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Alteryx Designer Ideas

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Hello all,

Big picture : on Hadoop, a table can be

-internal (it's managed by Hive or Impala, and act like any other database)
-external (it's managed by hadoop, can be shared among the different hadoop db such as hive and impala and you can't delete it by default when dropping the table

 

for info, about suppression on external table :

https://docs.cloudera.com/HDPDocuments/HDP3/HDP-3.1.4/using-hiveql/content/hive_drop_external_table_...

Alteryx only creates internal tables while it would be nice to have the ability to create external tables that we can query with several tools (Hive, Impala, etc).

It must be implemented

-by default for connection
-by tool if we want to override the default

Best regards,

Simon

Hello,

As of today, we can't choose exactly the file format for Hadoop when writing/creating a table. There are several file format, each wih its specificity.

Therefore I suggest the ability to choose this file format :

-by default on connection (in-db connection or in-memory alias)

-ability to choose the format for the writing tool itself.

Best regards,

Simon

Hi all,
Something really interesting I found - and never knew about, is there are actually in-DB predictive tools. You can find these by having a connect-indb tool on the canvas and dragging on one of the many predictive tools.

For instance:
boosted model dragged on empty campus:

TheOC_0-1660125228395.png


Boosted model tool deleted, connect in-db tool added to the canvas:

TheOC_1-1660125281871.png



Boosted Model dragged onto the canvas the exact same:

TheOC_2-1660125303663.png

 


This is awesome! I have no idea how these tools work, I have only just found out they are a thing. Are we able to unhide these? I actually thought I had fallen into an Alteryx Designer bug, however it appears to be much more of a feature.

 

Sadly these tools are currently not searchable for, and do not show up under the in-DB section. However, I believe these need to be more accessible and well documented for users to find.

TheOC_3-1660125345924.png



 

Cheers,
TheOC

 

For in-DB use, please provide a Data Cleansing Tool.

 

 

01.jpg

 

Sometimes I need to connect to the data in my Database after doing some filtering and modeling with CTEs. To ensure that the connection runs quicker than by using the regular input tool, I would like to use the in DB tool. But is doesn't working because the in DB input tool doesn't support CTEs. CTEs are helpful for everyday life and it would be terribly tedious to replicate all my SQL logic into Alteryx additionally to what I'm already doing inside the tool. 

I found a lot of people having the same issue, it would be great if we can have that feature added to the tool. 

Please add support for Databricks' Unity Catalog

 

Currently, when selecting a Databricks-connection in the “Connect In-DB”-tool, and opening the “Query Builder”, only tables in the catalog named “hive_metastore” are listed. That is, Alteryx submits the following SQL query to Databricks:

Listing tables 'catalog : hive\_metastore, schemaPattern : %, tableTypes : null, tableName : %'

 

However, with Unity Catalog in Databricks the namespace is three-tier and there may be multiple catalogs (and not just the "hive_metastore" catalog), see https://docs.microsoft.com/en-gb/azure/databricks/lakehouse/data-objects#--what-is-a-catalog

 

I reached out to Alteryx support, which replied that you currently have a feature request for implementing this change (ID TDCB-4056) and they furthermore suggested that I post here.

 

Thanks in advance.

Hello all,

In help, we can read that :
https://help.alteryx.com/current/designer/write-data-db-tool

Update/Delete is currently only supported for SQL Server ODBC connections.

 

 I don't know about you but SQL Server is well used in transactional workload but in analytics... well... I have only used once in several dozens of context !

Maybe it would be cool to make it work on many more database?

Best regards,

Simon

Currently Alteryx does not support writing to SharePoint document libraries.

However there are success sometimes but not at other times.

Please see attachment where we ran into an issue.

See this link for additional information.

https://community.alteryx.com/t5/Data-Sources/Connect-to-and-Publish-Back-to-SharePoint-Online/m-p/4...

 

We need official support for reading and writing to SharePoint document libraries.

It's an important Output target, and will becoming more so, as Alteryx enhances its reporting capabilities.

 

Alteryx Designer is slow when using In-DB tools.

 

We use Alteryx 2019.1 on Hive/HortonWords with the Simba ODBC Driver configured with SSL enabled.

 

Here is a compare In-DB / in Memory : 

demo01.gif

demo02.gif

 

We found that Alteryx open a new connection for each action : 

- First link to joiner = 1 connection.

- Second ling to joiner = 1 connection.

- Click on the canevas = 1 connection.

 

Each connection take about 2,5 sec... It really slow down the Designer : 

ScreenLog.jpg

 

 

Please, keep alive the first connection instead of closing it and creating a new one for each action on the Designer.

 

 

 

Currently the Databricks in-database connector allows for the following when writing to the database

  1. Append Existing
  2. Overwrite Table (Drop)
  3. Create New Table
  4. Create Temporary Table

This request is to add a 5th option that would execute

  • Create or Replace Table

Why is this important?

  • Create or Replace is similar to the Overwrite Table (Drop) in that it fully replaces the existing table however, the key differences are
    • Drop table completely removes the table and it's data from Databricks
      • Any users or processes connected to that table live will fail during the writing process
      • No history is maintained on the table, a key feature of the Databricks Delta Lake
    • Create or Replace does not remove the table
      • Any users or processes connected to that table live will not fail as the table is not dropped
      • History is maintained for table versions which is a key feature of Databricks Delta Lake

 

While this request was specific to testing on Azure Databricks the documentation for Azure and AWS for Databricks both recommend using "Replace" instead of "Drop" and "Create" for Delta tables in Databricks. 

 

AStasi_0-1661864644374.pngAStasi_1-1661864772827.png

We really need a block until done to process multiple calculations inDB without causing errors. I have heard that there is a Control Container potentially on the road map.  That needs to happen ASAP!!!!

We're not too happy with the Gallery Data Connections not being available for the IN-DB data input tool but that will hopefully be a feature to be looked at in future product improvements; Let us know if there are reasons not having this feature already.

Thank you.

 

Hello,


As of today, when you connect o, a database, you go through a batch of queries to retrieve which database it is ( cf https://community.alteryx.com/t5/Alteryx-Designer-Ideas/Smart-Visual-Query-Builder-for-in-db-less-te... where I suggest a solution to speed up the process) and then, Alteryx queries the metadata. In order to get the column in each table, Alteryx use a SHOW TABLES and then loop on each table. This is really slow. 

However, since Hive 3.0, an information_schema with the list of columns for each  table is now available. I suggest to use the information_schema.columns instead of the time-consuming loop.

 
 

image.png


PS : I don't know if it's linked to the Active Query Builder, the third-party tool behind the Visual Query Builder. In that case, it would be a good idea to update it as suggested here https://community.alteryx.com/t5/Alteryx-Designer-Ideas/Update-Query-Builder-component/idi-p/799086



Best regards,

Simon

Hello,

 

We use the pre-sql statement of the input to set some parameters of connections. Sadly, we cannot do that in a in-db workflow. This would be a total game-changing feature for us.

 

Best Regards,

 

Simon

  • Category In Database

Currently, when one uses the Google BigQuery Output tool, the only options are to create a table, or append data to an existing table.  It would be more useful if there was a process to replace all data in the table rather than appending. Having the option to overwrite an existing table in Google BigQuery would be optimal.

  • Category In Database

Hello all,

According to wikipedia :
https://en.wikipedia.org/wiki/Join_(SQL)

 

CROSS JOIN returns the Cartesian product of rows from tables in the join. In other words, it will produce rows which combine each row from the first table with each row from the second table.[1]

Example of an explicit cross join:

SELECT *
FROM employee CROSS JOIN department;

Example of an implicit cross join:

SELECT *
FROM employee, department;

The cross join can be replaced with an inner join with an always-true condition:

SELECT *
FROM employee INNER JOIN department ON 1=1;

 

For us, alteryx users, it would be very similar to Append Fields but for in-db.

Best regards,

Simon

It would be great to have the below functionality in Alteryx.

A workflow is built in Alteryx and button click in Alteryx can be used to generate SQL code that can be ran on a specific database platform, such as SQL Server to run external editors such as SQL Server Management Studio. Thanks. 

Alteryx has the ability to connect to data sources using fat clients and ODBC but not JDBC.  If the ability to use JDBC could be added to the product it could remove the need to install fat clients.

From Wikipedia :

In a database, a view is the result set of a stored query on the data, which the database users can query just as they would in a persistent database collection object. This pre-established query command is kept in the database dictionary. Unlike ordinary base tables in a relational database, a view does not form part of the physical schema: as a result set, it is a virtual table computed or collated dynamically from data in the database when access to that view is requested. Changes applied to the data in a relevant underlying table are reflected in the data shown in subsequent invocations of the view. In some NoSQL databases, views are the only way to query data.

Views can provide advantages over tables:

    Views can represent a subset of the data contained in a table. Consequently, a view can limit the degree of exposure of the underlying tables to the outer world: a given user may have permission to query the view, while denied access to the rest of the base table.
    Views can join and simplify multiple tables into a single virtual table.
    Views can act as aggregated tables, where the database engine aggregates data (sum, average, etc.) and presents the calculated results as part of the data.
    Views can hide the complexity of data. For example, a view could appear as Sales2000 or Sales2001, transparently partitioning the actual underlying table.
    Views take very little space to store; the database contains only the definition of a view, not a copy of all the data that it presents.
    Depending on the SQL engine used, views can provide extra security.

I would like to create a view instead of a table.

  • Category In Database

Please could you enhance the Alteryx download tool to support SFTP connections with Private Key authentication as well.  This is not currently supported and all of our SFTP use cases use PK.

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