. Siri also does this kind of conflict detection (“hey, you already have an event at the time, shall I still create the conflicting one, master?”)
b) But in a reasonable system you actually need to guarantee that
the information isn’t outdated at PUT time. I.e. that no second
client has scheduled the same attendee/resource.
I think in CalDAV you can accomplish that by testing the sync-token or the CTag using an If header on the PUT. I.e. let the PUT only succeed if the whole underlying collection didn’t change. And if it did (the PUT will fail with a conflict), redo the freebusy, then try again.
I don’t think that there is a reliable way to do this in CalDAV cross collections (calendars), that is, if the availability of a resource changed because it got booked in a different calendar, the targeted sync collection won’t usually change its sync tag and the PUT would run through.
The bad thing about CalDAV (w/ scheduling) is that PUTs are not idempotent anymore. Otherwise you could do the PUT, recheck whether it still has no conflicts, and if so drop it after the fact.
I want to look at the effect of having performed a specific action sequence at any (tracked) time in the past on user retention and engagement.
The action sequence is that of performing an optional New User Flow.
This is signalled to Google Analytics via sending it appropriate events. That works fine. The events show up in reports as expected.
My problem is what happens to results when I used these events to create segments. I have tried two different ways of creating a segment based on this in Advanced Segmentations, via Conditions (defining the segment via the end event, filtered over users not sessions), and via Sequences (defining start and end events, again filtered over users not sessions).
What I get when I look at various retention/loyalty reports, using either of these segments, is ever so very clearly a result which is doing this segmentation within session, not across uses sessions. So for NUF completers , I am seeing all my loyalty/recency on Session 1, in which people are most likely to do the NUF, if they ever do it at all. This is not what I want. (Mind you it is something that could be really useful in other context, with another event! But not for the new user flow.)
What are my options for getting what I want? I see two possible ways forward:
Using custom dimensions, assigning a custom dimension value in the code when the New User Flow is completed. However I do not know if this will solve the cross-session persistence problem.
Injecting a UserID, which we do not currently do, and (somehow!) using the reports available when you inject a UserID to do this.
Are either of these paths plausible? Is there a better way forward? Is it silly to even try to do this in Google Analytics? I'm way more familiar with App Tracking solutions (e.g. Flurry, Mixpanel, DeltaDNA) which do this as a matter of course, than with Google Analytics, and the fact this is at the very least awkward in Google Analytics is coming a bit of a surprise.
thanks,
Heather
An example:
Say, I have an AJAX chat on a page where people can talk to each other.
How is it possible to display (send) the message sent by person A to persons B, C and D while they have the chat opened?
I understand that technically it works a bit different: the chat(ajax) is reading from DB (or other source), say every second, to find out if there are new messages to display.
But I wonder if there is a method to send the new message to the rest of the people just when it is sent, and not to load the DB with 1000s of reads every second.
Please note that the AJAX chat example is just an example to explain what I want, and is not something I want to realize. I just need to know if there is a method to let all the opened browser at a specific page(ajax) that there is new content on the server that should be gathered.
{sorry for my English}
Since the server cannot respond to a client without a corresponding request, you need to keep state for each user's queued message. However, this is exactly what the database accomplishes. You cannot get around this by replacing the database with something that doesn't just accomplish the same thing in a different way. That said, there are surely optimizations you could do. Keep in mind, however, that you shouldn't prematurely optimize situations like this; databases are designed to handle extremely high traffic, and it's very possible (and in fact, likely), that the scenario described will be handled just fine by the database out of the box.
What you're describing is generally referred to as the 'Comet' concept. See the Wikipedia article for details, especially implementation options (long polling, etc.).
Another answer is to have the server push changes to connected clients, that way there is just one call to the database and then the server pushes the change to all the clients. This article indicates it is possible, however I have never tried this myself.
It's very basic, but if you want to stick with a standard AJAX solution, a simple means of reducing load on the server when polling would be to get the AJAX call to forward the last collected comment ID for that client - you then use that (with the appropriate escaping) in the lookup query on the server side to ensure you only return new comments.