The Data Warrior

Changing the world, one data model at a time. How can I help you?

Better Data Modeling: Customizing Oracle Sql Developer Data Modeler (#SQLDevModeler) to Support Custom Data Types

On a recent customer call (for Snowflake), the data architects were asking if Snowflake provided a data model diagramming tool to design and generate data warehouse tables or to view a data model of an existing Snowflake data warehouse. Or if we knew of any that would work with Snowflake.

Well, we do not provide one of our own – our service is the Snowflake Elastic Data Warehouse (#ElasticDW).

The good news is that there are data modeling tools in the broader ecosystem that you can of course use (since we are ANSI SQL compliant).

If you have read my previous posts on using JSON within the Snowflake, you also know that we have a new data type called VARIANT for storing semi structured data like JSON, AVRO, and XML.

In this post I will bring it together and show you the steps to customize SDDM to allow you to model and generate table DDL that contain columns that use the VARIANT data type.

Read the details of how I did it here on my Snowflake blog:

Snowflake SQL: Customizing Oracle Sql Developer Data Modeler (SDDM) to Support Snowflake VARIANT – Snowflake

Enjoy!

Kent

The Data Warrior

P.S. If you are in Austin, Texas this weekend, I will be speaking at Data Day Texas (#DDTX16). Snowflake will have a booth there too, so come on by and say howdy!

Snowflake SQL: Making Schema-on-Read a Reality (Part 2)

This is the 2nd of my articles on the Snowflake blog.

In the first article of this series, I discussed the Snowflake data type VARIANT, showed a simple example of how to load a VARIANT column in a table with a JSON document, and then how easy it is to query data directly from that data type. In this post I will show you how to access an array of data within the JSON document and how we handle nested arrays. Then finally I will give you an example of doing an aggregation using data in the JSON structure and how simple it is to filter your query results by referring to values within an array.

Check out the rest of the post here:

Snowflake SQL: Making Schema-on-Read a Reality (Part 2) – Snowflake

Enjoy!

Kent

The Data Warrior

#DataWarrior 2015 in review

Happy New Year again everybody!

Shoutout to Jeff Smith for again being the #1 real person that I actually know who referred people to my blog via his blog. If you don’t already, please add ThatJeffsSmith to your reading list.

The WordPress.com stats helper monkeys prepared a 2015 annual report for me.

Here’s an excerpt:

Madison Square Garden can seat 20,000 people for a concert. This blog was viewed about 69,000 times in 2015. If it were a concert at Madison Square Garden, it would take about 3 sold-out performances for that many people to see it.

Click here to see the complete report.

Cheers!

Kent

The Data Warrior and Snowflake Evangelist

Happy 2016!

Happy New Year

Better Data Modeling: Discovering Foreign Keys (FK) in #SQLDevModeler (SDDM)

A while back I had an interesting situation when I was attempting to reverse engineer and document a database for a client.

I had a 3rd party database that had PKs defined on every table but no FKs in the database. The question I posed (on the Data Modeler Forum) was:

How do I get the FK Discover utility to find FK columns with this type of pattern:

Parent PK column = TABCUSTNUM

Child FK column = ABCCUSTNUM

So the root column name (CUSTNUM) is standard but in every table the column name has a different 3 character “prefix” that is effectively the table short name. Is there way to get the utility to ignore the first three characters of the column names?

This was in SDDM 4.1.873.

No easy answer.

Well, the ever helpful Philip was very kind and wrote me a slick custom Transformation Script that did the trick! (Check the post if you want to see the code.)

But wait there’s more!

In his response he mentioned a feature coming in 4.1.888 – the ability to include a table prefix as part of a FK column naming template (just like this app had done).

Cool, I thought, but how does that help?

Well with the template in place it turns out that you can have the FK Discovery utility search based on the Naming Template model rather than just look for exact matching column names.

Using the Custom Naming Template

So recently (today in fact) I was trying to add FKs to the Snowflake DB model I reverse engineered a few weeks back (Jeff pointed out they were missing). I noticed the model had that pattern of a prefix on both the FK and PK column names.

In the CUSTOMER table the PK is C_CUSTKEY. In the ORDER table it is O_CUSTKEY. Nice simple pattern (see the diagram below for more). That reminded me of the previous issue and Philip’s script.

Snowflake Schema

Off to OTN to find that discussion and refresh my memory.

In the post, Philip has posted an example of a template that fit my previous problem:

{table abbr}SUBSTR(4,30,FRONT,{ref column})

With the note that {table abbr} would be the equivalent of what I called the table prefix. So first I went to the table properties and put in the prefixes using the Abbreviation property:

Add Table Abbrev

Then all I had to do was modify his example to account for the underscore and the fact that the main column text would start at character #3 instead of #4:

{table abbr}_SUBSTR(3,30,FRONT,{ref column})

I input that by going to Properties -> Settings -> Naming Standards -> Templates and then editing the default template:

Set up FK template

Discover FKs!

Now it was just a matter of running the utility. You find that with a right mouse click on the Relational Design node:

Discover FK tool

Next you get the list of candidate FKs:

Create FKs

Note that the utility also suggested some FKs based on the unique constraints (UKs) as well. I did not want those, so I unchecked them before I hit “OK”.

The result was getting all the FKs I wanted added into my model! Viola!

Snowflake with RI

So I can happily report that Philip’s little enhancement works just fine in 4.1.3. WooHoo! I can see this being very useful for a lots of cases in the future.

In a future post (early next year), I will continue with showing how we implemented Referential Integrity constraints in Snowflake DB and if I can generate the DDL from #SQLDevModeler.

Happy New Year Y’all

Kent

The Data Warrior & Snowflake Technical Evangelist

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