Mirror API latency when sending something to a timeline - google-mirror-api

It seems that sometimes timeline items (just text) arrive instantly and other times they take forever... Is there a way to send one at precisely the right time?

You can send the notification at a precise time.
timelineItem.getNotification()
.setDeliveryTime(new DateTime(oneMinuteInFuture.getTime()));
That's a java example, where oneMinuteInFuture is a Calendar object set to one minute after now.
What happens when you do this is the card is inserted in the timeline immediately, but the notification is delayed until the specified time. So the card goes in right away and one minute later I get a chime.
There is an unaccepted issue related to this at the issue tracker you might want to star and follow, it appears that this functionality might change in the future.

Related

Consolidate/discard events in count window

I just started using Flink and have a problem I'm not sure how to solve. I get events from a Kafka Topic, these events represent a "beacon" signal from a mobile device. The device sends an event every 10 seconds.
I have an external customer that is asking for a beacon from our devices but every 60 seconds. Since we are already using Flink to process other events I thought I could solve this using a count window, but I'm struggling to understand how to "discard" the first 5 events and emit only the last one. Any ideas?
There are some ways to do this. As Far as I understand the idea is as follows: You receive beacon signal each 10 sec but You actually only need the most actual one and disard the others since the client asks for the data each 60 sec.
The simplest would be ofc to use ProcessFunction with count/event time window as You said. The type of the window actually depends on Your requirements. Then You sould do something like this:
stream.timeWindow([windowSize]).process(new CustomWindowProcessFunction())
The signature of the process() method of the ProcessWindowFunctionis as follows, depending on the type of the actual function def process(context: Context, elements: Iterable[IN], out: Collector[OUT]). So basically it gives you the acces to all window elements, so You can easily only push further the elements You like.
While this is the simplest idea, you may want also to take a look at the Flink timers, as they seem to be a good solution for Your issue. They are described here.

Extended windows

I have an always one application, listening to a Kafka stream, and processing events. Events are part of a session. And I need to do calculations based off of a sessions data. I am running into a problem trying to correctly run my calculations due to the length of my sessions. 90% of my sessions are done after 5 minutes. 99% are done after 1 hour. Sessions may last more than a day, due to this being a real-time system, there is no determined end. Session are unique, and show never collide.
I am looking for a way where I can process a window multiple times, either with an initial wait period and processing any later events after that, or a pure process per event type structure. I will need to keep all previous events around(ListState), as well as previously processed values(ValueState).
I previously thought allowedLateness would allow me to do this, but it seems the lateness is only considered for when the event should have been processed, it does not extend an actual window. GlobalWindows may also work, but I am unsure if there is a way to process a window multiple times. I believe I can used an evictor with GlobalWindows to purge the Windows after a period of inactivity(although admittedly, I did not research this yet, because I was unsure of how to trigger a GlobalWindow multiple times.
Any suggestions on how to achieve what I am looking to do would be greatly appreciated, I would also be happy to clarify any points needed.
If SessionWindows won't do the job, then you can use GlobalWindows with a custom Trigger and Evictor. The Trigger interface has onElement and timer-based callbacks that can fire whenever and as often as you like. If you go down this route, then yes, you'll also need to implement an Evictor to dispose of elements when they are no longer needed.
The documentation and the source code are helpful when trying to understand how this all fits together.

Instagram "posted for first time in a while" notification

Does anyone know how Instagram determines whether or not to send a push notification saying "_______ has posted for the first time in a while". Is it based purely on time, or is it different based on how often the user posts? If it's based on the individual person, what is the algorithm they use to determine whether a notification should be sent?
It depends on how often you post before. If you post every day, but then only post a week later, the notification may appear.
In general, it could be some range from 1 to 3 weeks to multiple months.

Clear previous Alexa Cards

Is there a way to tell Alexa to either remove previous cards when I send a new one?
I have an skill which sends kind of a status each time you run a command, and typical use case is to do multiple actions in a session, each of which I'd like to send a card. It gets really cluttered since they all just add on to each other. I'd like to just either update the first card, or remove it and make a new one each time.
That is not possible with the current API. I think anyone using skills is already used to the flood of cards that come after each interaction.

Is there an elegant way to post messages to AWS SQS with visibility delay of longer than 15 minutes?

In Amazon Web Services, their queues allow you to post messages with a visibility delay up to 15 minutes. What if I don't want messages visible for 6 months?
I'm trying to come up with an elegant solution to the poll/push problem. I can write code to poll the SQS (or a database) every few seconds, check for messages that are ready to be visible, then move them to a "visible queue", or something like that. I wish there was a simpler, more reliable method to have messages become visible in queues far into the future without me having to worry about my polling application working perfectly all the time.
I'm not married to AWS, SQS or any of that, but I'd prefer to find a cloud-friendly solution that is stable, reliable and will trigger an event far into the future without me having to worry about checking on its status every day.
Any thoughts or alternate trees for me to explore barking up are welcome.
Thanks!
It sounds like you might be misunderstanding the visibility delay. Its purpose is to make sure that the polling application doesn't pull the same item off the queue more than once.
In other words, when the item is pulled off the queue it becomes invisible for a predetermined period of time (default is 30 seconds, max is 15 minutes) in case the polling system has a cluster of machines reading from the queue all at once.
Here's the relevant documentation:
http://docs.amazonwebservices.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/IntroductionArticle.html#AboutVT
...and the sentence in particular that relates to my comment is:
"Immediately after the component receives the message, the message is still in the queue. However, you don't want other components in the system receiving and processing the message again. Therefore, Amazon SQS blocks them with a visibility timeout, which is a period of time during which Amazon SQS prevents other consuming components from receiving and processing that message."
You should be able to use SQS for your purpose since you can leave an item in the queue for as long as you want.
7 years later, and Amazon still doesn't support the feature you need!
The two ways you can sort of get it to work are:
have messages contain a delivery target datetime in their message_attributes, and have the workers that consume the queue's messages just delete and recreate any message that is consumed before its target, with delay = max(0, min(secs_until_target_datetime, 900)) ; that would allow you to effectively schedule a message for any arbitrary future time;
or,
(slightly less frequent and costly:) similarly, if a message isn't due to be handled yet, recreate it and change its visibility timeout to be timeout = max(0, min(secs_until_target_datetime, 43200))
The disadvantage of using visibility timeout is that any read will re-trigger it.
There has been a direct AWS solution possible since 2016-12-01: AWS Step Functions
Each execution can last/idle up to one year, persists the state between transitions, and doesn't cost you any money while it waits.

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