Alteryx Designer Desktop Ideas

it would be great if the formula tool could expand the intellisense to the select column box. For example, I could start typing in the select column box and it would widdle down the list of fields down.let's suppose I wanted to update field 79A, I could type in 7 and it might show something like 

7

17

27

37

70

71

79A

79B.

So if I typed in 79 then, it would further reduce it to 

79A

79B

And i could select 79A.

In the Gallery, the File Browse tool returns the file location on the server where the file was uploaded. This allows the file to then be read in as input to a workflow.

If you need the file path of the original file location, you have to add a Text Input for the user to manually add it.

In my case (#00293302), I used a chained app to populate a list box for the user to select the Sheet Names they would like to process through the application. Unfortunately, since I was not able to capture the original file location the application errored out. This is due to the second app using the file location on the server where the file was uploaded, which is provided by the first workflow. This file location (from the Browse tool) is a temporary file location, where inputs are immediately deleted after processing.

Want to test this out? Create an application where you Output the file path from a File Browse tool.

i know.....grrr, this doesn't match your original file location!

Thank you,

Mark

Hi there,

When you connect to a DB using a connection string or an alias - this shows up in the Workflow Dependancies in a way that is very useful to allow you to identify impacts if a DB is moved or migrated.

However - in 2023.1, if you use DCM then the database dependancies just show up as .\ which makes dependancy management much more difficult.

Please could you add the capability to view the DCM dependancies correctly in the dependancy window?

BTW - this workflow Dependancy Window would be a great place to build a simple process to move existing DB connections to a DCM connection!

CC: @wesley-siu @_PavelP 

Hello Alteryx Devs - 

When I got to write some scripting in the formula tool, my data stream properties should be the first to be suggested once a user starts typing a letter, not the last. 

uppercase(Ad -> gives me:

DateTimeAdd

FileAddPaths

PadLeft

PadRight

ReadRegistryString

[Address]

I think we would need a dedicated R macro to ascertain the chances anyone in is going to need [ReadRegistryString] before they need a column of their own data that starts with [Ad...]

Easy fix.  Makes a big difference.  

Thanks.

I am running into unexpected functionality when utilizing the date interface tool in an Analytic App after upgrading to 21.3. Previously I was able to easily select dates in the past in the app interface by first selecting the Year, then the month, date, etc. After updating I am only able to see the prior and upcoming three months, which makes it difficult if you need to navigate back, say, 10 years. A ticket was put in they could not find when or why this change was made. This issue was brought up to our Designer SME group and they agreed that this isn't an improvement on the old design and is more cumbersome. They recommended posting to the Ideas page to bring back the old design.

Hello all,

From https://www.sqltutorial.org/sql-triggers/

Introduction to SQL Triggers

A trigger is a piece of code executed automatically in response to a specific event occurred on a table in the database.

A trigger is always associated with a particular table. If the table is deleted, all the associated triggers are also deleted automatically.

A trigger is invoked either before or after the following event:

• INSERT – when a new row is inserted
• UPDATE – when an existing row is updated
• DELETE – when a row is deleted.

When you issue an INSERT, UPDATE, or DELETE statement, the relational database management system (RDBMS) fires the corresponding trigger.

In some RDMBS, a trigger is also invoked in the result of executing a statement that calls the INSERT, UPDATE, or DELETE statement. For example, MySQL has the LOAD DATA INFILE, which reads rows from a text file and inserts into a table at a very high speed, invokes the BEFORE INSERT and AFTER INSERT triggers.

On the other hand, a statement may delete rows in a table but does not invoke the associated triggers. For example, TRUNCATE TABLE statement removes all rows in the table but does not invoke the BEFORE DELETE and AFTER DELETE triggers.



So basically, I would like to create some triggers from in db tools in Alteryx.

Best regards,

Simon

Tableau v2018.3 introduced multiple table extracts. These are particularly useful for fact table to fact table joins and fact table to entitlement table joins for row-level security where the number of rows created by the join and/or size of join results would be prohibitively large. Also they are useful for fact table to spatial joins where we might have multiple spatial objects (for example custom province/district/health facility catchment) for each row of fact table data.

So in Alteryx I'd like to be able to specify 2+ tables & their join keys and then write out a .hyper multiple tables extract.

Jonathan

Syntax Highlighting Idea:

Similar to the Formula Tool, allow the Multi-Field Formula tool (and other similar tools) to have Syntax Highlighting to allow user to easily determine if the formula being input doesn't have any errors.

Variable Autofill Idea:

Similar to the Formula Tool and how it provide a list of columns as you begin to type them, allow the Multi-Field Formula tool (and other similar tools) to have the ability to autofill variables such as [_CurrentField_] or [_CurentFiledName_] as you begin to type them.

I recently came to know that Alteryx doesn't support Denodo Data sources. We at our company are using Denodo as a data virtualization tool and also Alteryx is used for data blending. The request is for Alteryx to start supporting Denodo as a data source so that our company can reach out to Alteryx for any support related issues with Denodo.

Hello all,

When looking at the Results window, I often find it a headache to read the numeric results because of the lack of commas. I understand that incorporating commas into the data itself could make for some weird errors; however, would it be possible to toggle an option that displays all numeric fields with proper commas and right-aligned in the Results window? I am referring to using a display mask to make numeric fields look like they have the thousands separator while retaining numeric functionality (as opposed to converting the fields to strings). 

What do you think?

From Wikipedia

Druid is a column-oriented, open-source, distributed data store written in Java. Druid is designed to quickly ingest massive quantities of event data, and provide low-latency queries on top of the data.[1] The name Druid comes from the shapeshifting Druid class in many role-playing games, to reflect the fact that the architecture of the system can shift to solve different types of data problems.

Druid is commonly used in business intelligence/OLAP applications to analyze high volumes of real-time and historical data.[2] Druid is used in production by technology companies such as Alibaba,[2] Airbnb,[2] Cisco,[3] eBay,[4] Netflix,[5] Paypal,[2], Yahoo.[6] and Wikimedia Foundation [7] 

More and more companies are going from Hive to Druid for Dataviz needs, maybe it's time to look for Druid Integration with Alteryx?

I know this has been posted before, but the posts are fairly old, and I have just confirmed with Support that it is still an issue.  Seems to be a pretty basic request, so I'm putting it out there again under this new heading.

The issue is that if you have data in a field, and you have that data separated by a new line (\n), it will show up fine in a browse tool, or pretty much any other output (database file, Office Document file, etc.). But if you try to use the Table Tool under Reporting, it ignores the line break and strings the data together.

Example:

The field data looks like this in a browse or most other outputs:

Hello, my name is 

Michael Barone

and I love

Alteryx

But when I try to pull this field into a Table Tool, it shows up like this:
Hello, my name is Michael Barone and I love Alteyrx

Putting this out here again in hopes that it gets lots and lots of stars so it gets put on the road map!!

I reported this to the support team but was told it was by design and to post here.

In-DB Inefficient SQL

I would like to report that the In-DB tools are generating horribly inefficient SQL code for simple operations.  It seems no matter what tools you use every statement is starting with a nested 'Select * From'.

Example Simple workflow:

This is a simple Select and Group by but the SQL Generated is:

SELECT "ShipTo", "ShipTo_Name", SUM("ECM_3PL_OVERHEADS_Unit") AS "Sum_ECM_3PL_OVERHEADS_Unit"

FROM (SELECT * FROM "_SYS_BIC"."shell.app.gsap.FL000_LSC.FL002_CTS.INT.RPT/CA_CTS_RPT_MAIN_001") AS "a"

GROUP BY "ShipTo", "ShipTo_Name"

This is taking a very long time to execute:

Statement 'SELECT "ShipTo", "ShipTo_Name", SUM("ECM_3PL_OVERHEADS_Unit") AS "Sum_ECM_3PL_OVERHEADS_Unit" FROM ...'

successfully executed in 15.752 seconds  (server processing time: 15.699 seconds)

Whereas if I take the same query and remove the nested Select *:

SELECT "ShipTo", "ShipTo_Name", SUM("ECM_3PL_OVERHEADS_Unit") AS "Sum_ECM_3PL_OVERHEADS_Unit"

FROM "_SYS_BIC"."shell.app.gsap.FL000_LSC.FL002_CTS.INT.RPT/CA_CTS_RPT_MAIN_001" AS "a"

GROUP BY "ShipTo", "ShipTo_Name"

It is very quick:

Statement 'SELECT "ShipTo", "ShipTo_Name", SUM("ECM_3PL_OVERHEADS_Unit") AS "Sum_ECM_3PL_OVERHEADS_Unit" FROM ...'

successfully executed in 1.211 seconds  (server processing time: 1.157 seconds)

So Alteryx is generating queries up to x13 slower than they should be thereby defeating the point of using In-DB.  As you can imagine in a workflow where we have multiple Connect In-DB tools this is a really substantial amount of time.  Example used above is from SAP HANA DB has 1.9m rows and ~90 columns but we have much bigger tables/views than this.

If you look you will see its same behaviour for all In-DB tools where each tool creates another nested Select with its particular operator.

MY SUGGESTION:

So my suggestion is that Alteryx should combine the SQL of the first few tools and avoid using SELECT * completely unless no Select tools have been used.  So it should combine:

- Connect In-DB + Select

- Connect In-DB + Filter

- Connect In-DB + Summarise

Preferably it should combine/flatten everything up until the first join or union.  But Select + Filter are a must!

Note it seems some DB's can cope OK with un-nesting these big nested queries in the query plans for some Tables but normally not for Views.  But some cannot cope at all and so the In-DB tools cannot even be used to Browse 100 records (due to select *).

When training people on the use of action tools, something that I always have to hit on is that when you are telling the tool which piece of the XML that you are adjusting, it's sort of difficult to tell what you have selected, and super easy to accidentally select something else.

Example:

When you initially select the action to take it's this nice Blue Color. However, it still doesn't feel exactly like you have actually selected anything or told the Action Tool what to do, since it's so easy to just select any other one of these actions.

A slightly different problem is that if you are selecting an action that has been previously configured, it is just this light grey color. So it can be easy to accidentally change your settings because you may not realize it's actually set up.

Here is a recent community post that sort of outlines a few of these problems.

https://community.alteryx.com/t5/Alteryx-Designer-Discussions/Analytic-App-to-Create-Custom-SQL-Quer...

At the moment if a part of your python code takes more than 30s to run, Jupyter times out and Alteryx cancels the workflow. This makes the Python Tool unusable for anything intensive and the timeout should be removed by default or be configurable per workflow.

I've made this idea as none of the solutions in these threads feel satisfactory:

https://community.alteryx.com/t5/Alteryx-Designer-Discussions/Python-tool-NbConvertApp-Timeout/m-p/3...

https://community.alteryx.com/t5/Alteryx-Designer-Discussions/Python-Tool-Timeouts-When-Running-Work...

https://community.alteryx.com/t5/Alteryx-Designer-Discussions/Python-SDK-timeout-error-cell-executio...

Hi Alteryx Devs - 

It would be *really tight* to have a drop down interface tool that would support auto completion based on a odbc connection to a table/column or ajax call.  I recently had a situation wherein we need to give the users the ability to select an address, then run a workflow.  But the truth is, our address data is terrible, and what I really needed was to be able to let the users start typing the address, then give them a list of choices to pick from, they pick the correct (but usually wrongly formatted) address, and then I send that value into the workflow. 

I could not find a decent way to give a gallery user a reliable way to pick an address from our list, so eventually wound up having to write an ajax piece to handle the auto completion, capture the user input, then post to a service that would in turn, interact with gallery through the API, get the response, and send it back calling page, and back to the user.  A significant amount of work to put into something that is an exceedingly common web operation of auto completion.  

This would make a lot of gallery operations flow so much more naturally.  

Thanks for listening! 

brian

There are few workarounds for this task, but it would be really very easy if Data Cleansing Tool could delete Null Rows and Null Columns. After all its just a macro which can be modified and re-packaged into Alteryx Designer.

Currently, to delete a null row requires multiple columns validation for common Null attributes,

similarly to delete a null column every column has to be compared on a row-level and flagged for removal. Both of these approaches are clumsy.

Wouldn't it be so simple if Data Cleansing Tool gave such check boxes !!!

Please add Parquet data format (https://parquet.apache.org/) as read-write option for Alteryx.

Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language.

Thank you.

Regards,

Cristian.