Month: December 2013

BIWA Summit 2014

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The BIWA Summit 2014 is on from January 14th-16th, and is located in the Oracle Conference Center, at Oracle Head Office, in Redwood City (CA, USA). This conference is organised by a very dedicated and experienced group of people, including some very senior people in Oracle who are responsible for various analytics offerings from Oracle.

I presented that this conference last January (2013), and I’ve been tempted into presenting again in January (2014).

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The conference has been expanded with more parallel tracks, a hands-on track, and a meet the experts/presenters session. So lots and lots more content and learning experiences.

I will be giving two presentations. The first one is on how Universities in the UK are using Oracle Data Miner and OBIEE to manage their Student Churn. I gave this presentation at Oracle Open World (Sept, 2013) along with Tony Heljula from Peak Indicators.  This time (Tuesday 14th @10am) I’ll be giving the presentation on my own. My second presentation is a demonstration of how you can use Oracle Data Miner to do Sentiment Analysis using a sample data set from Kaggle (Wednesday 15th @11:15am). I’ve given this presentation a couple of times already and the feedback that I keep on hearing is ‘I didn’t know you could do that in Oracle’. So it is an alternative to using Endeca, R and any of the other tools that we keep on hearing about. Instead we can just use SQL.

If you come to one of my presentations make sure you ask me for one of my Oracle Data Scientist conference ribbons.  I got these made up for Oracle Open World and there was lots of interest in them.

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I’ve agreed to take part in the meet the experts/presenters. This is were attendees at the conference can sign up for a 15 minute 1-to-1 slot with one of the experts/presenters. I’ll be available for this from 3pm on Wednesday 15th. If you would like to sign up for one of these slots then there will be a sign up sheet at the conference. I will be hanging out at the conference for most of the 2.5 days, so do make sure you say hello at some stage.

The full agenda is live (subject to change of course) and can be found by clicking on the image below

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Hopefully I’ll see you there.

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Upgrading to SQL Dev 4 & Oracle Data Miner 4

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The production release of SQL Developer 4 and Oracle Data Miner 4 has just been released. If you are like me you will want to upgrade and start using this latest release. For me I particularly want to be using the new Oracle Data Miner 4.  Over the past (almost) 6 months I’ve been working with the Early Adopter versions (EAs) with some degree of frustration. So hopefully it will be all working now.

To download the production version of SQL Developer 4 that include Oracle Data Miner go to here.

The following are the steps that I followed to get SQL Developer installed and to migrate my Oracle Data Miner Repository.  I’m running a 12.1c Oracle Database.

1. Download and unzip the SQL Developer software. Go to the \sqldeveloper folder to locate the sqldeveloper.exe file. I created a shortcut on my desktop for this. When ready then run this file.

2. As SQL Developer is opening you will get the typical splash screen and at some point you will be asked about migrating your preferences from your previous release. In my case I’m migrating from EA1. I select Yes.

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After a few more seconds SQL Developer should open with all your previous settings.

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3. Now to update and migrate your existing Oracle Data Mining Repository to the new versions. To start this process, to to the Tool Menu and then select Data Miner –> Make Visible

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This will open the Oracle Data Miner Connections tab and the Workflow Jobs tab. If you don’t make do this step then your Oracle Data Miner workflows may not run.

4. Double click on one of your schemas in the Data Miner Connection tab.

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5. Before you upgrade your repository it is advisable to take a full backup of your database, and to export your workflows. Just in case anything might happen during the Repository upgrade. I cannot stress this enough, because during a previous upgrade my repository got wiped and I had to rely on my backups.

5. The version of the repository will be check and if it needs updating then you will get the following window. I’m migrating from EA1 so you might get a slightly different messages. It all depends on what version you were previously using. Select Yes.

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6. Next you will need to give the SYS password (or talk nicely to your DBA). Then you will get a warning about disconnecting your session from the repository. Click OK.

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Then you can click on the Start Button

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Everything should finish after a few minutes.

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7. Open one of your workflows and run it to make sure all is OK.

 

Based on my initial few hours of working with the production version of SQL Developer 4 and Oracle Data Miner 4 is that it seems to run a lot quicker than the Early Adopter versions.

Watch out for some blog posts over the coming weeks about some of the new features that are available in SQL Developer 4.  Like my previous blog posts, the new posts will be how-to type of articles.

Running PL/SQL Procedures in Parallel

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As your data volumes increase, particularly as you evolve into the big data world, you will be start to see that your Oracle Data Mining scoring functions will start to take longer and longer.  To apply an Oracle Data Mining model to new data is a very quick process. The models are, what Oracle calls, first class objects in the database. This basically means that they run Very quickly with very little overhead.

But as the data volumes increase you will start to see that your Apply process or scoring the data will start to take longer and longer. As with all OLTP or OLAP environments as the data grows you will start to use other in-database features to help your code run quicker. One example of this is to use the Parallel Option.

You can use the Parallel Option to run your Oracle Data Mining functions in real-time and in batch processing mode. The examples given below shows you how you can do this.

Let us first start with some basics. What are the typical commands necessary to setup our schema or objects to use Parallel. The following commands are examples of what we can use

ALTER session enable parallel dml;
ALTER TABLE table_name PARALLEL (DEGREE 8);
ALTER TABLE table_name NOPARALLEL;
CREATE TABLE … PARALLEL degree …
ALTER  TABLE … PARALLEL degree …
CREATE INDEX … PARALLEL degree …
ALTER  INDEX … PARALLEL degree …

You can force parallel operations for tables that have a degree of 1 by using the force option.

ALTER SESSION ENABLE PARALLEL DDL;
ALTER SESSION ENABLE PARALLEL DML;
ALTER SESSION ENABLE PARALLEL QUERY;

alter session force parallel query PARALLEL 2

You can disable parallel processing with the following session statements.

ALTER SESSION DISABLE PARALLEL DDL;
ALTER SESSION DISABLE PARALLEL DML;
ALTER SESSION DISABLE PARALLEL QUERY;

We can also tell the database what degree of Parallelism to use

ALTER SESSION FORCE PARALLEL DDL PARALLEL 32;
ALTER SESSION FORCE PARALLEL DML PARALLEL 32;
ALTER SESSION FORCE PARALLEL QUERY PARALLEL 32;

 

Using your Oracle Data Mining model in real-time using Parallel

When you want to use your Oracle Data Mining model in real-time, on one record or a set of records you will be using the PREDICTION and PREDICTION_PROBABILITY function. The following example shows how a Classification model is being applied to some data in a view called MINING_DATA_APPLY_V.

column prob format 99.99999
SELECT cust_id,
       PREDICTION(DEMO_CLASS_DT_MODEL USING *)  Pred,
       PREDICTION_PROBABILITY(DEMO_CLASS_DT_MODEL USING *) Prob
FROM   mining_data_apply_v
WHERE  rownum <= 18
/

   CUST_ID       PRED      PROB
———- ———- ———
    100574          0    .63415
    100577          1    .73663
    100586          0    .95219
    100593          0    .60061
    100598          0    .95219
    100599          0    .95219
    100601          1    .73663
    100603          0    .95219
    100612          1    .73663
    100619          0    .95219
    100621          1    .73663
    100626          1    .73663
    100627          0    .95219
    100628          0    .95219
    100633          1    .73663
    100640          0    .95219
    100648          1    .73663
    100650          0    .60061

If the volume of data warrants the use of the Parallel option then we can add the necessary hint to the above query as illustrated in the example below.

SELECT /*+ PARALLEL(mining_data_apply_v, 4) */
       cust_id,
       PREDICTION(DEMO_CLASS_DT_MODEL USING *)  Pred,
       PREDICTION_PROBABILITY(DEMO_CLASS_DT_MODEL USING *) Prob
FROM   mining_data_apply_v
WHERE  rownum <= 18
/

If you turn on autotrace you will see that Parallel was used. So you should now be able to use your Oracle Data Mining models to work on a Very large number of records and by adjusting the degree of parallelism you can improvements.

Using your Oracle Data Mining model in Batch mode using Parallel

When you want to perform some batch scoring of your data using your Oracle Data Mining model you will have to use the APPLY procedure that is part of the DBMS_DATA_MINING package. But the problem with using a procedure or function is that you cannot give it a hint to tell it to use the parallel option. So unless you have the tables(s) setup with parallel and/or the session to use parallel, then you cannot run your Oracle Data Mining model in Parallel using the APPLY procedure.

So how can you get the DBMA_DATA_MINING.APPLY procedure to run in parallel?

The answer is that you can use the DBMS_PARALLEL_EXECUTE package. The following steps walks you through what you need to do to use the DMBS_PARALLEL_EXECUTE package to run your Oracle Data Mining models in parallel.

The first step required is for you to put the DBMS_DATA_MINING.APPLY code into a stored procedure. The following code shows how our DEMO_CLASS_DT_MODEL can be used by the APPLY procedure and how all of this can be incorporated into a stored procedure called SCORE_DATA.

create or replace procedure score_data
is
begin

dbms_data_mining.apply(
  model_name => ‘DEMO_CLAS_DT_MODEL’,
  data_table_name => ‘NEW_DATA_TO_SCORE’,
  case_id_column_name => ‘CUST_ID’,
  result_table_name => ‘NEW_DATA_SCORED’);

end;
/

Next we need to create a Parallel Task for the DBMS_PARALLEL_EXECUTE package. In the following example this is called ODM_SCORE_DATA.

— Create the TASK
  DBMS_PARALLEL_EXECUTE.CREATE_TASK (‘ODM_SCORE_DATA’);

Next we need to define the Parallel Workload Chunks details

 -- Chunk the table by ROWID
DBMS_PARALLEL_EXECUTE.CREATE_CHUNKS_BY_ROWID('ODM_SCORE_DATA', 'DMUSER', 'NEW_DATA_TO_SCORE', true, 100);
The scheduled jobs take an unassigned workload chunk, process it and will then move onto the next unassigned chunk. 
 
Now you are ready to execute the stored procedure for your Oracle Data Mining model, in parallel by 10.

DECLARE
   l_sql_stmt   varchar2(200);
BEGIN
   — Execute the DML in parallel
   l_sql_stmt := ‘begin score_data(); end;’;
  
   DBMS_PARALLEL_EXECUTE.RUN_TASK(‘ODM_SCORE_DATA’, l_sql_stmt, DBMS_SQL.NATIVE,
                                  parallel_level => 10);
END;
/

When every thing is finished you can then clean up and remove the task using

BEGIN
   dbms_parallel_execute.drop_task(‘ODM_SCORE_DATA’);
END;
/

 

NOTE: The schema that will be running the above code will need to have the necessary privileges to run DBMS_SCHEDULER, for example

grant create job to dmuser;

Non-running workflows in ODMr 4 EA3

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If you are brave enough to be using the early adopter releases of ODMr you may have run into the issue with your workflows not running.

When you go to run your workflow you will get the following window and nothing else happens.

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To get passed this you will need to kill SQL Developer using the task manager or equivalent.

So how do you stop this from happening so that you can get your workflows to run. The simple solutions is that you need to have the workflow tab open for the workflow to run correctly.

To do this you need to make Oracle Data Miner visible, by selecting Tools from the menu, then Data Miner and finally Make Visible

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Then you will need to go to the View menu option, then select Data Miner and then Workflow Jobs

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Now your workflows will work and complete.

Hopefully this will be fixed in the production release of ODMr 4 (SQL Developer 4)