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Submission GuidelinesHello,
After used the new "Image Recognition Tool" a few days, I think you could improve it :
> by adding the dimensional constraints in front of each of the pre-trained models,
> by adding a true tool to divide the training data correctly (in order to have an equivalent number of images for each of the labels)
> at least, allow the tool to use black & white images (I wanted to test it on the MNIST, but the tool tells me that it necessarily needs RGB images) ?
Question : do you in the future allow the user to choose between CPU or GPU usage ?
In any case, thank you again for this new tool, it is certainly perfectible, but very simple to use, and I sincerely think that it will allow a greater number of people to understand the many use cases made possible thanks to image recognition.
Thank you again
Kévin VANCAPPEL (France ;-))
Thank you again.
Kévin VANCAPPEL
Hello all,
This is a very interesting feature of the List Box and Drop Down interface tool : the ability to select fields
However such a feature is not available for in-database, highly limiting the use of macros.
Please change.
Best regards,
Simon
Hello all,
As of today, when you want to retrieve or create a file on Apache Spark for Databricks, you have only two choices : CSV and Avro
However it's clearly missing parquet file type :
-it's faster
-it's better for storage
-it's standard and already supported as input/output of Alteryx or for HDFS so doesn't seem hard to add here.
Best regards,
Simon
Hello all,
It's really frustrating to have an "alteryx field type" in In-Database Select. It doesn't even make sense since we're manipulating only data in SQL database where those types does not exist. What we should see is the SQL field type.
Best regards,
Simon
Hello all,
When using in-database, all you have in select or formula are the Alteryx field types (V_String, etc..).
However, since you're mostly writing in database, in the end, there is a conversion of Alteryx field types to real SQL field types (like varchar). But how is it done ? As of today, it's a total black box. Some documentation would be appreciated.
Best regards,
Simon
Hello all,
As of today, you can populate the Drop Down tool in the interface category with a query launched from a in-memory connection. I would really appreciate the ability to use instead an in-db connection.
Why ?
It means managing two connections instead of one, and finding ways to manage it on server for both of them, etc etc.. Simplicity is key.
Best regards,
Simon
Hello all,
Apache Doris ( https://doris.apache.org/ ) is a modern datawarehouse with a lot of ambitions. It's probably the next big thing.
You can read the full doc here https://doris.apache.org/docs/get-starting/what-is-apache-doris but to sum it up, it aims to be THE reference solution for OLAP by claiming even better performance than Clickhouse, DuckDB or MonetDB. Even benchmarks from the Clickhouse team seem to agree.
Best regards,
Simon
Hello all,
ADBC is a database connection standard (like ODBC or JDBC) but specifically designed for columnar storage (so database like DuckDB, Clickhouse, MonetDB, Vertica...). This is typically the kind of stuff that can make Alteryx way faster.
more info in https://arrow.apache.org/blog/2023/01/05/introducing-arrow-adbc/
Here a benchmark made by the guys at DuckDB : 38x improvement
https://duckdb.org/2023/08/04/adbc.html
Best regards,
Simon
Hello all,
As of now, you have two very distinct kinds of connection :
-in memory alias
-in database alias
It happens than every single time I use a in-database alias I have to create the same for in memory since some operations cannot be realized in in-database (such as pre-sql or interface tools)
What does that mean for us :
-more complex settings operations/training/tests
-unefficient worflows that have to deal with two kinds of alias.
What I propose :
-a single "connection alias", that can be used either for in-db either for in-memory,
-one place to configure
-the in-db or in-memory being dependant on the tools you use
Best regards,
Simon
Hello all,
As of today, you must set which database (e.g. : Snowflake, Vertica...) you connect to in your in db connection alias. This is fine but I think we should be able to also define the version, the release of the database. There are a lot of new features in database that Alteryx could use, improving User Experience, performance and security. (e.g. : in Hive 3.0, there is a catalog that could be used in Visual Query Builder instead of querying slowly each schema)
I think of a menu with the following choices :
-default (legacy) and precision of the Alteryx default version for the db
-autodetect (with a query launched every time you run the workflow when it's possible). if upper than last supported version, warning message and run with the last supported version settings.
-manual setting a release (to avoid to launch the version query every time). The choices would be every supported alteryx version.
Best regards,
Simon
Hello all,
As of today, we can easily copy or duplicate a table with in-database tool.This is really useful when you want to have data in development environment coming from production environment.
But can we for real ?
Short answer : no, we can't do it in these cases :
-partitions
-any constraints such as primary-foreign keys
But even if these ideas would be implemented, this means manually setting these parameters.
So my proposition is simply a "clone table"' tool that would clone the table from the show create table statement and just allow to specify the destination path (base.table)
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
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 all,
We all love pretty much the in-memory multi-row formula tool. Easy to use, etc. However, the indb counterpart does not exist.
I see that as a wizard that would generate windowing functions like LEAD or LAG
https://mode.com/sql-tutorial/sql-window-functions/
Best regards,
Simon
Hello all,
According to wikipedia https://en.wikipedia.org/wiki/Materialized_view
In computing, a materialized view is a database object that contains the results of a query. For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function.
The process of setting up a materialized view is sometimes called materialization.[1] This is a form of caching the results of a query, similar to memoization of the value of a function in functional languages, and it is sometimes described as a form of precomputation.[2][3] As with other forms of precomputation, database users typically use materialized views for performance reasons, i.e. as a form of optimization.
So, I would like to create that in Alteryx, for obvious performance reasons in some use cases.
This is not a duplicate of https://community.alteryx.com/t5/Alteryx-Designer-Desktop-Ideas/In-DB-Create-View/idi-p/157886
Best regards,
Simon
Hello all,
According to wikipedia :
https://en.wikipedia.org/wiki/Embedded_database
An embedded database system is a database management system (DBMS) which is tightly integrated with an application software; it is embedded in the application.
It's often like a single file/dll that you can use inside an application without the user having to connect (or at least to configure it) to it (it's all done inside the application). So, it's widely portable.
Why it does matter ?
As of today, there is not a single example of in database workflow because all the supported databases need the user to:
1/install an odbc driver (most of time, he won't have the rights to do so)
2/configure an odbc connection (sometimes, he doesn't have the rights to)
3/configure a connection on Alteryx (ok, he can)
So it requires IT action, which can be pretty long (in ùany organization, it requires several weeks !!). And even with all of that,the users must be granted privilege to access database and the customer need to develop its own examples and write its own specific documentation.
Well, this is not efficient.
What I suggest is Alteryx to use one of embedded database for training support/one tool examples. SQLlite seems good, maybe a more analytics oriented (like DuckDB ) would be more efficient.
The requirement are, I think, the following :
-OpenSource and free
-Fast
-SQL compliant
-With a bulk load ability
Best regards,
Simon
Hello,
Just like Monetdb or Vertica, Clickhouse is a column-store database, claiming to be the fastest in the world. It's available on Cloud (like Snowflake), linux and macos (and here for free, it's open-source). it's also very well ranked in analytics database https://db-engines.com/en/system/ClickHouse and it would be a good differenciator with competitors.
https://clickhouse.com/
it has became more popular than Greenplum that is supported : (black snowflake, red greenplum, orange clickhouse)
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:
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:
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,
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
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
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