In my Anylogic model I have a hub which can store 5 containers. So it has a capacity parameter with value 5. I also have given it a variable with the numberOfContainers stored at the hub at that moment. When I run the model I see that the variable works (it changes over time to the number of containers that is stored at that moment).
Now I want another agent in my model to make a decision based on whether the capacity of the hub is reached at that moment (within its statechart). I tried to create a branche with the following condition:
main.hub.numberOfContainers > main.hub.capacity
but it doesn't work, the statechart acts like the capacity is never reached, even if the number of containers is much higher than the capacity. Does anybody know how to make this work?
Typically, condition branches are tricky because the condition may not be evaluated at the time you want it to be. Here is an example.
At time n there are 3 containers in the hub
At time n+1 there are 10 containers in the hub
At time n+2 there are 2 containers in the hub
The model may have missed evaluating the condition at time (n+1) which is why your transition would not be triggered.
To address this issue, I have 3 possible suggestions:
Do not use a condition transition. Instead, use a message. For example, if you are storing the containers in a queue, then, on the "On Enter" and "On Exit" fields of the queue, add the condition:
if(queue.size >= main.hub.numberOfContainers)
<send msg to the statechart>
Use a cyclic event to check if the condition is met every second or millisecond or whatever time period makes sense to you. When the condition is met, send a message to trigger the transition. But the problem with this method is that it might slow down your model with poor performance.
Use the onChange() function. This function is used to signal to your model that a change happened and the condition trigger needs to be evaluated. So, you need to make sure to place onChange() whenever a change that might cause the condition to become true happens. In the example provided under option 1 above, that would be in the fields of the queue "On Enter" and "On Exit".
Related
I would like to know how many times the GET event would happen without actually calling it (or calling it only one time).
By now, I know how to get the total number of iterations: lines( (ldb_include)node_table[] ) , but this only works if the GET has been called, and if the GET has been called, it will iterate through node_table and if it has 8798237 entries, they all will be PUT, but as I already have the number of iterations (that's all I need), I don't want to have all the values put.
I can leave the GET by using REJECT, but it will only go to the next iteration... currently, I don't know how to completely quit the GET.
I've tried using STOP, but it raises the event of end-of-selection immediately, which is not the idea...
at selection-screen output.
"process the selection screen
start-of-selection.
get <node_tab>
"lv_total = lines( (ldb_include)node_table[] )
"some sort of REJECT to all get events
"continue processing the rest of the code, using the lv_total
end-of-selection.
"display the output
I can achieve it using a flag like
if first execution = abap_true. "process it
else reject <node_tab>.
But it would, in all cases, iterate through all the GET events, against the idea. I would like to understand if there is a smarter (possibly more elegant) to iterate only the first GET, and skip all the others.
It's like saying there's a database view with joined tables, but one table is not needed, how to make the program read the view but tell the database not read one table...
Impossible!
The only solution is to copy and adapt the Logical Database. As simple as that.
And, of course, logical databases are obsolete for a long time, so prefer using a database join, or anything else better.
In a vrp problem, I want to employ different probability distribitions for all moveSelectors depending on where in the chain the planning is being done. More concretely, I want to employ a block distribution for the first entity in the chain and parabolic for anywhere else in the (same) chain.
Now, I could configure identical moves one with block distribution and one with parabolic, but this is going to get cluttered very quick. So, instead I am wondering what will happen if I state that in the implemented NearbyDistanceMeter the distance is 0 if it is the first entity in the chain and a value > 0 if it is not the first entity. Will this work as intended ?
It will not.
The NearbyDistanceMeter should be idempotent (give the same result when called twice), regardless of the state of the planning variables.
In fact, it's called & cached before solving really starts.
I have a Prometheus counter, for which I want to get its rate on a time range (the real target is to sum the rate, and sometimes use histogram_quantile on that for histogram metric).
However, I've got multiple machines running that kind of job, each one sets its own instance label. This causes different inc operations on this counter in different machines to create different entities of the counter, as the combination of labels values is unique.
The problem is that rate() works separately on each such counter entity.
The result is that counter entities with unique combinations don't get into account for rate().
For example, if I've got:
mycounter{aaa="1",instance="1.2.3.4:6666",job="job1"} value: 1
mycounter{aaa="2",instance="1.2.3.4:6666",job="job1"} value: 1
mycounter{aaa="2",instance="1.2.3.4:7777",job="job1"} value: 1
mycounter{aaa="1",instance="5.5.5.5:6666",job="job1"} value: 1
All counter entities are unique, so they get values of 1.
If counter labels are always unique (come from different machines), rate(mycounter[5m]) would get values of 0 in this case,
and sum(rate(mycounter[5m])) would get 0, which is not what I need!
I want to ignore the instance label so that it would refer these mycounter inc operations as they were made on the same counter entity.
In other words, I expect to have only 2 entities (they can have a common instance value or no instance label):
mycounter{aaa="1", job="job1"} value: 2
mycounter{aaa="2", job="job1"} value: 2
In such a case, inc operation in new machine (with existing aaa value) would increase some entity counter instead of adding new entity with value of 1, and rate() would get real rates for each, so we may sum() them.
How do I do that?
I made several tries to solve it but all failed:
Doing a rate() of the sum() - fails because of type mismatch...
Removing the automatic instance label, using metric_relabel_configswork with action: labeldrop in configuration, but then it assigns the default address value.
Changing all instance values to a common one using metric_relabel_configswork with replacement, but it seems that one of the entities overwrites all others, so it doesn't help...
Any suggestions?
Prometheus version: 2.3.2
Thanks in Advance!
You'd better expose your counters at 0 on application start, if the other labels (aaa, etc) have a limited set of possible combinations. This way rate() function works correctly at the bottom level and sum() will give you correct results.
If you have to do a rate() of the sum(), read this first:
Note that when combining rate() with an aggregation operator (e.g. sum()) or a function aggregating over time (any function ending in _over_time), always take a rate() first, then aggregate. Otherwise rate() cannot detect counter resets when your target restarts.
If you can tolerate this (or the instances reset counters at the same time), there's a way to work around. Define a recording rule as
record: job:mycounter:sum
expr: sum without(instance) (mycounter)
and then this expression works:
sum(rate(job:mycounter:sum[5m]))
The obvious query rate(sum(...)) won't work in most cases, since the resulting sum(...) may hide possible resets to zero for individual time series, which are passed to sum. So usually the correct answer is to use sum(rate(...)) instead. See this article for details.
Unfortunately, Prometheus may miss some increases for slow-changing counter when calculating rate() as shown in the original question above. The same applies to increase() calculations. See this issue, this comment and this article for details. Prometheus developers are going to fix these issues - see this design doc.
In the mean time try to use VictoriaMetrics when you need exact values for rate() and increase() functions over slow-changing counter (and distributed counter).
I have a stored procedure that returns 2 values.
In another procedure, I call this (edit: NOT selectable) procedure but only need one of the two returned values.
Is there a way to discard the other value? I'm wondering what is a good practice, and hoping for a small performance gain.
Here is how I call the procedure without error:
CREATE or ALTER procedure my_proc1
as
declare variable v_out1 integer default null;
declare variable v_out2 varchar(10) default null;
begin
execute procedure my_proc2('my_param')
returning_values :v_out1, :v_out2;
end;
That is the only way I found to call this procedure without getting a -607 error 'unsuccessful metadata update request depth exceeded. (Recursive definition?)' whenever I use only one variable v_out1.
So my actual question is: can I avoid creating a v_out2 variable for nothing, as I will never use it (that value is only used in other procedures which also call my_proc2)?
Edit: the stored procedure my_proc2 is actually not selectable. But I made it selectable after all.
Because your stored procedure is selectable, you should call it by SELECT statement, ie
select out1, out2 from my_proc2('my_param')
and in that case you can indeed omit some of the return value(s). However, I wouldn't expect noticeable performance gain as the logic inside the SP which calculates the omitted field is still executed.
If your procedure is not selectable, then creating a wrapper SP is the only way, but again, it woulnd't give any performance gain as the code which does the hard work inside the original SP is still executed.
The answer is made to use text formatting while demonstrating "race conditions" in the multithreading programming (which SQL is) when [ab]using out-of-transaction objects (SQL sequences aka Firebird Generators).
So, the "use case".
Initial condition: table is empty, generator=0.
You start two concurrent transactions, A and B. For ease of imagining you may think those transactions were started from concurrent connections made by two persons working with your program on two networked computers. Though actually it does not matter much, if you open them transactions from one same connection - the scenario would not change a bit. Just for the ease of imagining.
The Tx.A issues UPDATE-OR-INSERT which inserts new row into the table. Doing so it up-ticks the generator. The transaction is not committed yet. Database condition: the table has one invisible (non-committed) row with auto_id=1, the generator = 1.
The Tx.B issues UPDATE-OR-INSERT too which inserts yet another row into the table. Doing so it also up-ticks the generator. The transaction maybe commits now, or maybe later, irrelevant. Database condition: the table has two rows (one or both are invisible (non-committed)) with auto_id=1 and auto_id=2, the generator = 2.
The Tx.A meets some error, throws the exception, DOWNTICKS the generator and rolls back. Database condition: the table has one row with auto_id=2 the generator = 1.
If Tx.B was not committed before, it is committed now. (this "if" just to demonstrate that it does not matter when other transactions would be committed, earlier or later, it only matters that Tx.A downticks the generator after any other transaction upticked it)
So, the final database condition: the table has one committed=visible row with auto_id=2 and the generator = 1.
Any next attempt to add yet one more row would try to up the generator 1+1=2 and then fail to insert new row with PK violation, then it would down the generator to 1 to recreate the faulty condition outlined above.
Your database stuck and without direct intervention by DB Administrator can not have data added further.
The very idea of rolling back the generator is defeating all intentions generators were created for and all expectations about generators behavior that the database and connection libraries and other programmers have.
You just placed a trap on the highway. It is only a matter of time until someone will be caught into it.
Even if you would continue guarding this hack by other hacks for now - wasting a lot of time and attention to do that scrupulously and pervasively - still one unlucky day in the future there would be another programmer, or even you would forget this gory details - and you would start using the generator in standard intended way - and would run into the trap.
Generators were not made to be backtracked during normal work.
existence of primary key is checked in the procedure before doing anything
Yep, that is the first reaction when multithreading programmer meets his first race condition. Let's just add more prior checks.
First few checks indeed can decrease probability of a clash, but it never can alleviate it completely. And the more use your program would see, the more transactions would get opened by more and more concurrent and active users - it is only a matter of time until this somewhat lowered probability would turn out still too much.
Think about it, SQL is about transactions, yet they had to invent and introduce explicitly out-of-transactions device Generator/Sequence is. If there was reliable solution without them - it would be just used instead of creating that so non-SQLish transaction boundary breaking tool.
When you say your SP "checks for PK violation" it is exactly the same as if you would drop the generator altogether and instead just issue "good old"
:new_id = ( select max(auto_id)+1 from MyTable );
By your description you actually do something like that, but in some indirect way. Something like
while exists( select * from MyTable where auto_id = gen_id(MyGen, +1))
do ;
:new_id = gen_id(MyGen, 0);
You may feel, that because you mentioned generators, you somehow overcame the cross-transaction invisibility problem. But you did not, because the very check "if PK was already taken" is done against in-transaction table.
That changes nothing, your two transactions Tx.A and Tx.B would not see each other's records, because they both did not committed yet. Now it only takes some unlucky Tx.C that would fail and downtick the generator to them collide on the same ID.
Or not, you do not even need Tx.C and downticking at all!
Here we bump into the multithreading idea about "atomic operations".
Let's look at it again.
while exists( select * from MyTable where auto_id = gen_id(MyGen, +1))
do ;
:new_id = gen_id(MyGen, 0);
In a single-threaded application that code is okay: you just keep running the generator up until the free slot, then you just query the value without changing it. "What could possibly go wrong?" But in multithreaded environment it is rooks waiting to be stepped over. Example:
Initial condition, table has 100 rows (auto_id goes from 1 to 100), the generator = 100.
Tx.A starts adding the row, upticks the generator in the while loop and exits the loop. It does not yet pass to the second line where local variable gets assigned. Not yet. The generator = 101, rows not added yet.
Tx.B starts adding the row, upticks the generator in the while loop and exits the loop. The generator = 102, rows not added yet.
Tx.A goes to the second line and reads gen_id(MyGen,0) into a variable for new row. While it was 101 out of the loop, it is 102 now!
Tx.B goes to the second line and reads gen_id(MyGen,0) and gets 102 too.
Tx.A and Tx.B both try to insert new row with auto_id=102
RACE CONDITIONS - both Tx.A and Tx.B try to commit their work. One of them succeeds, another fails. Which one? It is not predictable. A lucky one commits, an unlucky one fails.
The failed transaction downticks the generator.
Final condition: the table has 101 rows, the auto_id consistently goes from 1 to 100 and then skips to 102. The generator = 101, which his less than MAX(auto_id)
Now you might want to add more hacks, I mean more prior checks before actually inserting rows and committing. It will make mistakes yet less probable, right? Wrong. The more checks you do - the slower gets the code. The slower gets the code - the greater gets probability, that while one thread runs throw all them checks there happens another thread that interferes and alters the situation that was checked a moment ago.
The fundamental issue with multithreading is that any check is SEPARATE action. And between those actions the situation MAY change. Your procedure may check whatever it wants BEFORE actually inserting the row. It would not warrant much. Because when you finally gets at the row inserting statement, all the checks you did in the PAST are a matter of past. And the situation is potentially already altered. And warrants your checks were giving in the PAST only belong to that past, not to the moment at hands.
And even if you no more look for warranting sure thing, still adding every new check you can not even be sure if doing so you just decreased or increased probability of failure. Because multithreading is a bitch, it is flowing chaotically out of your control.
So, remember the KISS principle. Until proven otherwise - you most probably do not need SP2 at all, you only need one single UPDATE-OR-INSERT statement.
PS. There was a pretty fun game in my school days, it was called Pascal Robots. There are also C Robots I heard and probably implementation for other many languages. With Pascal Robots though came a number of already coded robots, demonstrating different strategies and approaches. Some of them were really thought out in very intrinsic details. And there was one robot which program was PRIMITIVE. It only had two loops: if you do not see an enemy - keep turning your radar around, if you do see an enemy - keep running to it and shooting at it. That was all. What could this idiot do against sophisticated robots having creative attack and defense strategies, flanking maneuvers, optimal distance to maintain by back and forth movements, escape tricks and more? Those sophisticated robots employed very extensive checks and very thought through hacks to be triggered by those checks. So... ...so that primitive idiot was second or maybe third best robot in the shipped set. there was only one or two smarties who could outwit it. With ALL the other robots this lean-and-fast idiot finished them before they could run through all their checks and hacks thrice. That is what multithreading does to programming. It was astonishing to watch those battles, which went so against out single-threaded intuition.
I am building a pymc model which must evaluate a very cpu expensive function (up to 1 sec per call on a very decent hardware). I am trying to limit the explored parameter space to meaningful solutions by means of a potential (the sum of a list of my variables has to stay within a given range). This works but I noticed that even when my potential returns an infinite value and forbids the parameters choice, this function gets evaluated. Is there a way to prevent that? Can one force the sampler to use a given evaluation sequence (pick up the necessary variables, check if the potential is ok and proceed if allowed)
I thought of using the potential inside the function itself and use it to determine whether it must proceed or immediately return, but is there a better way?
Jean-François
I am not aware of a way of ordering the evaluation of the potentials. This might not be the best way of doing so, but you might be able to check if the parameters are within reasonable at the beginning of the simulation. If the parameters are not within reasonable bounds you can return a value that will create your posterior to be zero.
Another option is to create a function for your likelihood. At the beginning of this function you could check if the parameters are within reasonable limits. If they are not you can return -inf without running your simulation. If they are reasonable you can run your model and calculate the log(p).
This is definitely not an elegant solution but it should work.
Full disclosure - I am not by any means a pymc expert.