I found out that it is possible to detect the absence of an event using for example:
select * from pattern [every EventX -> (timer:interval(10 sec) and not EventX)], but is it also possible to detect the presence of an event after it was absent? Using prior perhaps? And is it possible to use one statement for detecting both absence and presence?
Thanks in advance!
Its sounds like you are looking for this
every EventX -> (timer:interval(10 sec) and not EventX) -> Event X
...adding some time interval withing which the event should arrive...
every EventX -> (timer:interval(10 sec) and not EventX) -> Event X where timer:within(10)
Try an outer join to detect with multiple patterns:
select * from pattern[...].win:length_batch(1) as pattern1 full outer join pattern[...].win:length_batch(1) as pattern2
Related
I'm trying to batch Notification events like this and I'm getting one Notifications event with a single notification event. Can anyone help me?
Thnks in advance.
Relevant Statements
INSERT INTO Notification SELECT d.id as id,a.stationId as stationId,d.firebaseToken as firebaseToken, d.position as devicePos,a.location as stationPos,a.levelNumber as levelNumber,a.levelName as levelName FROM AirQualityAlert.win:time(3sec) as a, device.win:time(3sec) as d WHERE d.position.distance(a.location) < 300
INSERT INTO Notifications SELECT * FROM Notification.std:groupwin(id).win:time_batch(20sec) for grouped_delivery(id)
This solution delivers a row per 'id' that contain a column with the list of events.
create context Batch20Sec start #now end after 20 sec;
context Batch20Sec select id, window(*) as data
from Notifications#keepall
group by id
output all when terminated;
I think that is what you want.
I was looking to this question, i need this select * from pattern [every (timer:interval(10 sec) and not EventX)]; but with a WHERE id = "001", i dont know where to put the WEHERE.
select * from pattern [every (timer:interval(10 sec) and not EventX(id="001"))];
Given chain of insert-into statements, for example:
on GenericEvent insert into rule_A_stream select *;
on rule_A_stream
insert into rule_B_stream select * where condition1
insert into rule_C_stream select * where condition2;
on rule_B_stream
insert into rule_D_stream select * where condition3
insert into rule_E_stream select * where condition4;
on rule_E_stream
insert into rule_F_stream select * where condition4
insert into rule_G_stream select * where condition5;
How can we terminate Event processing immediately once rule_E_stream is reached and return the results? (termination means stopping event propagation so no following statements should not be invoked)
Is it possible to stop processing on Subscriber/Listener side?
Considering using context with “terminated by” Event:
create context Ctx initiated by InitEvent terminated by TerminateEvent
I wonder is it applicable in our case?
The #Drop annotation (aka. prioritized execution) terminates. An example would be:
#Drop #Priority(1) select * from rule_E_stream(drop_conditions_here_if_any)
#Priority(0) on rule_E_Stream ....
Listeners don't stop things in Esper in general. But listeners can reinsert (aka. route) events as a result of their own filter or transformation they may do.
I have a question about using the output clause in combination with a named window, patterns and the insert into statement.
My goal is to detect the absence of an event, store it in a named window and when the events start coming again select and delete the row and use that as an "online" indicator (see Esper - detect event after absence)
I somehow want to be able limit the rate of events when there are multiple offline - online events in a short period of time (disable false positives). I thought the output clause could help here but when I use that on the insert into statement no events are stored in the named window. Is this the right approach or is there an other way to limit the events in this scenario?
This is my code in Esper EPL online:
create schema MonitorStats(id string, time string, host string, alert string);
create window MonitorWindow.win:keepall() as select id, alert, time, host from MonitorStats;
insert into MonitorWindow select a.id as id, 'offline' as alert, a.time as time, a.host as host from pattern
[every a=MonitorStats(id='1234') -> (timer:interval(25 sec) and not MonitorStats(id=a.id))];
on pattern[every b=MonitorStats(id='1234') -> (timer:interval(25 sec) and MonitorStats(id=b.id))]
select and delete b.id as id, 'online' as alert, b.time as time, b.host as host from MonitorWindow as win
where win.id = b.id;
You may insert output events into another stream and use "output first every".
insert into DetectedStream select ....;
select * from DetectedStream output first every 10 seconds;
The problem is pretty simple: extract only the not exists records from 2 different streams using Esper engine.
ID exists in streamA but NOT EXITS in streamB.
In SQL it would look like this:
SELECT *
FROM tableA
WHERE NOT EXISTS (SELECT *
FROM tableB
WHERE tableA.Id = tableB.Id)
I've tried it Esper style but it doesn't work:
SELECT *
FROM streamA.win:ext_timed(timestamp, 5 seconds) as stream_A
WHERE NOT EXSITS
(SELECT stream_B.Id
FROM streamB.win:ext_timed(timestamp, 5 seconds) as stream_B
WHERE stream_A.Id = stream_B.Id)
Sadly if stream_A.Id inserted before stream_B.id than it will answer the query conditions and the query won't work.
Any suggestions on how to identify "ID exists in streamA but NOT EXITS in streamB" using Esper?
One simple way is to time-order the stream, so that A and B are timestamp ordered before sending events in.
Or you could delay A such as this query:
select * from pattern [every a=streamA -> timer:interval(1 sec)] as delayed_a
where not exists (... where delayed_a.a.id = b.id)
There is no need for an externally timed window for streamA. For externally timed behavior in general use external timer events.