topic Re: Incremental load in App Development

Incremental load

ka51 — Tue, 28 Apr 2026 14:08:56 GMT

Hi Team,

Need a help here, this might be a simple question .

I am doing an incremental load of 270 million records which is for duration of 3months. While concatenating the new data with history Qvd it is taking more time to load as history Qvd is having more data.

Is there any solution where i should not be loading again the history Qvd, only can concatenate to the new data.

Would be grateful if any ideas can be posted here.

Re: Incremental load

Eduardo_Monteiro — Tue, 28 Apr 2026 14:16:15 GMT

Hi @ka51

What about separating .qvd per period?

Regards,

Re: Incremental load

vighnesh_gawad — Tue, 28 Apr 2026 14:34:04 GMT

While concatenating these two QVDs, are you applying any transformations? If yes, that’s likely why it’s taking more time.

You can reduce the load time by loading the history QVD in optimised mode and avoiding any transformations during concatenation.

Re: Incremental load

ka51 — Tue, 28 Apr 2026 16:48:24 GMT

As we are maintaining rolling 3 months of historical data ,hence applying a filter for the same while concatenating.

Re: Incremental load

marcus_sommer — Wed, 29 Apr 2026 12:15:08 GMT

Take a more careful look on the above suggestions. Loading qvd-data optimized (no transformations unless a single where exists(OnlyWithOneParameter); is really fast (the kind of filtering matters).

In addition and/or as an alternative the historical data could be sliced and the slice-information be included within the file-name. Afterwards this file-information could be read before the data are touched, for example:

for each file in filelist('path/*.qvd')
if subfield(subfield('$(file)', '.', 1), '_', -1) >= MyPeriodInformation then
t: load ...;
end if
next

Re: Incremental load

rwunderlich — Wed, 29 Apr 2026 20:48:01 GMT

As others have suggested you may not have an optimized load in your concatenate. If you post the script we may have some suggestions. Here are some general ideas to maintain the optimized load.

Load the history QVD first with a Where Exists(trandate) pattern to roll off old data. Then concatenate the updated rows to this resident table. https://qlikviewcookbook.com/2026/02/optimized-load-script-patterns/

If the history QVD is just too large here are some script patterns for segmenting your QVD. https://qlikviewcookbook.com/2022/03/how-to-segment-qvd-files/

-Rob

Re: Incremental load

ka51 — Thu, 30 Apr 2026 04:59:18 GMT

Sure, will have a look. Also will try to paste the code here.

Re: Incremental load

RafaelBarrios — Sat, 02 May 2026 09:26:24 GMT

Hi @ka51

i would suggest using partial reload instead of incremental

In a standard reload, the app first flushes all data and starts as if it had no data, while in a partial reload keeps the data and only executes specific parts of the script. This way you dont need to load old qvd, just load new data and "add" or "merge".

https://help.qlik.com/en-US/sense/November2025/Subsystems/Hub/Content/Sense_Hub/Scripting/ScriptPrefixes/PartialReload.htm

here an example to only "add" data to an existing table

Tab1: LOAD Name, Number FROM Persons.csv; Add Only LOAD Name, Number FROM newPersons.csv;

on your full load you will get all records in Persons.csv, and the partial reload will concatenate NewPersons.csv to existing table

Here an example to merge

Set DateFormat='D/M/YYYY'; Persons: load * inline [ Name, Number Jake, 3 Jill, 2 Steven, 3 ]; Merge only (ChangeDate, LastChangeDate) on Name Concatenate(Persons) LOAD * inline [ Operation, ChangeDate, Name, Number Insert, 1/1/2021, Mary, 4 Delete, 1/1/2021, Steven, Update, 2/1/2021, Jake, 5 ];

After standard reload you will get

After partial reload you will get

good thing about merge is that it will take care of NEW, UPDATE and DELETE

also, if your standard reload takes 20 minutes, you could get several partial reloads during the days with less than a minute each.

hope this helps.
Best,

help users find answers! Don't forget to mark a solution that worked for you & to smash the like button!

Re: Incremental load

ka51 — Sat, 02 May 2026 14:02:49 GMT

Ohh this is great ! Even i was looking for partial reload . But is there any drawbacks of partial reload?

Also is it advisable to go for Add load instead of Merge. I can see the output is different in case of standard reload and partial reload.

Re: Incremental load

RafaelBarrios — Sat, 02 May 2026 15:17:17 GMT

Hi @ka51

drawbacks ? i dont see any, im using it for "near real time" application and works perfect, but it will depend on what are you trying to achive.

if you are only adding new record and not updating or deleting, you can go with "add" statement

if you are going to receive updates or deletion, i would suggest use to use "merge"

note that:

"add load * from...." will work on standard and partial reload "add only load * from...." will work only when partial reload happens

now the difference in the output is because of what i just commented

lets say you trigger a full standard reload in the morning, then only this part will be excute, while the task will ignore "merge only" because of the "only" statement

Set DateFormat='D/M/YYYY'; Persons: load * inline [ Name, Number Jake, 3 Jill, 2 Steven, 3 ];

now, the rest of day you can trigger partial reload to grab the data that changes during the day, partial reload will ignore all load statements that doesnt has "add|replace|merge".

in this example, it will create a new record "Mary", update "Jake" record from 3 to 4, and delete "Steven" record.

Merge only (ChangeDate, LastChangeDate) on Name Concatenate(Persons) LOAD * inline [ Operation, ChangeDate, Name, Number Insert, 1/1/2021, Mary, 4 Delete, 1/1/2021, Steven, Update, 2/1/2021, Jake, 5 ];

I hope I've explained myself well.
But if you have any questions, feel free to write.

Best regards,