Hi All,

I want to Share my Qliksense App to the Another  Machine.

But the thing is I don want others to see the source code which I have written in the Script. I just want them to use the UI/charts/table which I used in the App.

How can I do this?

Hi, I am desperately trying to fight my way through creating a new dashboard and have come across a show stopping problem which, after 3 or 4 days of searching, I just cannot find any help on.  I am successfully importing data from Excel files, which are stored in a folder on my hard disk by dragging and dropping them in the data load screen, however I cannot point the script to these files.  I want to be in the situation where I can save new source data, overwriting the existing files, and then simply click "reload" in the dashboard, and see the new data.  Can anyone please advise what I am missing, and obviously what extra information you need.
I am using a qliksense cloud based dashboard as I think I can do this in the desktop, but keep receiving warnings the desktop version is ceasing to be used.
Many Thanks in advance, Paul

I am replicating from Oracle 11g to Azure SQL DB (using redo logs). I have only just set this up within the last few days, but I have noticed very big gaps in the delay of processing. i.e. I can see changes in my source DB, but they aren't being picked up by Replicate for sometimes 1 hour or more.

I am getting many of the below errors in my task log. My source is Oracle 11g and target is Azure SQL DB. The updates do indeed get applied, but I would prefer they are done in bulk (much faster)

00003336: 2020-02-20T13:48:35 [TARGET_APPLY ]I: Bulk apply operation failed. Trying to execute bulk statements in 'one-by-one' mode (bulk_apply.c:2312)
00003336: 2020-02-20T13:48:35 [TARGET_APPLY ]I: Applying UPDATES one-by-one for table '<tablename>' (56) (bulk_apply.c:4810)
00003336: 2020-02-20T13:48:35 [TARGET_APPLY ]I: Switch back to bulk apply mode (bulk_apply.c:4907)

I want to Resident Load the [Assessment] table to the [Limited Assessment] table while restricting every record in the [Limiter] table. The [Limiter] table is an excel workbook that looks like this but with many more records. Can you help?

[Assessment] :
Identifier,
Inches
FROM [lib://Capacity/Sheet1.xlsx

[Limit Assessment] :
Identifier,
Inches
RESIDENT [Assessment] ;
DROP TABLE [Assessment] ;

Hello All,

We are trying to install the qlik sense Feb 2019 through the userdata of EC2 instances in AWS. We are passing required service/domain users to the exe and it is failing to validate the service user.

To be clear, when we run this using userdata, it will be executed via system admin user. And the error comes is below,

[11EC:1348][2019-04-04T09:50:10]i000: PREREQUISITE CHECK: Service user validation failed.

[11EC:1348][2019-04-04T09:50:10]i000: PREREQUISITE CHECK: Qlik Sense cannot be installed as Local System.
[11EC:1348][2019-04-04T09:50:10]i000: About to quit this session (with exit code -1000).

Is there anyway to install differently in the userdata in AWS EC2?

Thanks,

Karthick

I have multiple CSV files with slightly different columns that I wish to concatenate load into a single table. Each file contains approximately 120 columns.

Unfortunately, the source files also contain multiple "Filler" columns (header = "Filler").

So, this fails:

[SDE]:
Load * Inline [
SDE
];

// This method won't work, because the file is littered with "Filler" columns (field names must be unique)

For Each File in Filelist('$(vPath)/$(vFileMask)')

SET vFile = '$(File)';

Concatenate
LOAD *
FROM [$(vFile)]
(txt, codepage is 28591, embedded labels, delimiter is ',');

Next File;

Is there a way to dynamically load multiple files, but exclude (or dynamically rename) columns named "Filler"?

Thank you!

Hi all, long time reader, first time poster.

I have a straight table that contains unique calculated expressions and headings in each column.I want to reference the output of these columns into a mini chart as a sparkline.

An example of the data can be seen below:

Any ideas on how I can do this?

Many thanks.