buildNewStructure(){
removeAll(children.query());
sprite = Sprite(Flame.images.fromCache('new_structure.png'));
add(ListButton0(g,structure!));
add(ListButton1(g,structure!));
add(ListButton2(g,structure!));
add(ListButton3(g,structure!));
add(LeftButton(g,structure!));
add(RightButton(g,structure!));}
With this design, old components are not deleted when called frequently. What is the reason for this behavior? How to properly remove old components so that they are definitely removed?
They are deleted, but everything is processed before the next tick, not in the same tick. Just like you say you'll notice a performance degradation if you call lifecycle.processQueues manually since it will then be done two times per tick.
Preferably you shouldn't build logic that depends on checking whether components are in the component tree in the same tick. You can check component.isRemoving if you want to see whether the component is going to be removed before the next tick.
lifecycle.processQueues();
This helped solve the problem, but I'm not sure that this is the right solution, I notice a drop in performance.
Related
I'm planning on using rxdb + hasura/postgresql in the backend. I'm reading this rxdb page for example, which off the bat requires sync-able entities to have a deleted flag.
Q1 (main question)
Is there ANY point at which I can finally hard-delete these entities? What conditions would have to be met - eg could I simply use "older than X months" and then force my app to only ever displays data for less than X months?
Is such a hard-delete, if possible, best carried out directly in the central db, since it will be the source of truth? Would there be any repercussions client-side that I'm not foreseeing/understanding?
I foresee the number of deleted's growing rapidly in my app and i don't want to have to store all this extra data forever.
Q2 (bonus / just curious)
What is the (algorithmic) basis for needing a 'deleted' flag? Is it that it's just faster to check a flag rather than to check for the omission of an object from, say, a very large list. I apologize if it's kind of a stupid question :(
Ultimately it comes down to a decision that's informed by your particular business/product with regards to how long you want to keep deleted entities in your system. For some applications it's important to always keep a history of deleted things or even individual revisions to records stored as a kind of ledger or history. You'll have to make a judgement call as to how long you want to keep your deleted entities.
I'd recommend that you also add a deleted_at column if you haven't already and then you could easily leverage something like Hasura's new Scheduled Triggers functionality to run a recurring job that fully deletes records older than whatever your threshold is.
You could also leverage Hasura's permissions system to ensure that rows that have been deleted aren't returned to the client. There is documentation and examples for ways to work with soft deletes and Hasura
For your second question it is definitely much faster to check for the deleted flag on records than to have to try and diff the entire dataset looking for things that are now missing.
I have my graphs in Grafana automatically updating every few seconds. The last data point on the right drops down temporaily as data comes in. The correct value is eventually shown, but it's low for a few updates. Is this normal? Can it be fixed?
Probably, this will help. Actually, it depends on what type of datasource you use. Some of them, like Elasticsearch, have option "Trim edges".
Expanding/updating Anna's answer: There is now a dashboard-wide setting for "Now Delay" to avoid requesting recent data that might not show up yet. Note, you'll see this delay reflected in your time picker.
Central to a project I'm working on is a highlighting-mechanic that can be applied to certain items on the website. The idea is, that this highlighted-status is only active for a certain amount of time.
I'm trying to find the most performant way to achieve this (in querying, setting status, checking status and revoking it)
A first approach would be to set simply set a value 'highlighted:true' to the item. This seems to be the most performant way to query for highlighted items. The Drawback I see here, is that there also needs to be stored a date for the highlighting-action, but furthermore there needs to run an interval to check on the highlighted items and potentially revoke their highlighted status. Also the exact moment when the item stops beeing highlighted can't be determined exactly, since its depending on the interval of the check-function.
A second approach would be to mainly store the date of the highlighting-action and run the query against it. It seems that the query of highlighted objects is way less performant, since every item ever is beeing checked, and on top its not just a boolean, but a proper function that throws those differnt date-values around to check if it is still valid. On the upside there is no external cleanup-function neccessary and every highlighting period ends perfectly on time.
Would love to have your input on this. Is there maybe a clever pattern on this?
I know about prepared transaction in Postgres, but seems you can just commit or rollback it later. You cannot even view the transaction's db state before you've committed it. Is any way to save transaction for later use?
What I want to achieve actually is a preview (and correcting) of some changes in db (changes are imports from csv file, so user need to see preview before apply it). I want to make changes, add some changes later, see full state of db and apply it (certainly, commit transaction)
I cannot find a very good reference in docs, but I have a very strong feeling that the answer is: No, you cannot do that.
It would mean that when you "save" the transaction, the database would basically have to maintain all of its locks in place for an indefinite amount of time. Even if it was possible, it would mean horrible failure modes and trouble on all fronts.
For the pattern that you are describing, I would use two separate transactions. Import to a staging table and show that to user (or import to the main table but mark rows as "unapproved"). If user approves, in another transactions move or update these rows.
You can always end up in a situation where user can simply leave or crash without clicking "OK" or "Cancel". If what you're describing was possible, you would end up with a hung transaction holding all these resources. In my proposed solution you end up with wasteful rows in "staging" table that you may still show to user later or remove.
You may want to read up on persistence saga. This is actually a very simple example of a well known and researched problem.
To make the long story short, this pattern breaks down a long-running process like yours into smaller operations that are applied and persisted in some way in separate transactions. If any of them happens to fail (or does not occur as expected), you have compensating actions that usually undo what the steps executed so far have done (e.g. by throwing away stale/irrelevant data).
Here's a decent introduction:
https://blog.couchbase.com/saga-pattern-implement-business-transactions-using-microservices-part/#:~:text=The%20SAGA%20Pattern,completion%20of%20the%20previous%20one.
http://vasters.com/clemensv/2012/09/01/Sagas.aspx
This concept was formally introduced in the 80s, but is well alive and relevant today.
I have a collection with a bunch of documents representing various items. Once in a while, I need to update item properties, but the update takes some time. When properties are updated, the item gets a new timestamp for when it was modified. If I run updates one at a time, then there is no problem. However, if I want to run multiple update processes simultaneously, it's possible that one process starts updating the item, but the next process still sees the item as needing an update and starts updating it as well.
One solution is to mark the item as soon as it is retrieved for update (findAndModify), but it seems wasteful to add a whole extra field to every document just to keep track of items currently being updated.
This should be a very common issue. Maybe there are some built-in functions that exist to address it? If not, is there a standard established method to deal with it?
I apologize if this has been addressed before, but I am having a hard time finding this information. I may just be using the wrong terms.
You could use db.currentOp() to check if an update is already in flight.