I have a query (relationship between CONTRACT <-> ORDERS) that I decided to break up into 2 parts (contract and orders) so I can reuse in another stored procedure.
When I run the code before the break up, it took around 10 secs to run; however, when I use a function for getting the contract, then pump the data into a temp table first, then join to the other parts it takes 2m:30s - why the difference in time?
The function takes less than a second to run and returns only one row i.e. details of one contract (contract_id is the parameter supplied to the function).
The part that is most effecting the performance the (ORDERS) largest table in the query has 4.1 million rows and joins to a few other tables however; if I just run the sub query for orders in isolation with a particular filter i.e. the contract id it takes less than a second to run and just happens to return zero records based for the contract I am testing on (due to filtering on the type of order it is looking for).
Base on the above information you would think 1 sec at most for the function + 1 sec at most to get the orders + summarize = 2 seconds at most, not 2 and half minutes!
Where am I going wrong, how do I begin to isolate the issue in time difference?
I know someone is going to tell me to paste the code but surely it is an issue of the database vs indexes perhaps vs how the compiler performs when dealing with raw code versus broken up code into parts. Is there an area of the code I can look at before having to post my whole code as I have tried variations of OUTER APPLY vs LEFT JOIN from the contract temp table to the orders subquery and both give me about the same result. Any ideas?
I don't think the issue was with the code but the network I was running it on. Although bizarre in the fact I had 2 versions of the proc running side by side and yesterday or rather before the weekend one was running in 10 secs and it is still running in 10 secs 3 days later and my new version (using the function) was taking anywhere between 2 to 3 minutes. This morning it is running at 2 or 3 seconds!! So I don't know if it is the fact I changed from declaring my table structure and using a table variable instead first to where previously I was using SELECT ... INTO #Contract made the difference or the network or precompiling has an affect. Whatever it is it no longer an issue. Should I delete this post?
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i am struggling with my dashboard performance which runs queries on Redshift using JDBC driver.
the query is like -
select <ALIAS_TO_SCHEMA.TABLENAME>.<ANOTHER_COLUMN_NAME> as col_0_0_,
sum(<ALIAS_TO_SCHEMA.TABLENAME>.devicecount) as col_1_0_ from <table_schema>.<table_name> <ALIAS_TO_SCHEMA.TABLENAME> where <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$1
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$2
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$3
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$4
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$5
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$6
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$7
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$8
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$9
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$10
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$11
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$12
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$13
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$14
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$15
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$16
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$17
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$18
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$19
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$20
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$21
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$22
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$23
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$24
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$25
or <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME>=$26
or ........
The For dashboard we use Spring, Hibernate ( I am not 100% sure about it though ).
But the query might sometimes stretch till $1000 + according to the filters/options being selected on the UI.
But the problem we are seeing is - The First Time this query is being run by the reports, it takes more than 40 sec - 60 seconds for the response. After the first time , the query runs quite fast and takes only few seconds to run.
We initially suspected there must be something wrong with redshift caching , but it turns out that , Even simple queries like these ( But Huge ) takes considerable time to COMPILE, which is clear when we look into the svl_compile table which shows this query was compiled in over 35 seconds.
What should I do to handle such issues ?
Recommend restructuring the query generated by your dashboard to use an IN list. Redshift should be able to reuse the already compiled query segments for different length IN lists.
Note that IN lists with less than 10 values will still be evaluated as OR. https://docs.aws.amazon.com/redshift/latest/dg/r_in_condition.html#r_in_condition-optimization-for-large-in-lists
SELECT <ALIAS_TO_SCHEMA.TABLENAME>.<ANOTHER_COLUMN_NAME> as col_0_0_
, SUM(<ALIAS_TO_SCHEMA.TABLENAME>.devicecount) AS col_1_0_
FROM <table_schema>.<table_name> <ALIAS_TO_SCHEMA.TABLENAME>
WHERE <ALIAS_TO_SCHEMA.TABLENAME>.<COLUMN_NAME> IN ( $1,$2,$3,$4,$5,$6,$7,$8,$9,$10,$11 … $1000 )
;
I will try to explain the problem on an abstract level first:
I have X amount of data as input, which is always going to have a field DATE. Before, the dates that came as input (after some process) where put in a table as output. Now, I am asked to put both the input dates and any date between the minimun date received and one year from that moment. If there was originally no input for some day between this two dates, all fields must come with 0, or equivalent.
Example. I have two inputs. One with '18/03/2017' and other with '18/03/2018'. I now need to create output data for all the missing dates between '18/03/2017' and '18/04/2017'. So, output '19/03/2017' with every field to 0, and the same for the 20th and 21st and so on.
I know to do this programmatically, but on powercenter I do not. I've been told to do the following (which I have done, but I would like to know of a better method):
Get the minimun date, day0. Then, with an aggregator, create 365 fields, each has that "day0"+1, day0+2, and so on, to create an artificial year.
After that we do several transformations like sorting the dates, union between them, to get the data ready for a joiner. The idea of the joiner is to do an Full Outer Join between the original data, and the data that is going to have all fields to 0 and that we got from the previous aggregator.
Then a router picks with one of its groups the data that had actual dates (and fields without nulls) and other group where all fields are null, and then said fields are given a 0 to finally be written to a table.
I am wondering how can this be achieved by, for starters, removing the need to add 365 days to a date. If I were to do this same process for 10 years intead of one, the task gets ridicolous really quick.
I was wondering about an XOR type of operation, or some other function that would cut the number of steps that need to be done for what I (maybe wrongly) feel is a simple task. Currently I now need 5 steps just to know which dates are missing between two dates, a minimun and one year from that point.
I have tried to be as clear as posible but if I failed at any point please let me know!
Im not sure what the aggregator is supposed to do?
The same with the 'full outer' join? A normal join on a constant port is fine :) c
Can you calculate the needed number of 'dublicates' before the 'joiner'? In that case a lookup configured to return 'all rows' and a less-than-or-equal predicate can help make the mapping much more readable.
In any case You will need a helper table (or file) with a sequence of numbers between 1 and the number of potential dublicates (or more)
I use our time-dimension in the warehouse, which have one row per day from 1753-01-01 and 200000 next days, and a primary integer column with values from 1 and up ...
You've identified you know how to do this programmatically and to be fair this problem is more suited to that sort of solution... but that doesn't exclude powercenter by any means, just feed the 2 dates into a java transformation, apply some code to produce all dates between them and for a record to be output for each. Java transformation is ideal for record generation
You've identified you know how to do this programmatically and to be fair this problem is more suited to that sort of solution... but that doesn't exclude powercenter by any means, just feed the 2 dates into a java transformation, apply some code to produce all dates between them and for a record to be output for each. Java transformation is ideal for record generation
Ok... so you could override your source qualifier to achieve this in the selection query itself (am giving Oracle based example as its what I'm used to and I'm assuming your data in is from a table). I looked up the connect syntax here
SQL to generate a list of numbers from 1 to 100
SELECT (MIN(tablea.DATEFIELD) + levquery.n - 1) AS Port1 FROM tablea, (SELECT LEVEL n FROM DUAL CONNECT BY LEVEL <= 365) as levquery
(Check if the query works for you - haven't access to pc to test it at the minute)
I want to grab data from a KDB data base for a list of roughly 200 days within the last two years. The 200 days are in no particular pattern.
I only need the data from 09:29:00.000 to 09:31:00.000 everyday.
My first approach was to query all of the last two years data that have time stamp between 09:29:00.000 and 09:31:00.000, because I didn't see a way to just query the particular 200 days that I need.
However this proved to be too much for my server to handle.
Then I tried to summarize the 2 minute data for each date into an average and just print out the average, so now I will only have 200 rows of data as output. But somehow this still turns out to be too much. I'm not sure if this is because I'm not selecting the data correctly.
My other suspicion is that the query is garbing all the data first then averaging each date, which means averaging is not making it easier to handle.
Here's the code that I have:
select maxPriceB:max(price), minPriceB:min(price), avgPriceB:avg(price), avgSizeB:avg(qty) by date from dms where date within(2015.01.01, 2016.06,10), time within(09:29:00.000, 09:31:00.000), sym = `ZF6
poms is the table that the data is in
ZFU6 is the symbol that im looking for
I tried adding the key word distinct after select.
I want to know if there's anyway to break up the query, or make the query lighter for the server to handle.
Thank you!
If you use 32-bit kdb+ and get infamous 'wsfull error then you may try processing one day at a time like this:
raze{select maxPriceB:max(price), minPriceB:min(price), avgPriceB:avg(price), avgSizeB:avg(qty)
from dms where date=x,sym=`ZF6,time within 09:29:00.000 09:31:00.000}each 2015.01.01+1+til 2016.06.10-2015.01.01
Tough problem I am working on here.
I have a table of CustomerIDs and CallDates. I want to measure whether there is a 'repeat call' within a certain period of time (up to 30 days).
I plan on creating a parameter called RepeatTime which is a range from 0 - 30 days, so the user can slide a scale to see the number/percentage of total repeats.
In Excel, I have this working. I sort CustomerID in order and then sort CallDate from earliest to latest. I then have formulas like:
=IF(AND(CurrentCustomerID = FutureCustomerID, FutureCallDate - CurrentCallDate <= RepeatTime), 1,0)
CurrentCustomerID = the current row, and the FutureCustomerID = the following row (so it is saying if the customer ID is the same).
FutureCallDate = the following row and the CurrentCallDate = the current row. It is subtracting the future call time from the first call time to measure the time in between.
The goal is to be able to see, dynamically, how many customers called in for a specific reason within maybe 4 hours or 1 day or 5 days, etc. All of the way up until 30 days (this is our actual metric but it is good to see the calls which are repeats within a shorter time frame so we can investigate).
I had a similar problem, see here for detailed version Array calculation in Tableau, maxif routine
In your case, that is basically the same thing as mine, so you could apply that solution, but I find it easier to understand the one I'm about to give, I would do:
1) Create a calculated field called RepeatTime:
DATEDIFF('day',MAX(CallDates),LOOKUP(MAX(CallDates),-1))
This will calculated how many days have passed since the last call to the current. You can add a IFNULL not to get Null values for the first entry.
2) Drag CustomersID, CallDates and RepeatTime to the worksheet (can be on the marks tab, don't need to be on rows or column).
3) Configure the table calculation of RepeatTIme, Compute using Advanced..., partitioning CustomersID, Adressing CallDates
Also Sort by Field CallDates, Maximum, Ascending.
This will guarantee the table calculation works properly
4) Now you have a base that you can use for what you need. You can either export it to csv or mdb and connect to it.
The best approach, actually, is to have this RepeatTime field calculated outside Tableau, on your database, so it's already there when you connect to it. But this is a way to use Tableau to do the calculation for you.
Unfortunately there's no direct way to do this directly with your database.
Hi all I've got an interesting task to update a single column in a table that has roughly 2 million rows. I've tried doing this using MVC Entity Framework, however I'm encountering "Out of memory exceptions" and I'm just wondering if there's another way.
The interesting part is that its not just a simple update. The procedure needs to read the TelephoneNumber column already in the table and this could be 014812001 for example. Then it needs to calculate a score for this number based on the number of occurrences greater than 1. So for example using the above number this would score a 6 as we have 3 x 1's and 3 x 0's giving a total of 6.
Once this score has been calculated this number needs to be inserted into the a column in the current row be processed, so in our case the row with the TelephoneNumber = 014812001.
Is this possible using TSQL or is it better to carry on with my Entity Framework approach?
For such a bulk update, I would always recommend doing this on the server itself - there's really no point in dragging down 2 million rows, updating a single column, and then pushing those back to the server again.....
I think based on your description, it should be fairly simple to create a little T-SQL user defined function that would calculate this score. Once you have that, you can issue a single T-SQL statement:
UPDATE dbo.YourTable
SET Score = dbo.fnCalculateScore(TelephoneNumber)
WHERE .... (whatever condition you might have) .....
That should be faster by several orders of magnitude than with your Entity Framework approach....