2016: A review of the year

As 2016 draws to a close I like to look back at what I have achieved over the year. Most of the following achievements are based on my work with the Oracle User Group community. I have some other achievements are are related to the day jobs (Yes I have multiple day jobs), but I won't go into those here.

As you can see from the following 2016 was another busy year. There was lots of writing, which I really enjoy and I'll be continuing with in 2017. As they say, watch this space for writing news in 2017.

Books

Yes 2016 was a busy year for writing and most of the later half of 2015 and the first half of 2016 was taken up writing two books. Yes two books. One of the books was on Oracle R Enterprise and this book compliments my previous published book on Oracle Data Mining. I now have the books that cover both components of the Oracle Advanced Analytics Option.

I also co-wrote a book with legends of Oracle community. These were Arup Nada, Martin Widlake, Heli Helskyaho and Alex Nuijten.

More news coming in 2017.

Blog Posts

One of the things I really enjoy doing is playing with various features of Oracle and then writing some blog posts about them. When writing the books I had to cut back on writing blog posts. I was luck to be part of the 12.2 Database beta this year and over the past few weeks I've been playing with 12.2 in the cloud. I've already written a blog post or two already on this and I also have an OTN article on this coming out soon. There will be more 12.2 analytics related blog posts in 2017.

In 2016 I have written 55 blog posts (including this one). This number is a little bit less when compared with previous years. I'll blame the book writing for this. But more posts are in the works for 2017.

Articles

In 2016 I've written articles for OTN and for Toad World. These included:

OTN

1. Oracle Advanced Analytics : Kicking the Tires/Tyres
2. Kicking the Tyres of Oracle Advanced Analytics Option - Using SQL and PL/SQL to Build an Oracle Data Mining Classification Model
3. Kicking the Tyres of Oracle Advanced Analytics Option - Overview of Oracle Data Miner and Build your First Workflow
4. Kicking the Tyres of Oracle Advanced Analytics Option - Using SQL to score/label new data using Oracle Data Mining Models
5. Setting up and configuring RStudio on the Oracle 12.2 Database Cloud Service

ToadWorld

1. Introduction to Oracle R Enterprise
2. ORE 1.5 - User Defined R Scripts

Conferences

1. January - Yes SQL Summit, NoCOUG Winter Conference, Redwood City, CA, USA **
2. January - BIWA Summit, Oracle HQ, Redwood City, CA, USA **
3. March - OUG Ireland, Dublin, Ireland
4. June - KScope, Chicago, USA (3 presentations)
5. September - Oracle Open World (part of EMEA ACEs session) **
6. December - UKOUG Tech16 & APPs16

** for these conferences the Oracle ACE Director programme funded the flights and hotels. All other expenses and other conferences I paid for out of my own pocket.

OUG Activities

I'm involved in many different roles in the user group. The UKOUG also covers Ireland (incorporating OUG Ireland), and my activities within the UKOUG included the following during 2016:

• Editor of Oracle Scene: We produced 4 editions in 2016. Thank you to all who contributed and wrote articles.
• Created the OUG Ireland Meetup. We had our first meeting in October. Our next meetup will be in January.
• OUG Ireland Committee member of TECH SIG and BI & BA SIG.
• Committee member of the OUG Ireland 2 day Conference 2016.
• Committee member of the OUG Ireland conference 2017.
• KScope17 committee member for the Data Visualization & Advanced Analytics track.

I'm sure I've forgotten a few things, I usually do. But it gives you a taste of some of what I got up to in 2016.

Auditing Oracle Data Mining model usage

In a previous blog post I talked about how you can rename and comment your Oracle Data Mining models. This is to allow you to easily to see and understand the intended use of the data mining model.

Another feature available to you is to audit the usage of the the data mining models. As your data mining environment grows to many 10s or more typically 100s of models, you will need to have some way of tracking their usage. This can allow you to discover what models are frequently being used and those that are not being used in-frequently. You can then use this information to investigate if there are any issues. Or in some companies I've seen an internal charging scheme in place for each time the models are used.

The following outlines the steps required to setup the auditing of your models and how to inspect the usage.

Note: You will need to the AUDIT_ADMIN role to audit the models.

First create an audit policy for the data mining model in a particular schema.

CREATE AUDIT POLICY oaa_odm_audit_usage 
ACTIONS ALL 
ON MINING MODEL dmuser.high_value_churn_clas_svm;

This creates a policy that monitors all activity on the data mining model HIGH_VALUE_CHURN_CLAS_SVM in the DMUSER schema.

Now we need to enable the policy and allow to to tract all activity on the model.

AUDIT POLICY oaa_odm_audit_usage BY oaa_model_user;

This will track all usage of the data mining model by the schema call OAA_MODEL_USER. We can then use the following query to search for the audit records for the OAA_MODEL_USER schema.

SELECT dbusername,
       action_name, 
       systemm_privilege_used, 
       return_code,
       object_schema, 
       object_name, 
       sql_text
FROM  unified_audit_trail
WHERE object_name = 'HIGH_VALUE_CHURN_CLAS_SVM';

But there is a little problem with using what I've just shown you above. The problem is that it will track all activity on the data mining model. Perhaps this isn't what we really want. Perhaps we only want to track only certain activity of the data mining model. Instead of creating the policy using 'ACTIONS ALL', we can list out the actions or operations we want to track. For example, we want to tract when it is used in a SELECT. The following shows how you can set this up for just SELECT.

CREATE AUDIT POLICY oaa_odm_audit_select 
ACTIONS SELECT 
ON MINING MODEL dmuser.high_value_churn_clas_svm;

AUDIT POLICY oaa_odm_audit_select BY oaa_model_user;

The list of individual audit events you can use include:

• AUDIT
• COMMENT
• GRANT
• RENAME
• SELECT

A policy can be setup to tract one or more of these events. For example, if we wanted a policy to track SELECT and GRANT, we would have list each event separated by a comma.

CREATE AUDIT POLICY oaa_odm_audit_select_grant 
ACTIONS SELECT 
ON MINING MODEL dmuser.high_value_churn_clas_svm,
ACTIONS GRANT 
ON MINING MODEL dmuser.high_value_churn_clas_svm,
;

AUDIT POLICY oaa_odm_audit_select_grant BY oaa_model_user;

Renaming & Commenting Oracle Data Mining Models

As your company evolves with their data mining projects, the number of models produced and in use in production will increase dramatically.

Care needs to be taken when it comes to managing these. This includes using meaningful names, adding descriptions of what the model is about or for, and being able to track their usage, etc.

I will look at tracking the usage of the models in another blog post, but the following gives examples of how to rename Oracle Data Mining models and how to add comments or descriptions to these models. This is particularly useful because our data analytics teams have a constant turn over or it has been many months since you last worked on a model and you want a quick idea of what purpose of the model was for.

If you have been using the Oracle Data Mining tool (part of SQL Developer) will will see your model being created with some sort of sequencing numbers. For example for a Support Vector Machine (SVM) model you might see it labelled for classification:

CLAS_SVM_5_22

While you are working on this project you will know and understand what it was about and why it is being used. But afterward you may forget as you will be dealing with many hundreds of models. Yes you could check your documentation for the purpose of this model but that can take some time.

What if you could run a SQL query to find out?

But first we need to rename the model.

DBMS_DATA_MINING.RENAME_MODEL('CLAS_SVM_5_22', 'HIGH_VALUE_CHURN_CLAS_SVM');

Next we will want to add a longer description of what the model is about. We can do this by adding a comment to the model.

COMMENT ON MINING MODEL high_value_churn_clas_svm IS
'Classification Model to Predict High Value Customers most likely to Churn';

We can now see these updated details when we query the Oracle Data Mining models in a user schema.

SELECT model_name, mining_function, algorithm, comments 
FROM user_mining_models;

These are two very useful commands.

12.2 DBaaS (Extreme Edition) possible bug/issue with the DB install/setup

A few weeks ago the 12.2 Oracle Database was released on the cloud. I immediately set an account and got my 12.2 DBaaS setup. This was a relatively painless process and quick.

For me I wanted to test out all the new Oracle Advanced Analytics new features and the new features in SQL Developer 4.2 that only become visible when you are using the 12.2 Database.

When you are go to use the Oracle Data Miner (GUI tool) in SQL Developer 4.2, it will check to see if the ODMr repository is installed in the database. If it isn't then you will be promoted for the SYS password.

This is the problem. In previous version of the DBaaS (12.1, etc) this was not an issue.

When you go to create your DBaaS you are asked for a password that will be used for the admin accounts of the database.

But when I entered the password for SYS, I got an error saying invalid password.

After using ssh to create a terminal connection to the DBaaS I was able to to connect to the container using

sqlplus / as sysdba

and also using

sqlplus sys/ as sysdba

Those worked fine. But when I tried to connect to the PDB1 I got the invalid username and/or password error.

sqlplus sys/@pdb1 as sysdba

I reconnected as follows

sqlplus / as sysdba

and then changed the password for SYS with containers=all

This command completed without errors but when I tried using the new password to connect the the PDB1 I got the same error.

After 2 weeks working with Oracle Support they eventually pointed me to the issue of the password file for the PDB1 was missing. They claim this is due to an error when I was creating/installing the database.

But this was a DBaaS and I didn't install the database. This is a problem with how Oracle have configured the installation.

The answer was to create a password file for the PDB1 using the following

% orapwd file=$ORACLE_HOME/dbs/orapwPDB1 password= entries=10

I then changed the password again for SYS, then tried to connect as SYS to the PDB1, and if by magic I was connected.

I then tried installing the ODMr repository again (in SQL Developer) and when I entered the new password for SYS, it worked !

It's a pity that it took Oracle Support 2 weeks to get me to this point.

As 12.2 is a cloud service hopefully Oracle will get that issue fixed soon so that one one else has to suffer like I did.

Evaluating Cluster Dispersion in Oracle Data Mining

When working with the Clustering algorithms, and particularly k-Means, in the Oracle Data Miner tool there is no way of seeing how compact or dispersed the data is within a cluster.

There are a number of measures typically used in various tools and algorithms, but with Oracle Data Miner we are not presented with any of this information.

But if we flip from using the Oracle Data Miner tool to using SQL we can get to see some more details of the clusters produced by the k-Means algorithm along with some additional and useful information.

As I said there are a number of different measures used to evaluate clusters. The one that Oracle uses is called Dispersion. Now there are a few different definitions of what this could be and I haven't been able to locate what is Oracle's own definition of it in any of the documentation.

We can use the Dispersion value as a measure of how compact or how spread out the data is within a cluster. The Dispersion value is a number greater than 0. The lower the value of the more compact the cluster is i.e. the data points are close the the centroid of the cluster. The larger the value the more disperse or spread out the data points are.

The DBMS_DATA_MINING PL/SQL package comes with a function called GET_MODEL_DETAILS_KM. This function returns a record of the form DM_CLUSTERS.

(id                   NUMBER,
 cluster_id           VARCHAR2(4000),
 record_count         NUMBER,
 parent               NUMBER,
 tree_level           NUMBER,
 dispersion           NUMBER,
 split_predicate      DM_PREDICATES,
 child                DM_CHILDREN,
 centroid             DM_CENTROIDS,
 histogram            DM_HISTOGRAMS,
 rule                 DM_RULE)

We can not use the following query to get the Dispersion value for each of the clusters from an ODM cluster model.

SELECT cluster_id,
       record_count,
       parent,
       tree_level,
       dispersion
FROM  table(dbms_data_mining.get_model_details_km('CLUS_KM_3_2'));