Alteryx Designer

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Enable Gallery Server Connections as Input for In-DB Tools. Currently, we can only create file connections, and we'd like to centralize all connections to our Gallery Connections.

The Tableau Hyper API supports regular SQL queries, see https://help.tableau.com/current/api/hyper_api/en-us/reference/sql/index.html and https://help.tableau.com/current/api/hyper_api/en-us/docs/hyper_api_reference.html for more information. Being able to use the In-database tools for querying Hyper would let us take advantage of Hyper's internal optimizations just like other databases.

 

 

TIBCO Data Virtualization is a Data Virtualization product focused on creating a virtual data store consolidating data from throughout the enterprise.  It can be accessed via a SQL query engine, and has a variety of supported connectors, including an ODBC driver.

 

This data source can be connected to via ODBC in Alteryx today, but error messaging is unclear/unhelpful, and attempting to use the Visual Query Builder causes Alteryx to crash.

 

Adding TIBCO Data Virtualization as a supported ODBC connection would empower business users to leverage this product and easily utilize this enterprise data store, enhancing the value of the Alteryx platform as a consumer of this data.

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.

 

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

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.

 

 

 

Hi,

 

     Currently loading large files to Postgres SQL(over 100 MB) takes an extremely long time. For example writing a 1GB file to Postgres SQL takes 27 minutes! This is serious impacting our ability to use Alteryx as an ETL tool for loading our target Postgres Data Warehouse. We would really like to see the bulk load capacity to Postgres supported by Alteryx to help alleviate the performance issues.

 

Thanks,

Vijaya

Hello,

 

As of today, if you want to add a PostgreSQL in database connection, you may feel embarrased :

 

simonaubert_bd_2-1576917126485.png

 

 

However, the help states that PostgreSQL is supported by in-database.

https://help.alteryx.com/current/In-DatabaseOverview.htm

 

Whaaaaaaaaat?

oh, I forgot to mention : with a little luck, you can find tis help page : https://help.alteryx.com/current/DataSources/PostgreSQL.htm

Yep, you have to configure a "greenplum" connection if you want to use a PSQL.

i think this is not user-friendly and can lead to mistake, errors, frustration and even lack of sales for Alteryx :

https://community.alteryx.com/t5/Alteryx-Designer-Discussions/Do-you-use-generic-in-database-connect...

 

Also, Greeenplum and PSQL will have separate features so I think having two separate entries in the menu is pertinent.

Best regards,

 

Simon

  • Category In Database

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

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

MySQL released version 8 for general availability in April 2018. It would be nice when Alteryx installed LUA scripts for MySQL 8 by default. Now only LUA scripts for MySQL 5 are installed.

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:

  Support1.jpgSupport2.jpg

 

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 *).

  • Category In Database

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.

The idea is to store credentials, login/pw in a "credential alias".

 

Then, those credential aliases can be used in :

-traditional aliases/connection

-in database aliases/connection

-hdfs aliases/connection

-API

-on user aliases for connected controllers/gallery

...etc.

 

The idea is that I only have to change the credentials once for all the connection type (on Hive, I have the in db alias, the traditional alias and even an HDFS alias using exactly the same credentials !! and I have to change all that manually).

 

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.

  • 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.

I would like to see In-DB batch macros, currently we are joining tables with 30 million+ records and we are having to run it through standards tools because we are unable to process via In-DB, which has a 20% improvement in processing speed based on the peformance profiling.  

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.

  • Category In Database

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

Where it stands now, only a file input tool can be used to pull data from Google BigQuery tables. The issue here is that the data is streamed and processed locally, meaning the power of BigQuery processing isn't actually being leveraged.

Adding BigQuery In-Database as a connection option would appeal to a wide audience. BigQuery is also standard SQL compliant with the SQL 2011 standard, so this may make for an even easier integration.

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