Oracle

18c is now available (but only on the Cloud)

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On Friday afternoon (16th February) we started to see tweets and blog posts from people in Oracle saying that Oracle 18c was now available. But is only available on Oracle Cloud and Engineered Systems.

It looks like we will have to wait until the Autumn before we can install it ourselves on our own servers 😦

Here is the link to the official announcement for Oracle 18c.

Oracle 18c is really Oracle 12.2.0.2. The next full new release of the Oracle database is expected to be Oracle 19.

The new features and incremental enhancements in Oracle 18c are:

  • Multitenant
  • In-Memory
  • Sharding
  • Memory Optimized Fetches
  • Exadata RAC Optimizations
  • High Availability
  • Security
  • Online Partition Merge
  • Improved Machine Learning (OAA)
  • Polymorphic Table Functions
  • Spatial and Graph
  • More JSON improvements
  • Private Temporary Tablespaces
  • New mode for Connection Manager

And now the all important links to the documentation.

Oracle 18c Documentation

Oracle 18c New Features

Oracle 18c Data Warehousing

To give Oracle 18c a try you will need to go to cloud.oracle.com and select Database from the drop down list from the Platform menu. Yes you are going to need an Oracle Cloud account and some money or some free credit. Go and get some free cloud credits at the upcoming Oracle Code events.

If you want a ‘free’ way of trying out Oracle 18c, you can use Oracle Live SQL. They have setup some examples of the new features for you to try.

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NOTE: Oracle 18c is not Autonomous. Check out Tim Hall’s blog posts about this. The Autonomous Oracle Database is something different, and we will be hearing more about this going forward.

Oracle Code Online December 2017

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This week Oracle Code will be having an online event consisting of 5 tracks and with 3 presentations on each track.

This online Oracle Code event will be given in 3 different geographic regions on 12th, 13th and 14th December.

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I’ve been selected to give one of these talks, and I’ve given this talk at some live Oracle Code events and at JavaOne back in October.

The present is pre-recorded and I recorded this video back in September.

I hope to be online at the end of some of these presentations to answer any questions, but unfortunately due to changes with my work commitments I may not be able to be online for all of them.

The moderator for these events will take your questions (or you can send them to me here) and I will write a blog post answering all your questions.

My Oracle Open World 2017 Presentations

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Oracle Open World 2017 will be happening very soon (1st-5th October). Still lots to do before I can get on that plane to San Francisco.

This year I’ll be giving 2 presentations (see table below). One on the Sunday during the User Groups Sunday sessions. I’ve been accepted on the EMEA track. I then get a few days off to enjoy and experience OOW until Thursday when I have my second presentation that is part of JavaOne (I think!)

My OOW kicks off on Friday 29th September with the ACE Director briefing at Oracle HQ, after flying to SFO on Thursday 28th. This year it is only for one day instead of two days. I really enjoy this event as we get to learn and see what Oracle will be announcing at OOW as well as some things that will be coming out during the following few months.

Day Time Presentation Location
Sunday 13:45-14:30 SQL: One Language to Rule All Your Data [OOW SUN1238]

SQL is a very powerful language that has been in use for almost 40 years. SQL comes with many powerful techniques for analyzing your data, and you can analyze data outside the database using SQL as well. Using the new Oracle Big Data SQL it is now possible to analyze data that is stored in a database, in Hadoop, and in NoSQL all at the same time. This session explores the capabilities in Oracle Database that allow you to work with all your data. Discover how SQL really is the unified language for processing all your data, allowing you to analyze, process, run machine learning, and protect all your data.

Hopefully this presentation will be a bit of Fun! For those who have been working with the database for a long time, we can sometimes forget what we can really do. For those starting out in the career may not realise what the database can do. The presentation delivers an important message while having a laugh or two (probably at me).

Marriott Marquis (Golden Gate Level) – Golden Gate C1/C2
Thursday 13:45-14:30 Is SQL the Best Language for Statistics and Machine Learning?

[OOW and JavaOne CON7350]

Did you know that Oracle Database comes with more than 300 statistical functions? And most of these statistical functions are available in all versions of Oracle Database? Most people do not seem to know this. When we hear about people performing statistical analytics, we hear them talking about Excel and R, but what if we could do statistical analysis in the database without having to extract any data onto client machines? This presentation explores the various statistical areas available in Oracle Database and gives several demonstrations. We can also greatly expand our statistical capabilities by using Oracle R Enterprise with the embedded capabilities in SQL.

This presentation is just one of the 14 presentations that are scheduled for the Thursday! I believe this session is already fully booked, but you can still add yourself to the wait list.

Marriott Marquis (Golden Gate Level) – Golden Gate B

My flights and hotel have been paid by OTN as part of the Oracle ACE Director program. Yes this costs a lot of money and there is no way I’d be able to pay these costs. Thank you.

My diary for OOW is really full. No it is completely over booked. It is just mental. Between attending conference session, meeting with various product teams (we only get to meet at OOW), attending various community meet-ups, this year I get to attend some events for OUG leaders (representing UKOUG), spending some time on the EMEA User Group booth, various meetings with people to discuss how they can help or contribute to the UKOUG, then there is Oak Table World, trying to check out the exhibition hall, spend some time at the OTN/ODC hangout area, getting a few OTN t-shirts, doing some book promotions at the Oracle Press shop, etc., etc., etc. I’m exhausted just thinking about it. Mosts days start at 7am and then finish around 10pm.

I’ll need a holiday when I get home! but it will be straight back to work 😦

If you are at OOW and want to chat then contact me via DM on Twitter or WhatsApp (these two are best) or via email (this will be the slowest way).

I’ll have another blog post listing the presentations from various people and partners from the Republic of Ireland who are speaking at OOW.

My Oracle Open World 2017 Presentations

Posted on

Oracle Open World 2017 will be happening very soon (1st-5th October). Still lots to do before I can get on that plane to San Francisco.

This year I’ll be giving 2 presentations (see table below). One on the Sunday during the User Groups Sunday sessions. I’ve been accepted on the EMEA track. I then get a few days off to enjoy and experience OOW until Thursday when I have my second presentation that is part of JavaOne (I think!)

My OOW kicks off on Friday 29th September with the ACE Director briefing at Oracle HQ, after flying to SFO on Thursday 28th. This year it is only for one day instead of two days. I really enjoy this event as we get to learn and see what Oracle will be announcing at OOW as well as some things that will be coming out during the following few months.

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Day Time Presentation Location
Sunday 13:45-14:30 SQL: One Language to Rule All Your Data [OOW SUN1238]

SQL is a very powerful language that has been in use for almost 40 years. SQL comes with many powerful techniques for analyzing your data, and you can analyze data outside the database using SQL as well. Using the new Oracle Big Data SQL it is now possible to analyze data that is stored in a database, in Hadoop, and in NoSQL all at the same time. This session explores the capabilities in Oracle Database that allow you to work with all your data. Discover how SQL really is the unified language for processing all your data, allowing you to analyze, process, run machine learning, and protect all your data.

Hopefully this presentation will be a bit of Fun! For those who have been working with the database for a long time, we can sometimes forget what we can really do. For those starting out in the career may not realise what the database can do. The presentation delivers an important message while having a laugh or two (probably at me).

Marriott Marquis (Golden Gate Level) – Golden Gate C1/C2
Thursday 13:45-14:30 Is SQL the Best Language for Statistics and Machine Learning?

[OOW and JavaOne CON7350]

Did you know that Oracle Database comes with more than 300 statistical functions? And most of these statistical functions are available in all versions of Oracle Database? Most people do not seem to know this. When we hear about people performing statistical analytics, we hear them talking about Excel and R, but what if we could do statistical analysis in the database without having to extract any data onto client machines? This presentation explores the various statistical areas available in Oracle Database and gives several demonstrations. We can also greatly expand our statistical capabilities by using Oracle R Enterprise with the embedded capabilities in SQL.

This presentation is just one of the 14 presentations that are scheduled for the Thursday! I believe this session is already fully booked, but you can still add yourself to the wait list.

Marriott Marquis (Golden Gate Level) – Golden Gate C3

My flights and hotel have been paid by OTN as part of the Oracle ACE Director program. Yes this costs a lot of money and there is no way I’d be able to pay these costs. Thank you.

My diary for OOW is really full. No it is completely over booked. It is just mental. Between attending conference session, meeting with various product teams (we only get to meet at OOW), attending various community meet-ups, this year I get to attend some events for OUG leaders (representing UKOUG), spending some time on the EMEA User Group booth, various meetings with people to discuss how they can help or contribute to the UKOUG, then there is Oak Table World, trying to check out the exhibition hall, spend some time at the OTN/ODC hangout area, getting a few OTN t-shirts, doing some book promotions at the Oracle Press shop, etc., etc., etc. I’m exhausted just thinking about it. Mosts days start at 7am and then finish around 10pm.

I’ll need a holiday when I get home! but it will be straight back to work 😦

If you are at OOW and want to chat then contact me via DM on Twitter or WhatsApp (these two are best) or via email (this will be the slowest way).

I’ll have another blog post listing the presentations from various people and partners from the Republic of Ireland who are speaking at OOW.

Cluster Distance using SQL with Oracle Data Mining – Part 4

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This is the fourth and last blog post in a series that looks at how you can examine the details of predicted clusters using Oracle Data Mining. In the previous blog posts I looked at how to use CLUSER_ID, CLUSTER_PROBABILITY and CLUSTER_SET.

In this blog post we will look at CLUSTER_DISTANCE. We can use the function to determine how close a record is to the centroid of the cluster. Perhaps we can use this to determine what customers etc we might want to focus on most. The customers who are closest to the centroid are one we want to focus on first. So we can use it as a way to prioritise our workflows, particularly when it is used in combination with the value for CLUSTER_PROBABILITY.

Here is an example of using CLUSTER_DISTANCE to list all the records that belong to Cluster 14 and the results are ordered based on closeness to the centroid of this cluster.

SELECT customer_id, 
       cluster_probability(clus_km_1_37 USING *) as cluster_Prob,
       cluster_distance(clus_km_1_37 USING *) as cluster_Distance
FROM   insur_cust_ltv_sample
WHERE   cluster_id(clus_km_1_37 USING *) = 14
order by cluster_Distance asc;

Here is a subset of the results from this query.

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When you examine the results you may notice that the records that is listed first and closest record to the centre of cluster 14 has a very low probability. You need to remember that we are working in a N-dimensional space here. Although this first record is closest to the centre of cluster 14 it has a really low probability and if we examine this record in more detail we will find that it is at an overlapping point between a number of clusters.

This is why we need to use the CLUSTER_DISTANCE and CLUSTER_PROBABILITY functions together in our workflows and applications to determine how we need to process records like these.

Cluster Sets using SQL with Oracle Data Mining – Part 3

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This is the third blog post on my series on examining the Clusters that were predicted by an Oracle Data Mining model. Check out the previous blog posts.

In the previous posts we were able to list the predicted cluster for each record in our data set. This is the cluster that the records belonged to the most. I also mentioned that a record could belong to many clusters.

So how can you list all the clusters that the a record belongs to?

You can use the CLUSTER_SET SQL function. This will list the Cluster Id and a probability measure for each cluster. This function returns a array consisting of the set of all clusters that the record belongs to.

The following example illustrates how to use the CLUSTER_SET function for a particular cluster model.

SELECT t.customer_id, s.cluster_id, s.probability
FROM   (select customer_id, cluster_set(clus_km_1_37 USING *) as Cluster_Set
        from   insur_cust_ltv_sample 
        WHERE  customer_id in ('CU13386', 'CU100')) T,
      TABLE(T.cluster_set) S
order by t.customer_id, s.probability desc; 

The output from this query will be an ordered data set based on the customer id and then the clusters listed in descending order of probability. The cluster with the highest probability is what would be returned by the CLUSTER_ID function. The output from the above query is shown below.

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If you would like to see the details of each of the clusters and to examine the differences between these clusters then you will need to use the CLUSTER_DETAILS function (see previous blog post).

You can specify topN and cutoff to limit the number of clusters returned by the function. By default, both topN and cutoff are null and all clusters are returned.

– topN is the N most probable clusters. If multiple clusters share the Nth probability, then the function chooses one of them.

– cutoff is a probability threshold. Only clusters with probability greater than or equal to cutoff are returned. To filter by cutoff only, specify NULL for topN.

You may want to use these individually or combined together if you have a large number of customers. To return up to the N most probable clusters that are greater than or equal to cutoff, specify both topN and cutoff.

The following example illustrates using the topN value to return the top 4 clusters.

SELECT t.customer_id, s.cluster_id, s.probability
FROM   (select customer_id, cluster_set(clus_km_1_37, 4, null USING *) as Cluster_Set
        from   insur_cust_ltv_sample 
        WHERE  customer_id in ('CU13386', 'CU100')) T,
      TABLE(T.cluster_set) S
order by t.customer_id, s.probability desc;

and the output from this query shows only 4 clusters displayed for each record.

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Alternatively you can select the clusters based on a cut off value for the probability. In the following example this is set to 0.05.

SELECT t.customer_id, s.cluster_id, s.probability
FROM   (select customer_id, cluster_set(clus_km_1_37, NULL, 0.05 USING *) as Cluster_Set
        from   insur_cust_ltv_sample 
        WHERE  customer_id in ('CU13386', 'CU100')) T,
      TABLE(T.cluster_set) S
order by t.customer_id, s.probability desc;

and the output this time looks a bit different.

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Finally, yes you can combine these two parameters to work together.

SELECT t.customer_id, s.cluster_id, s.probability
FROM (select customer_id, cluster_set(clus_km_1_37, 2, 0.05 USING *) as Cluster_Set
from insur_cust_ltv_sample
WHERE customer_id in (‘CU13386’, ‘CU100’)) T,
TABLE(T.cluster_set) S
order by t.customer_id, s.probability desc;

Examining predicted Clusters and Cluster details using SQL

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In a previous blog post I gave some details of how you can examine some of the details behind a prediction made using a classification model. This seemed to spark a lot of interest. But before I come back to looking at classification prediction details and other information, this blog post is the first in a 4 part blog post on examining the details of Clusters, as identified by a cluster model created using Oracle Data Mining.

The 4 blog posts will consist of:

  • 1 – (this blog post) will look at how to determine the predicted cluster and cluster probability for your record.
  • 2 – will show you how to examine the details behind and used to predict the cluster.
  • 3 – A record could belong to many clusters. In this blog post we will look at how you can determine what clusters a record can belong to.
  • 4 – Cluster distance is a measure of how far the record is from the cluster centroid. As a data point or record can belong to many clusters, it can be useful to know the distances as you can build logic to perform different actions based on the cluster distances and cluster probabilities.

Right. Let’s have a look at the first set of these closer functions. These are CLUSTER_ID and CLUSTER_PROBABILITY.

CLUSER_ID : Returns the number of the cluster that the record most closely belongs to. This is measured by the cluster distance to the centroid of the cluster. A data point or record can belong or be part of many clusters. So the CLUSTER_ID is the cluster number that the data point or record most closely belongs too.

CLUSTER_PROBABILITY : Is a probability measure of the likelihood of the data point or record belongs to a cluster. The cluster with the highest probability score is the cluster that is returned by the CLUSTER_ID function.

Now let us have a quick look at the SQL for these two functions. This first query returns the cluster number that each record most strong belongs too.

SELECT customer_id, 
       cluster_id(clus_km_1_37 USING *) as Cluster_Id, 
FROM   insur_cust_ltv_sample
WHERE  customer_id in ('CU13386', 'CU6607', 'CU100');

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Now let us add in the cluster probability function.

SELECT customer_id, 
       cluster_id(clus_km_1_37 USING *) as Cluster_Id,
       cluster_probability(clus_km_1_37 USING *) as cluster_Prob       
FROM   insur_cust_ltv_sample
WHERE  customer_id in ('CU13386', 'CU6607', 'CU100');

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These functions gives us some insights into what the cluster predictive model is doing. In the remaining blog posts in this series I will look at how you can delve deeper into the predictions that the cluster algorithm is make.

Oracle Data Visualization Desktop – now available

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After a bit of a long wait Oracle have finally release Oracle Data Visualization for the desktop. The desktop version of this tool is only available for Windows desktops at the moment. I’m sure Oracle will be bringing out versions of other OS soon (I hope).

To get you hands on the Oracle Data Visualization to to the following OTN webpage (click on this image)

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After downloading has finished, you can run the installer.

When the Oracle Installer opens you will be prompted to enter the required details or to accept the defaults, as outlined below.

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  • Installation Location : Decide where you are going to have the Oracle Data Visualization tool installed on your desktop. The default location is C:\Program Files\Oracle Data Visualization Desktop . Click Next
  • Options : There are 2 check boxes for ‘Create desktop shortcut’ and ‘Deploy samples’. Leave both of these checked, as you will probably want these. Click Next.
  • Summary : Lists a summary of the installation. There is nothing really for you to do here, so on the Install button.
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  • Progress : You can ten sit back and monitor the progress of the installation. The installation tool about 4 minutes on my small Windows VM
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When the installation is complete you can now fire up Oracle Data Visualization and enjoy. If you have just installed the tool it will automatically be started for you.

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When the tool has finished all the configurations that it needs to do, the tool will open with the following window and shows a sample projects for you to get an idea of some of the things that are possible.

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For more details on the tool and on the Oracle Cloud hosted version click on the following image to get to the Oracle webpage for the product.

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Oracle Magazine – March/April 2001

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The headline articles of Oracle Magazine for March/April 2001 were on using Oracle 9i Application server to deliver e-business and web based applications. There was some case studies of companies using this technologies including Tantalus Communications, Digital River Commerce System, Tomatoland.com and Oracle themselves.

OM 2001 March April

Other articles included:

  • Tom Kyte’s column looked at tips on automation, cleanup and database maintenance. Some of the details included index rebuilds, indexing interMedia files, killing and cleaning up sessions, how to specify the column at runtime in an order by, and how to use DBMS_JOB for database maintenance.
  • Oracle announces the release of PORTAL.ORACLE.COM and MY.ORACLE.COM.
  • Fre Sansmark has an article on Database Benchmarking and discusses what it means and how well they address real-world performance questions.
  • Understanding XML Standards gives a brief introduction to what XML is about, explains the three layers of XML Grammar, XML based Protocols and XML Vocabularies. .
  • Part 3 of ‘Exploring Oracle Text Basics’ looks at text searching and comparisons, creating, indexing and loading data.
  • Creating Updatable Views explores the various requirements for creating an View that can be used to update data that is based on a single table or based on the joining of multiple tables..
  • Linking to Remote Databases explores the basics of Database Links and that the DBA needs to know to setup and manages these..
  • Steven Feuerstein’s article looks at Advanced Native Dynamic SQL and the use of bind variables and their limitations.

To view the cover page and the table of contents click on the image at the top of this post or click here.

My Oracle Magazine Collection can be found here. You will find links to my blog posts on previous editions and a PDF for the very first Oracle Magazine from June 1987.

Loading JSON data into Oracle using ROracle and jsonlite

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In this post I want to show you one way of taking a JSON file of data and loading it into your Oracle schema using ROracle. The JSON data will then be used to create a table in your schema. Yes you could use other methods to connect to the database and to create the table. But ROracle is by far the fastest method of connecting, selecting and processing data.

1. Necessary R Packages

You will need two R library. The first of these is the ROracle package. This gives us all the connection and data processing commands to work with the Oracle database. The second package is the jsonlite R package. This package allows us to open, read and process a file that has JSON data.

> install.package(“ROracle”)

> install.package(“jsonlite”)

After you have installed the packages you can now load them into your R environment so that you can use them in your current session.

> library(ROracle)

> library(jsonlite)

Depending on your version of R you may get some working messages about the libraries being built under a different version of R. Then again maybe you won’t get these 🙂

2. Open & Read the JSON file in R

Now you are ready to name and open the file that contains your JSON data. In my case the file is called ‘demo_json_data.json’

> jsonFile <- "c:/app/demo_json_data.json"

> jsonData <- fromJSON(jsonFile)

We now have the JSON data loaded into R. We can now look at the attributes of each JSON record and the number of records that was in the JSON file.

> names(jsonData$items)

[1] “cust_id” “cust_gender” “age”

[4] “cust_marital_status” “country_name” “cust_income_level”

[7] “education” “occupation” “household_size”

[10] “yrs_residence” “affinity_card” “bulk_pack_diskettes”

[13] “flat_panel_monitor” “home_theater_package” “bookkeeping_application”

[16] “printer_supplies” “y_box_games” “os_doc_set_kanji”

> nrow(jsonData$items)

[1] 1500

As you can see the records are grouped under a higher label of ‘items’. You might want to extract these records into a new data frame.

> data <- jsonData$items

>

Now we have our data ready in a data frame and we can use this data frame to create a table and insert the data.

3. Create the connection to the Oracle Schema

I have a previous post on connecting to an Oracle Schema using ROracle. That was connecting to an 11g Oracle Database.

JSON is a new feature in Oracle 12c and the connection details are a little bit different because we are now having to deal with connection to a pluggable database. The following illustrates connecting to a 12c database and assumes you have Oracle Client already installed and configured with your tnsnames.ora entry.

# Create the connection string

> host <- "localhost"

> port <- 1521

> service <- "pdb12c"

> connect.string <- paste(

“(DESCRIPTION=”,

“(ADDRESS=(PROTOCOL=tcp)(HOST=”, host, “)(PORT=”, port, “))”,

“(CONNECT_DATA=(SERVICE_NAME=”, service, “)))”, sep = “”)

> con2 <- dbConnect(drv, username = "dmuser", password = "dmuser",dbname=connect.string)

>

4. Create the table in your Oracle Schema

At this point we have our connection to our Oracle Schema setup and connected, we have read in the JSON file and we have the JSON data in a data frame. We are now ready to push the JSON data to a table in our schema.

> dbWriteTable(con, “JSON_DATA”, overwrite=TRUE, value=data)

Job done 🙂

The table JSON_DATA has been created and the data is stored in the table in typical table attributes and rows format.

One thing to watch our for with the above command is with the overwrite=TRUE parameter setting. This replaces a table if it already exists. So your old data will be gone. Be careful.

5. View and Query the data using SQL

When you now log into your schema in the 12c Database, you can now query the data in the JSON_DATA table. (Yes I know it is not in JSON format in this table).

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How did I get/generate my JSON data?

I generated the JSON file using a table that I already had in one of my schemas. This table is part of the sample data set that is built on top of the Oracle sample schemas.

The image below shows the steps involved in generating the data in JSON format. I used SQL Developer and set the SQLFORMAT to be JSON. I then ran the query to select the data. You will need to run this as a script. Then copy the JSON data and paste it into a file.

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The SQL FORMAT command sets the output format for a query back to the default query output format that we are well use to.

A nice little JSON viewer can be found at http://jsonviewer.stack.hu/

Copy and paste your JSON data into this and you can view the structure of the data. Check it out.

Pulling Large Database tables in R

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As the volume of the data in your tables grows, particularly in the big data world, you may run into some memory issues or package restrictions with pulling down the tables to your R environment.

Some of the R packages and drivers have some recommended numbers or limits for the number of records that can be fetched.

Caveate: My laptop is a Mac and at this point in time the ROracle package is unavailable for a Mac. It is for Windows, Solaris and AIX.

In the following example I’m looking at downloading a table with 300K records from an Oracle Database. I’ve already setup my DB connection using the Oracle JDBC driver. But when I run the following command I get an error.

> res<-dbSendQuery(jdbcConnection, "select * from my_large_table")

> dbFetch(res)

Error in .jcall(rp, “I”, “fetch”, stride) :

    java.lang.OutOfMemoryError: Java heap space

I also get a similar error if I run the following command.

> train_data <- dbReadTable(jdbcConnection, "MY_LARGE_TABLE")

How can you pull down a large table in R? So that you are not restricted to memory restrictions or limits on the number of records.

One way to do this is to loop through the data, pull the records down in chunks (a certain fetch size), put these into an array, and then merge them all together into a data frame. The following code illustrates how to do this.

> res<-dbSendQuery(jdbcConnection, "select * from my_large_table")

> dbFetch(res)

> rm(result)

> result<-list()

> i=1

> result[[i]]<-dbFetch(res,n=1000)

> while(nrow(chunk 0){

+     i<-i+1

+     result[[i]]<-chunk

+ }

> train_data<-do.call(rbind,result)

The above code runs surprisingly quickly, generate no errors and I now have all the data I need in my R environment.

The fetch size in the above example is set to 1000. This is a bit small really and is only set to that for illustration purposes here. You will need to play with this size to find out what size works best for your environment.

As with all programming languages and with R too there can be many different ways of performing the same thing.

2014 A review of the year as an ACED

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As 2014 draws to a close I working on finishing off a number of tasks and projects. One of these tasks is an annual one for me. The task is to list all the things I’ve done as an Oracle ACE Director. If has been a very busy year, not just with ACE activities but also work wise too. That will explain why I have been a bit quiet on the blogging side of things in recent months.

In 2014 I one major highlight. It was the publication of my book Predictive Analytics using Oracle Data Miner by Oracle Press. Many thanks for everyone involved in writing this book, especially my family and the people in Oracle Press who gave me the opportunity.

Here is my summary.

Conferences

  • January : BIWA Summit : 2 presentations (San Francisco, USA) **

  • March : OUG Ireland Conference (Dublin, Ireland)

  • April : OUG Norway : 2 presentations (Oslo, Norway) **

  • June : OUG Finland : 2 presentations (Helsinki, Finland) **

  • June : Oracle EMEA Data Warehousing Global Leaders Forum (Dublin, Ireland)

  • August : OUG Panama : 2 presentations (Panama City, Panama) **

  • August : OUG Costa Rica : 3 presentations (San Jose, Costa Rica) **

  • August : OUG Mexico : 2 presentations (Mexico City, Mexico) **

  • September : Oracle Open World (San Francisco, USA) **

  • December : UKOUG Tech15 : 2 presentations (Liverpool, UK)

  • December : UKOUG Apps15 (Liverpool, UK)

That is 19 hours of presenting this year.

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

My ODM Book

On the 8th August my book titled Predictive Analytics using Oracle Data Miner, was published by Oracle Press. It all began 12 months and 2 weeks previously. I had the book written and the technical edits done by the middle of February (2014). Between March and June the Copy edits and layouts where completed. The book is ideal for any data scientist, Oracle developer, Oracle architect and Oracle DBA, who want to use the in-databse data mining functionality. That way they can use and build upon their existing SQL and PL/SQL skills to perform predictive analytics.

The book is available on Amazon and comes in Print and eBook formats

Book Cover

Oracle Open World

This year I got to go to my second ACE Director briefing. This is held on the Thursday and Friday before OOW. At the briefing we get lots of Very senior people coming in to tell us what is happening with the products in their area and what the plans are over the next 12 to 18 months. Lots of what we are told is all under NDA. My favourite part of this briefing is when Thomas Kurian comes in and talks for about 90 minutes. No slides, no notes. The first 15 minutes is him telling us what Larry & Co are going to announce at OOW, that are the main product directions etc. Then he opens to the floor for questions. You can ask him anything about the set of Oracle products (>3000) and he will explain in detail what is happen. He even commented on the plans for the Oracle Games Console this year!!!

This year I had the opportunity to present at OOW again. It was a joint presentation with Roel Hartman and we had the pleasure of being one of the first presentations at OOW at 8:30am on the Sunday morning. Despite the early start we have really good turn out for our presentation.

Then I got to enjoy OOW with all the various activities, presentations, entertainment and hanging out at the OTN lounge with the other ACEs and ACEDs.

Blog Posts

One of the things I really like doing is playing with various features of Oracle and then writing some blog posts about them. Most of what I blog about evolves around the SQL & PL/SQL Statistics functions and the Advanced Analytics Option, comprising Oracle Data Mining and Oracle R Enterprise. In addition to these blog posts I also have posts relating to various Oracle User Group activities. So there is a good mixture of material on the blog.

In 2014 I have written 60 blog posts (including this one). This number is a little be less than previous years and perhaps the main reason for that is due to me being extremely busy with various project work this year.

OTN Articles

OTN has accepted three articles from me in 2014. I was delighted about these acceptances and I’m looking forward to writing some more articles in 2015 for them.

  • Sentiment Analysis using Oracle Data Miner
  • ROracle : How to get Started and Commands you need to Know
  • Predictive Queries in 12c

I have a few more ideas for articles and I will be writing these in 2015. We will have to wait and see if OTN will accept them.

My Oracle Magazine Collection & Reviews

You may or may not be aware that I’ve been collecting Oracle Magazine for over 20 years now. I have nearly the entire collection of Oracle Magazine going back to the very first edition. Check out the collection here. You will see that I’m missing a few and these are highlighted by the grey boxes. If you do have any of these and you would like to donate to my collection then please get in touch.

One of the things I like to blog about is on some of these old Oracle Magazines. If you go to my Oracle Magazine collection page you will see the past editions that I have writing a review of. Click on the links to view the blog post review an edition.

In 2014 I have written reviews of the following:

OUG Activities

The Oracle User Group in Ireland (OUG Ireland) has continued to grow this year in membership but also with the number of attendees at our events. In March of each year we have our flagship event which is our annual conference. This year we have almost 300 people and unfortunately people had to turned away at the door because we had headed the maximum limit on the number of attendees for the event. Planing has already commenced for 2015 and the call for presentations is now open. Hopefully 2015 will be bigger and better that 2014. We had a second day at the conference this year where we had Tom Kyte give a full day seminar. Again this was fully booked out for weeks/months before hand. In March 2015 we will be having a second day of the conference with Maria Colgan giving a one day workshop/seminar on the In-Memory option and the Optimiser. You cannot book your place on this seminar yet but then it does open make sure to book your place quick as I’m sure it will book out very quickly.

We also had a number of TECH and BI SIGs and the number of attendees has significantly grown over the past few years. This is fantastic and hopefully this will continue. If it does then maybe we might be able to put on more SIG events.

In the editor of Oracle Scene Magazine which is published by the UKOUG. This was my first full year as editor after spending many years as deputy editor. In 2014 we have published three editions of Oracle Scene and I would like to thanks everyone who has submitted an article. You have helped grow the quality of the contents and also grow the readership numbers. The calls for articles for the Spring edition is now open.

My Oracle Data Science newsletter & My Oracle User Group Weekly newsletter

A couple of years ago I set up a news aggregator based on Twitter feeds and on updates from certain websites. I’ve divided these into two different newsletters. The first is My Oracle Data Science News and as you might guess it is focused on the worlds of Data Science, Predictive Analytics and related developments with a bit of a focus towards the Oracle world. This newsletter gets published each day.

My second newsletter is focused on Oracle User Group activities around the World and is again based on the various Twitter handles of the Oracle User Groups. I’m include over 40 OUG Twitter handles in the aggregator so I should be picking up almost everyone. If you discover your OUG is not being included then drop me an email and I’ll add you to the list. This newsletter goes out every Friday.

Plans for 2015 so far

The start of 2015 is already very busy and I’m already booked for 3 conferences BIWA Summit (CA, USA), OUG Norway and OUG Ireland.

Planing for OUG Ireland is under ways and we are hoping to build on the successes we have had over the past few years.

So as editor of Oracle Scene magazine we are planning for our first issue in 2015, the call for articles is open and we have been busy recruiting authors of articles on specifics.

I’m sure I’ve forgotten a few things, I usually do.

It has been a fun year. I’ve made lots of friends around the World and I look forward to meeting you all at some conference in 2015.