I have an Esper query that returns multiple rows, but I'd like to instead get one row, where that row has a list (or concatenated string) of all of the values from the (corresponding columns of the) matching rows that my current query returns.
For example:
SELECT Name, avg(latency) as avgLatency
FROM MyStream.win:time(5 min)
GROUP BY Name
HAVING avgLatency / 1000 > 60
OUTPUT last every 5 min
Returns:
Name avgLatency
---- ----------
A 65
B 70
C 75
What I'd really like:
Name
----
{A, B, C}
Is this possible to do via the query itself? I tried to make this work using subqueries, but I'm not working with multiple streams. I can't find any aggregation functions or enumeration functions in the Esper documentation that fits what I'm trying to do either.
Thanks to anybody that has any insight or direction for me here.
EDIT:
If this can't be done via the query, I'm open to changing the subscriber, or anything else, if necessary.
You can have a subscriber or listener do the concat. There is a "Multi-Row Delivery" for subscribers. Or use a table like below.
// create table to hold aggregation result
create table LatencyTable(name string primary key, avgLatency avg(double));
// update aggregations in table from events coming in
into LatencyTable select name, avg(latency) as avgLatency from MyStream#time(5 min) group by name;
// do a select with the "aggregate" enumeration method
select (select * from LatencyTable where avgLatency > x).aggregate(....) from pattern[every timer:interval(5 min)]
How to get data from measurement by group by column_name and max time?
Here is query I am trying to execute
select cpu_number from vm_details where ro_id='8564a08b-9208-45bf-9758-7d64fe1f91a3' group by entity_uuid;
SELECT mt.*,
FROM MyTable mt INNER JOIN
(
SELECT ID, MIN(Record_Date) MinDate
FROM MyTable
GROUP BY ID
) t ON mt.ID = t.ID AND mt.Record_Date = t.MinDate
This gets the minimum date per ID, and then gets the values based on those values. The only time you would have duplicates is if there are duplicate minimum record_dates for the same ID.
Let's consider a simple object with the same representation in a SQL database with properties(columns¨): Id, UserId,Ip.
I would like to prepare a query that would generate event in case that one user logs in from 2 IP adresses (or more) within 1 hour period.
My SQL looks like:
SELECT id,user_id,ip FROM w_log log
LEFT JOIN
(SELECT user_id, count(distinct ip) AS ip_count FROM w_log GROUP BY user_id) ips
ON log.user_id = ips.user_id
WHERE ips.ip_count > 1
Transformation to EPL:
SELECT * FROM LogEntry.win:time(1 hour) logs LEFT INNER join
(select UserId,count(distinct Ip) as IpCount FROM LogEntry.win:time(1 hour)) ips
ON logs.UserId = ips.UserId where ips.IpCount>1
Exception:
Additional information: Incorrect syntax near '(' at line 1 column 100,
please check the outer join within the from clause near reserved keyword 'select'
UPDATE:
I was successfuly able to create a schema, named window and insert data into it (or update it). I would like to increase the counter when a new LogEvent arrives in the .win:time(10 seconds) and decrease it when the event is leaving the 10 seconds window. Unfortunately the istream() doesn't seem to provide the true/false when the event is in remove stream.
create schema IpCountRec as (ip string, hitCount int)
create window IpCountWindow.win:time(10 seconds) as IpCountRec
on LogEvent.win:time(10 seconds) log
merge IpCountWindow ipc
where ipc.ip = log.ip
when matched and istream()
then update set hitCount = hitCount + 1
when matched and not istream()
then update set hitCount = hitCount - 1
when not matched
then insert select ip, 1 as hitCount
Is there something I missed?
In EPL I don't think it is possible to put a query into the from-part. You can change using "insert into". An EPL alternative is also a named window or table.
I have two tables in hive:
Table1: uid,txid,amt,vendor Table2: uid,txid
Now I need to join the tables on txid which basically confirms a transaction is finally recorded. There will be some transactions which will be present only in Table1 and not in Table2.
I need to find out number of avg of transaction matches found per user(uid) per vendor. Then I need to find the avg of these averages by adding all the averages and divide them by the number of unique users per vendor.
Let's say I have the data:
Table1:
u1,120,44,vend1
u1,199,33,vend1
u1,100,23,vend1
u1,101,24,vend1
u2,200,34,vend1
u2,202,32,vend2
Table2:
u1,100
u1,101
u2,200
u2,202
Example For vendor vend1:
u1-> Avg transaction find rate = 2(matches found in both Tables,Table1 and Table2)/4(total occurrence in Table1) =0.5
u2 -> Avg transaction find rate = 1/1 = 1
Avg of avgs = 0.5+1(sum of avgs)/2(total unique users) = 0.75
Required output:
vend1,0.75
vend2,1
I can't seem to find count of both matches and occurrence in just Table1 in one hive query per user per vendor. I have reached to this query and can't find how to change it further.
SELECT A.vendor,A.uid,count(*) as totalmatchesperuser FROM Table1 A JOIN Table2 B ON A.uid = B.uid AND B.txid =A.txid group by vendor,A.uid
Any help would be great.
I think you are running into trouble with your JOIN. When you JOIN by txid and uid, you are losing the total number of uid's per group. If I were you I would assign a column of 1's to table2 and name the column something like success or transaction and do a LEFT OUTER JOIN. Then in your new table you will have a column with the number 1 in it if there was a completed transaction and NULL otherwise. You can then do a case statement to convert these NULLs to 0
Query:
select vendor
,(SUM(avg_uid) / COUNT(uid)) as avg_of_avgs
from (
select vendor
,uid
,AVG(complete) as avg_uid
from (
select uid
,txid
,amt
,vendor
,case when success is null then 0
else success
end as complete
from (
select A.*
,B.success
from table1 as A
LEFT OUTER JOIN table2 as B
ON B.txid = A.txid
) x
) y
group by vendor, uid
) z
group by vendor
Output:
vend1 0.75
vend2 1.0
B.success in line 17 is the column of 1's that I put int table2 before the JOIN. If you are curious about case statements in Hive you can find them here
Amazing and precise answer by GoBrewers14!! Thank you so much. I was looking at it from a wrong perspective.
I made little changes in the query to get things finally done.
I didn't need to add a "success" colummn to table2. I checked B.txid in the above query instead of B.success. B.txid will be null in case a match is not found and be some value if a match is found. That checks the success & failure conditions itself without adding a new column. And then I set NULL as 0 and !NULL as 1 in the part above it. Also I changed some variable names as hive was finding it ambiguous.
The final query looks like :
select vendr
,(SUM(avg_uid) / COUNT(usrid)) as avg_of_avgs
from (
select vendr
,usrid
,AVG(complete) as avg_uid
from (
select usrid
,txnid
,amnt
,vendr
,case when success is null then 0
else 1
end as complete
from (
select A.uid as usrid,A.vendor as vendr,A.amt as amnt,A.txid as txnid
,B.txid as success
from Table1 as A
LEFT OUTER JOIN Table2 as B
ON B.txid = A.txid
) x
) y
group by vendr, usrid
) z
group by vendr;
i have this code to get the position of each record:
Message.all.each_with_index do |msg, i|
message_order[msg.id] = i
end
But now i have 100k+ messages and it takes to long to iterate over all the records.
Can anyone tell me how to do this more performant? (I'm using oracle)
I thought about rownum but didn't come to a solution.
A solution which returns the position for just one message would be great.
I don't know if I have understood your problem.
If you need the message with a specified order id (for example: 5), you can execute something like:
SELECT message
FROM (SELECT message, ROWNUM AS ID
FROM (SELECT message
FROM tab1
ORDER BY some_date))
WHERE ID = 5;
Or, using analytical functions:
SELECT message
FROM (SELECT message,
ROW_NUMBER() OVER(ORDER BY some_date) AS ID
FROM tab1)
WHERE ID = 5;
This should work:
Message.where("id < :id", id: msg.id).count