Sunday, February 18, 2018

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

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.

Tuesday, February 13, 2018

Oracle and Python setup with cx_Oracle

Is Python the new R?

Maybe, maybe not, but that I'm finding in recent months is more companies are asking me to use Python instead of R for some of my work.

In this blog post I will walk through the steps of setting up the Oracle driver for Python, called cx_Oracle. The documentation for this drive is good and detailed with plenty of examples available on GitHub. Hopefully there isn't anything new in this post, but it is my experiences and what I did.

1. Install Oracle Client
The Python driver requires Oracle Client software to be installed. Go here, download and install. It's a straightforward install. Make sure the directories are added to the search path.

2. Download and install cx_Oracle
You can use pip3 to do this.
 
pip3 install cx_Oracle

Collecting cx_Oracle
  Downloading cx_Oracle-6.1.tar.gz (232kB)
    100% |████████████████████████████████| 235kB 679kB/s
Building wheels for collected packages: cx-Oracle
  Running setup.py bdist_wheel for cx-Oracle ... done
  Stored in directory: /Users/brendan.tierney/Library/Caches/pip/wheels/0d/c4/b5/5a4d976432f3b045c3f019cbf6b5ba202b1cc4a36406c6c453
Successfully built cx-Oracle
Installing collected packages: cx-Oracle
Successfully installed cx-Oracle-6.1  

3. Create a connection in Python
Now we can create a connection. When you see some text enclosed in angled brackets <>, you will need to enter your detailed for your schema and database server.
 
# import the Oracle Python library
import cx_Oracle

# define the login details
p_username = ""
p_password = ""
p_host = ""
p_service = ""
p_port = "1521"

# create the connection
con = cx_Oracle.connect(user=p_username, password=p_password, dsn=p_host+"/"+p_service+":"+p_port)

# an alternative way to create the connection
# con = cx_Oracle.connect('/@/:1521')

# print some details about the connection and the library
print("Database version:", con.version)
print("Oracle Python version:", cx_Oracle.version)


Database version: 12.1.0.1.0
Oracle Python version: 6.1

4. Query some data and return results to Python
In this example the query returns the list of tables in the schema.
 
# define a cursor to use with the connection
cur = con.cursor()
# execute a query returning the results to the cursor
cur.execute('select table_name from user_tables')
# for each row returned to the cursor, print the record
for row in cur:
    print("Table: ", row)

Table:  ('DECISION_TREE_MODEL_SETTINGS',)
Table:  ('INSUR_CUST_LTV_SAMPLE',)
Table:  ('ODMR_CARS_DATA',)

Now list the Views available in the schema.
 
# define a second cursor
cur2 = con.cursor()
# return the list of Views in the schema to the cursor
cur2.execute('select view_name from user_views')
# display the list of Views
for result_name in cur2:
    print("View: ", result_name)

View:  ('MINING_DATA_APPLY_V',)
View:  ('MINING_DATA_BUILD_V',)
View:  ('MINING_DATA_TEST_V',)
View:  ('MINING_DATA_TEXT_APPLY_V',)
View:  ('MINING_DATA_TEXT_BUILD_V',)
View:  ('MINING_DATA_TEXT_TEST_V',)

5. Query some data and return to a Panda in Python
Pandas are commonly used for storing, structuring and processing data in Python, using a data frame format. The following returns the results from a query and stores the results in a panda.
 
# in this example the results of a query are loaded into a Panda
# load the pandas library
import pandas as pd

# execute the query and return results into the panda called df
df = pd.read_sql_query("SELECT * from INSUR_CUST_LTV_SAMPLE", con)

# print the records returned by query and stored in panda
print(df.head())

 CUSTOMER_ID     LAST    FIRST STATE     REGION SEX    PROFESSION  \
0     CU13388     LEIF   ARNOLD    MI    Midwest   M        PROF-2   
1     CU13386     ALVA   VERNON    OK    Midwest   M       PROF-18   
2      CU6607   HECTOR  SUMMERS    MI    Midwest   M  Veterinarian   
3      CU7331  PATRICK  GARRETT    CA       West   M       PROF-46   
4      CU2624  CAITLYN     LOVE    NY  NorthEast   F      Clerical   

  BUY_INSURANCE  AGE  HAS_CHILDREN   ...     MONTHLY_CHECKS_WRITTEN  \
0            No   70             0   ...                          0   
1            No   24             0   ...                          9   
2            No   30             1   ...                          2   
3            No   43             0   ...                          4   
4            No   27             1   ...                          4   

   MORTGAGE_AMOUNT  N_TRANS_ATM  N_MORTGAGES  N_TRANS_TELLER  \
0                0            3            0               0   
1             3000            4            1               1   
2              980            4            1               3   
3                0            2            0               1   
4             5000            4            1               2   

  CREDIT_CARD_LIMITS  N_TRANS_KIOSK  N_TRANS_WEB_BANK       LTV  LTV_BIN  
0               2500              1                 0  17621.00   MEDIUM  
1               2500              1               450  22183.00     HIGH  
2                500              1               250  18805.25   MEDIUM  
3                800              1                 0  22574.75     HIGH  
4               3000              2              1500  17217.25   MEDIUM  

[5 rows x 31 columns]

6. Wrapping it up and closing things
Finally we need to wrap thing up and close our cursors and our connection to the database.
 
# close the cursors
cur2.close()
cur.close()

# close the connection to the database
con.close()

Useful links
cx_Oracle website
cx_Oracle documentation
cx_Oracle examples on GitHub

Watch out for more blog posts on using Python with Oracle, Oracle Data Mining and Oracle R Enterprise.

Thursday, January 4, 2018

Relation Theory videos by CJ Date

Here is a series of videos by CJ Date on Relational Theory.

Introduction video

An Introduction to set theory (videos on O'Reilly website)

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Nullology (videos on O'Reilly website)

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Nulls, Three-Valued Logic, and Missing Information (videos on O'Reilly website)

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The Closed World Assumption (videos on O'Reilly website)

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View Updating (videos on O'Reilly website)

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