Alteryx Designer Desktop Ideas

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

When making any type of macro, it's important to test the functionality of the macro via a debug.  This is accomplished successfully with normal tools, however there's a bug that will not allow the user to debug In-DB macros that use either of the following standard Alteryx tools:  

• Macro Input In-DB
• Macro Output In-DB

If either of these tools are included in the macro you are building, an error message will appear not allowing you to open a debug.  

Error message: Question Tool Load Error:  A question tool with a tool id of XXX is missing the associated question data.

Of course, Macro input and output tools do not require any specific action/question tool associated with it.  This is a bug.  A user pointed out the XML issue almost 3 years ago here:

In summary: "It appears that the tool itself inserts a hidden Question attribute into the XML which can also be seen in Workflow Configuration"

Source:

https://community.alteryx.com/t5/Alteryx-Designer-Desktop-Discussions/In-DB-Macro-Input-and-Output-t...

Examples....

A normal macro, using standard tools:

After debugging a standard macro, the Macro Input/Output tools correctly change to a Text Input and a Browse tool.  This allows the macro author to test the macro.

However, when trying the same thing with In-DB tools in a macro, an error message appears:

In-DB macro 1:

In-DB Macro error message (after clicking "Open Debug"):

Hello all,

Sometimes, when you have too much time to retrieve your tables metadas, you can have this message

Initialization Timed Out: Workflow must be run for field meta info to be accurate.

From what I understand, it's Alteryx and the source system that drives the time out value. However, I have some cases where the long time is "normal" and that really hurts the user experience.
So, I would like the ability in settings to change the default value.

Best regards,

Simon

Hello all,

as of today, a join in-db can only be done with an equal operator.

Example : table1.customer_id = table2.customer_id

It's sufficient most of the time. However, sometimes, you need to perform another kind of join operation, (especially with calendar, period_table, etc).

Here an example of clause you can find in existing sql

inner join calendar on calendar.id_year_month between fact.start_period and fact.end_period

helping to solve that case :

(the turnaround I use to day being : I make a full cartesian product with a join on 1=1 and then I filter the lines for the between)

or <,>, .... et caetera.

It can very useful to solve the most difficult issues. Note that a product like Tableau already offers this feature.

Best regards,

Simon

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.

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.

Hello,

SQLite is :

-free

-open source

-easy to use
-widely used

https://en.wikipedia.org/wiki/SQLite

It also works well with Alteryx input or output tool. 🙂

However, I think a InDB SQLite would be great, especially for learning purpose : you don't have to install anything, so it's really easy to implement.

Best regards,

Simon

Hello all,

MonetDB is a very light, fast, open-source database available here :
https://www.monetdb.org/

Really enjoy it, works pretty well with Tableau and it's a good introduction to column-store concepts and analytics with SQL.

It has also gained a lot of popularity these last years :
https://db-engines.com/en/ranking_trend/system/MonetDB

Sadly, Alteryx does not support it yet.

Best regards

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,

According to wikipedia :

A partition is a division of a logical database or its constituent elements into distinct independent parts. Database partitioning is normally done for manageability, performance or availability reasons, or for load balancing. It is popular in distributed database management systems, where each partition may be spread over multiple nodes, with users at the node performing local transactions on the partition. This increases performance for sites that have regular transactions involving certain views of data, whilst maintaining availability and security. 

Well, basically, you split your table in several parts, according to a field. it's very useful in term of performance when your workflows are in delta or when all your queries are based on a date. (e.g. : my table helps me to follow my sales month by month, I partition my table by month).

So the idea is to support that in Alteryx, it will add a good value, especially in In-DB workflows.

Best regards,

Simon

I would like to suggest creating a fix to allow In-DB Connect tool's custom SQL to read Common Table Expressions. As of 2018.2, the SQL fails due to the fact that In-DB tools wrap everything in a select * statement. Since CTE's need to start with With, this causes the SQL to error out. This would be a huge help instead of having to write nested sub selects in a long, complex SQL code!

Statistics are tools used by a lot of DB to improve speed of queries (Hive, Vertica, etc...). It may be interesting to have an option on the write in db or data stream in to calculate the statistics. (something like a check box for )

Example on Hive : analyse {table} comute statistics; analyse {table} compute statistics for columns;

As of today, for a full refresh, I can :

-create a new table

-overwrite a table. (will drop and then create the new table)

But sometimes, the workflow fails and the old table is dropped while the new one is not created. I have to modify the tool (setting "create a new table")to launch it again, which may be a complex process in companies. After that, I have to modify it again back to "overwrite".

What I want :

-create a new table-error if table already exists

-overwrite a table-error if table doesn't exist

-overwrite a table-no error if table doesn't exist (easy in sql : drop if exists...)

Thanks!

When I create a new table in a in-Db workflow, I want to specify some contraints, especially the Primary Key/Foreign Key

For PK/FK, the UX could be either the selection of some fields of the flow or a free field (to let the user choose a constant).

From wikipedia :

In the relational model of databases, a primary key is a specific choice of a minimal set of attributes (columns) that uniquely specify a tuple (row) in a relation (table).[a] Informally, a primary key is "which attributes identify a record", and in simple cases are simply a single attribute: a unique id. 

So, basically, PK/FK helps in two ways :
1/ Check for duplicate, check if the value inserted is legit

2/ Improve query plan, especially for join

It would be awesome if there was a cross tab in DB option because right now I have to stream out millions of records to build a cross tab.

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.

I noticed through the ODBC driver log that Alteryx doesn't care about the kind of base I precise. It tests every single kind of base to find the good one and THEN applies the queries to get the metadata info.

Here an example. I have chosen an Hive in db connection. If  I read the simba logs, i can find those lines :

Mar 01 11:37:21.318 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select USER(), APPLICATION_ID() from system.iota

Mar 01 11:37:22.863 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select USER as USER_NAME from SYSIBM.SYSDUMMY1

Mar 01 11:37:23.454 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select * from rdb$relations

Mar 01 11:37:23.546 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select first 1 dbinfo('version', 'full') from systables

Mar 01 11:37:23.707 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select #01/01/01# as AccessDate

Mar 01 11:37:23.868 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: exec sp_server_info 1

Mar 01 11:37:24.093 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select top (0) * from INFORMATION_SCHEMA.INDEXES

Mar 01 11:37:24.219 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: SELECT  SERVERPROPERTY('edition')

Mar 01 11:37:24.423 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select DATABASE() as `database`, VERSION() as `version`

Mar 01 11:37:24.635 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select * from sys.V_$VERSION at where RowNum<2

Mar 01 11:37:25.230 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select cast(version() as char(10)), (select 1 from pg_catalog.pg_class) as t

Mar 01 11:37:25.415 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select NAME from sqlite_master

Mar 01 11:37:25.756 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select xp_msver('CompanyName')

Mar 01 11:37:26.156 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select @@version

Mar 01 11:37:26.376 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: select * from dbc.dbcinfo

Mar 01 11:37:26.522 INFO  5264 HardyDataEngine::Prepare: Incoming SQL: SELECT @@VERSION;

I can understand that when Alteryx doesn't know the kind of base he tries everything.. (eg : in memory visual query builder) but here, I have selected the Hive database and I have to loose more than 5 seconds for nothing.

Hello,

As I mentioned in this previous idea : https://community.alteryx.com/t5/Alteryx-Designer-Ideas/Generic-In-database-connection-please-stop-i...

field mapping in generic in-db connection is based on Microsoft Sql Server. Given the specificity of MSQL Server field types, I would like to change that in order to at least be able to use another database. Without that, this feature has no sense at all.

Best regards,

Simon

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.