I have a quite simple problem to modelize and I don't have experience in Esper, so I may be headed the wrong way so I'd like some insight.
Here's the scenario: I have one stream of events "ParkingEvent", with two types of events "SpotTaken" and "SpotFree". So I have an Esper context both partitioned by id and bordered by a starting event of type "SpotTaken" and an end event of type "SpotFree". The idea is to monitor a parking spot with a sensor and then aggregate data to count the number of times the spot has been taken and also the time occupation.
That's it, no time window or whatsoever, so it seems quite simple but I struggle aggregating data. Here's the code I got so far:
create context ParkingSpotOccupation
context PartionBySource
partition by source from SmartParkingEvent,
context ContextBorders
initiated by SmartParkingEvent(
type = "SpotTaken") as startEvent
terminated by SmartParkingEvent(
type = "SpotFree") as endEvent;
#Name("measurement_occupation")
context ParkingSpotOccupation
insert into CreateMeasurement
select
e.source as source,
"ParkingSpotOccupation" as type,
{
"startDate", min(e.time),
"endDate", max(e.time),
"duration", dateDifferenceInSec(max(e.time), min(e.time))
} as fragments
from
SmartParkingEvent e
output
snapshot when terminated;
I got the same data for min and max so I'm guessing I'm doing somthing wrong.
When I'm using context.ContextBorders.startEvent.time and context.ContextBorders.endEvent.time instead of min and max, the measurement_occupation statement is not triggered.
Given that measurements have already been computed by the EPL that you provided, this counts the number of times the spot has been taken (and freed) and totals up the duration:
select source, count(*), sum(duration) from CreateMeasurement group by source
Related
I have a series, disk, that contains a path (/mnt/disk1, /mnt/disk2, etc) and total space of a disk. It also includes free and used values. These values are updated at a specified interval. What I would like to do, is query to get the sum of the total of the last() of each path. I would also like to do the same for free and for used, to get a aggregate of the total size, free space, and used space of all of my disks on my server.
I have a query here that will get me the last(total) of all the disks, grouped by its path (for distinction):
select last(total) as total from disk where path =~ /(mnt\/disk).*/ group by path
Currently, this returns 5 series, each containing 1 row (the latest) and the value of its total. I then want to take the sum of those series, but I cannot just wrap the last(total) into a sum() function call. Is there a way to do this that I am missing?
Carrying on from my comment above about nested functions.
Building a toy example:
CREATE DATABASE FOO
USE FOO
Assuming your data is updated at intervals greater than[1] every minute:
CREATE CONTINUOUS QUERY disk_sum_total ON FOO
BEGIN
SELECT sum("total") AS "total_1m" INTO disk_1m_total FROM "disk"
GROUP BY time(1m)
END
Then push some values in:
INSERT disk,path="/mnt/disk1" total=30
INSERT disk,path="/mnt/disk2" total=32
INSERT disk,path="/mnt/disk3" total=33
And wait more than a minute. Then:
INSERT disk,path="/mnt/disk1" total=41
INSERT disk,path="/mnt/disk2" total=42
INSERT disk,path="/mnt/disk3" total=43
And wait a minute+ again. Then:
SELECT * FROM disk_1m_total
name: disk_1m_total
-------------------
time total_1m
1476015300000000000 95
1476015420000000000 126
The two values are 30+32+33=95 and 41+42+43=126.
From there, it's trivial to query:
SELECT last(total_1m) FROM disk_1m_total
name: disk_1m_total
-------------------
time last
1476015420000000000 126
Hope that helps.
[1] Picking intervals smaller than the update frequency prevents minor timing jitters from making all the data being accidentally summed twice for a given group. There might be some "zero update" intervals, but no "double counting" intervals. I typically run the query twice as fast as the updates. If the CQ sees no data for a window, there will be no CQ performed for that window, so last() will still give the correct answer. For example, I left the CQ running overnight and pushed no new data in: last(total_1m) gives the same answer, not zero for "no new data".
I am looking for an EPL statement which fires an event each time a certain value has increased by a specified amount, with any number of events in between, for example:
Considering a stream, which continuously provides new prices.
I want to get a notification, e.g. if the price is greater than the first price + 100. Something like
select * from pattern[a=StockTick -> every b=StockTick(b.price>=a.price+100)];
But how to realize that I get the next event(s), if the increase is >= 200, >=300 and so forth?
Diverse tests with context and windows has not been successful so far, so I appreciate any help! Thanks!
The contexts would be the right way to go.
You could start by defining a start event like this:
create schema StartEvent(threshold int);
And then have context that uses the start event:
create context ThresholdContext inititiated by StartEvent as se
terminated after 5 years
context ThresholdContext select * from pattern[a=StockTick -> every b=StockTick(b.price>=context.se.threshold)];
You can generate the StartEvent using "insert into" from the same pattern (probably want to remove the "every") or have the listener send in a StartEvent or declare another pattern that fires just once for creating a StartEvent.
I have a basic Esper query as follows:
#Name("MyTestQuery")
#Description("My First Test Query")
select sum(qty), venue
from MyTestWindow
group by venue
The query seems to duplicate the results of my sum i.e. if I send in a qty of 10 my query will fire multiple times and output:
10, 20, 30, 40
However, if I remove the group by function then it just outputs 10.
Is anyone able to advise why this might happen?
Typically you need to qualify the Stream name (MyTestWindow) with a window, so it is
"from MyTestWindow.win:time(1 sec) ". You need to select an appropriate window type from many Epser offers, depending on your application.
This example:
select sum(qty), venue
from MyTestWindow.win:time_batch(1 sec)
group by venue
having sum(qty) is not null
You can run a simple test of this at http://esper-epl-tryout.appspot.com/epltryout/mainform.html
the best way of doing a group by is to trigger an artificial "event" after sending in all events. this way you can fully control what you want you want to output and not let Esper's engine run in real time.
You might have to use the "distinct" feature in select to avoid duplicates. Esper can sometimes create duplicate events when you aren't using trigger variables, so distinct will allow you to get rid of unwanted events.
You can use win:time_batch to specified time interval in one update and coalesce function to handle the null value
select venue, sum(coalesce(ty, 0))
from MyTestWindow.win:time_batch(1 sec)
group by venue
I am trying to raise an event when the average value of a field is over a threshold for a minute. I have the object defined as:
class Heartbeat
{
public string Name;
public int Heartbeat;
}
My condition is defined as
select avg(Heartbeat) , Name
from Heartbeat.std:groupwin(Name).win:time(60 sec)
having avg(Heartbeat) > 100
However, the event never gets fired despite the fact that I fire a number of events with the Heartbeat value over 100. Any suggestions on what I have done wrong?
Thanks in advance
It confuses many people, but since time is the same for all groups you can simplify the query and remove the groupwin. The documentation note in this section explains why: http://esper.codehaus.org/esper-4.11.0/doc/reference/en-US/html_single/index.html#view-std-groupwin
The semantics with or without groupwin are the same.
I think you want group-by (and not groupwin) since group-by controls the aggregation level and groupwin controls the data window level.
New query:
select avg(Heartbeat) , Name from Heartbeat.win:time(60 sec) group by Name having avg(Heartbeat) > 100
I have a non real time Esper configuration where I feed a stream that I read from a file. I'm trying to create an expression that computes a statistic over the entire stream and outputs one value at the very end. Esper has semantics for forcing a view to output every X seconds, for instance, but is there a semantic for asking the view or the engine to "flush" the output when you know there are no more events to feed.
Turns out that at least one way to do this is to use the output clause with a variable trigger.
The expression would be:
select count(*) as totalCount from events output last when OutputSummary = true
The OutputSummary variable would be initialized like so:
epConfiguration.addVariable("OutputSummary", Boolean.class, "false");
When you're ready to flush, set the variable to true like so:
epRuntime.setVariableValue("OutputSummary", true);
long currentTime = epService.getEPRuntime().getCurrentTime();
epRuntime.sendEvent(new CurrentTimeEvent(currentTime));
It's necessary to send another time event to force the expression to evaluate.
When output requires at every 60 sec then the expression would be:
select emplyee_id from employees output snapshot every 60 sec
and when the output requires at every 10000 events then the expression would be:
select emplyee_id from employees output snapshot every 10000 events