On a route serving multiple cities, is there a limit to the number of people who can book tickets in one of the cities?

For example, consider a flight from Los Angeles to Moscow via New York. Is there a limit to the number of tickets that can be purchased in Los Angeles or New York?

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Evaluation: 5

.

python – incremental shift recovery and constant limit

I have the following algorithm to retrieve data using limit and offset.
I wonder if it's ok?

Perhaps there is a classic way to extract data in a loop using the chaul + offset method?

async def get_alerts_in_range (
self, date_start: str, date_end: str, offset = 0, limit = 100
):
alerts = []
    in truth:
if len (alerts)> = limit:
Pause

# IDs only of elastic search
ids = wait elastic_search.search_by_range (date_start, date_end,
offset, limit)
if not ids:
Pause

offset + = len (ids)

# Getting the list of dynamo table alert objects by their identifiers
in_range = wait dynamo_db.batch_get_ids (ids)
for alert in inrange:
if len (alerts) <limit and control (alert):
alerts.append (alert)
return alerts

I want to return a list of alerts it will pass check(it will return true / false) method and no more limit

Equation Resolution – Finding Limit Cases for the Root of a Function

I'm sorry my title is not descriptive; the feature that interests me is too long to put on it. What I'm studying is the real and positive roots of the following function:
$ f ( epsilon) = ( Delta ^ 2- epsilon ^ 2) ( epsilon ^ 2 – ( Gamma_1 + Gamma_2) ^ 2/4) + Delta ^ 2 Gamma_1 Gamma_2 + ( Gamma_1 + Gamma_2) , epsilon ^ 2 , sqrt { Delta ^ 2- epsilon ^ 2} $

Here all the coefficients are real and positive.

Now, this function is easily evaluated with the help of numerical methods, but I would like to know if it is possible to perform analyzes to come up with expressions indicating how things are evolving. .

More specifically, I am interested in scaling up $ epsilon $ (For who $ f ( epsilon) = $ 0) with $ delta = green { Gamma_1- Gamma_2} green $, in the case where $ Delta gg max {( Gamma_1, Gamma_2)} $. Indeed, we see that for $ Gamma_1 = Gamma_2 $, $ epsilon = $ 0. I would like to know how $ epsilon $ approach 0 as $ delta $ goes to 0. Is this something that is analytically possible? I'm quite good to know how the first order behaves, it would be a good start.

What I have tried to do so far is the following:

eqn = ([CapitalDelta]^ 2 - [Epsilon]^ 2) * ([Epsilon]^ 2 -
0 ^ 2 - ([CapitalGamma]1 + [CapitalGamma]2) ^ 2 /
4) + [CapitalDelta]^ 2 * [CapitalGamma]1 * [CapitalGamma]2 * 1 + 
([CapitalGamma]1 + [CapitalGamma]2) * [Epsilon]^ 2 *
sqrt[[[[[CapitalDelta]^ 2 - [Epsilon]^ 2]== 0;

soils = solve[Eqn{[Eqn{[{eqn[{eqn[CapitalGamma]1> 0, [CapitalGamma]2>
0, [CapitalDelta] > [CapitalGamma]1, [CapitalDelta] > 
[CapitalGamma]2}, [Epsilon], Reals]

This results in two solutions of rather complicated appearance and one of the two, at the digital inspection, is positive and the other negative. Let's say I'm interested in the positive for the moment. Put in numbers and look at the result

Ground[{[{[{[{[Epsilon] /. {Last @ sols}} /. {[CapitalDelta] ->
1, [CapitalGamma]2 -> 0.1}, {[CapitalGamma]1, 0, 1}]

enter the description of the image here

This shows the behavior that I expect in $ Gamma_1 = Gamma_2 $We are on the right track. But now, I might want to introduce a limit of $ ( Gamma_1, Gamma_2) / Delta rightarrow 0 $ or something like that, and do an expansion of the series in $ delta = green { Gamma_1- Gamma_2} green $but I am a bit stuck on how to get there. Could someone help?

For the context, the equation comes from Josephson resonance current
Beenakker and van Houten from 1992 through a Quantum Dot
and describes the energy-phase relationship of a bound state in the system.

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Evaluation: 5

.

postgresql – SELECT very slow when JOIN and LIMIT are specified but none / few results found

I'm having a problem where the query planner does not consider how a join affects the frequency of particular values.

For some contexts: I only store sessions in an auxiliary journal where each session will have an entry (with all the data in the session) for each update.

CREATE TABLE session
update_id bigint NOT NULL,
session_id bigint NOT NULL,
VARCHAR status (50) NOT NULL,
...
)

To keep track of the "coolest" information, I have a second chart that keeps track of it.

CREATE TABLE sessionlatest (
session_id BIGINT NOT NULL,
update_id BIGINT NOT NULL,
event_id BIGINT NOT NULL,
time_in_millis TIMESTAMP WITH NON-NULL TIME ZONE
)

cardinality

~ 5 million rows in session

~ 97% of the lines of the session have the status "STARTED"

~ 50K lines in sessionlatest

~ 10 to 50 lines on the join session and the last session (that is, most sessions are no longer started)

My goal is to get the list of sessions currently "STARTED", that is to say that their last update has the status "STARTED".

Postgres Version 9.6.10

Queries

Problematic query:

EXPLAIN THE SELECT ANALYSIS *
Session gs
join "public". "sessionlatest" gsl
on gs. "update_id" = gsl. "Update_id"
WHERE gs. "Status" = "STARTS & # 39;
order by gs. "session_id" desc
LIMIT 500;

Limit (cost = 0.85..37681.96 lines = 500 width = 909) (real time = 0.137..45960.666 lines = 29 loops = 1)
-> Nested loop (cost = 0.85..2996779.86 lines = 39765 width = 909) (real time = 0.135..45960.644 lines = 29 loops = 1)
-> Index Scan back using "IDX_session_session_id" on session gs (cost = 0.43..808987.56 rows = 4884873 width = 869) (real time = 0.038..32928.897 rows = 4848024 loops = 1)
Filter: ((status) :: text = & # 39; STARTED & # 39; :: text)
Lines removed by filter: 115172
-> Index Scan using "IDX_sessionlatest_update_id" on sessionlatest gsl (cost = 0.41..0.44 rows = 1 width = 32) (actual time = 0.002..0.002 rows = 0 loops = 4848024)
Cond Index: (update_id = gs.update_id)
Planning time: 1,108 ms
Running time: 45960.839 ms

Request without limit:

EXPLAIN THE SELECT ANALYSIS *
Session gs
join "public". "sessionlatest" gsl
on gs. "update_id" = gsl. "Update_id"
WHERE gs. "Status" = "STARTS & # 39;
order by gs. "session_id" desc;

Sort (cost = 249561.70..249661.11 rows = 39765 width = 909) (real time = 145.306..145.317 rows = 28 loops = 1)
Sort key: gs.session_id DESC
Sorting method: quicksort Memory: 55kB
-> Nested loop (cost = 0.43..230619.81 lines = 39765 width = 909) (real time = 69.713.145.205 lines = 28 loops = 1)
-> Seq Scan on sessionlatest gsl (cost = 0.00..743.23 lines = 40723 width = 32) (real time = 0.010..5.386 lines = 40732 loops = 1)
-> Index analysis using "IDX_session_update_partial_status_started" on session gs (cost = 0.43..5.63 rows = 1 width = 869) (actual time = 0.003..0.003 rows = 0 loops = 40732)
Cond Index: (update_id = gsl.update_id)
Planning time: 0.955 ms
Running time: 145.431 ms

Request without order:

EXPLAIN THE SELECT ANALYSIS *
Session gs
join "public". "sessionlatest" gsl
on gs. "update_id" = gsl. "Update_id"
WHERE gs. "Status" = "STARTS & # 39;
LIMIT 500;

Limit (cost = 0.43..2900.21 lines = 500 width = 901) (real time = 70.971..149.729 lines = 28 loops = 1)
-> Nested loop (cost = 0.43..230619.81 lines = 39765 width = 901) (real time = 70.970..149.721 lines = 28 loops = 1)
-> Seq Scan on sessionlatest gsl (cost = 0.00..743.23 lines = 40723 width = 32) (real time = 0.011..5.655 lines = 40732 loops = 1)
-> Index analysis using "IDX_session_update_partial_status_started" on session gs (cost = 0.43..5.63 rows = 1 width = 869) (actual time = 0.003..0.003 rows = 0 loops = 40732)
Cond Index: (update_id = gsl.update_id)
Planning time: 0.874 ms
Running time: 149.820 ms

In my case of use, I need both the command and the limit. After some research, I think that since the "STARTED" status is very common, the query planner prefers to perform a sequential analysis as long as there is a limit (because it assumes that it will respect the limit in the first lines). Which is not correct, because after joining the sessionlatest table, the limit will never be satisfied.

I tried to add a multi-column index but it was ignored.

CREATE INDEX idx_session_id_status ON public.session (session_id, status);

I also tried a partial index but the performance improvement was minimal.

CREATE INDEX idx_session_id_partial_status ON public.session WHERE public.session.status = STARTED;

Limit (cost = 0.72.34319.23 lines = 500 width = 903)
-> Nested loop (cost = 0.72..1145415.36 rows = 16688 width = 903)
-> Index Scan back using idx_session_id_partial_status on the gs session (cost = 0.43..435253.15 rows = 2252261 width = 863)
-> Index Scan using "IDX_Sessionlatest_update_id" on sessionlatest gsl (cost = 0.29..0.31 rows = 1 width = 32)
Cond Index: (update_id = gs.update_id)

Finally, I saw a very similar SELECT very slow when no result and a LIMIT is specified, the main difference being that my corner case is created by joins rather than by multiple filters (and I obviously can not create index on different tables).

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Evaluation: 5

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Evaluation: 5

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forms – How can I add a field type "reference to an entity" with a cardinality limit of 5

I'm doing this code but it's not complicated

    
    
    
    
$ form['details']['name_field'][]    = table (
& # 39; # type & # 39; => & # 39; entity_autocomplete & # 39 ;,
& # 39; # title & # 39; => $ this-> t (& # 39; Title & # 39;),
& # 39; # target_type & # 39; => & # 39; knot & # 39;
& # 39; # multiple & # 39; => TRUE,
& # 39; # selection_settings & # 39; => [
                'target_bundles' => ['article']
            ]