Saturday, October 27, 2012

Take Advantage of Materialized View

Materialized view is one of the most useful features for data processing in Oracle. We would suggest that materialized views be used when possible.

To create a materialized view, we use "create materialized view as select.. ", just as when we create a view or table. For example, the following SQL script creates a materialized view that calculates the following bank card summary information for each retailer terminal: the number of transactions, amount of transactions and number of unique cards.

create materialized view mv_retailer_terminal_sts
terminal_id ,
retailer_id ,
terminal_state ,
count(1) number_of_txn ,
sum(tran_amt) amount_of_transaction,
count(distinct card_key) number_of_cards
from credit_card_txn_detail a
group by
terminal_id ,
retailer_id ,
terminal_state ,

The materialized view captures a snapshot of the "from " tables. It can be refreshed later manually on demand or based on a defined schedule.

For example, we can refresh a materialized view manually using the following command.
execute DBMS_MVIEW.REFRESH('mv_retailer_terminal_sts','C');
('C') means complete refresh.

One of the advantages of using materialized view is that the SQL query used to produce it can be retrieved using the following query:
select query from user_mviews where mview_name=upper('mv_retailer_terminal_sts');

The difference between a view and a materialized view is that a materialized view creates a physical table. Thus a materialized view is faster to query than a view. Thus we suggest that materialized views be used when possible in replacement of tables.

Sunday, October 21, 2012

Oracle Normal Distribution Function

Oracle function dbms_random.normal generates a standard normal distribution number with zero mean and one standard deviation.
SQL> select dbms_random.normal from dual;
The following query generates 6,000 random numbers using dbms_random.normal and then calculate their mean and standard deviation.We can see that their mean is close to zero and standard deviation close to one.
SQL> select avg(v), stddev(v), count(1) from (select dbms_random.normal v from V_6K_OBS);
---------- ---------- ----------
-.00110804 1.00954138 6000

Wednesday, October 03, 2012

More on random sampling in Oracle

The earlier post Random Sampling using SQL uses dbms_random.random to generate random numbers. A better function is dbms_random.value which generates uniformly distributed random number greater than or equal to 0 and less than 1.
We can rewrite random sampling scripts as the following.
Step 1 . Create random numbers.
create table tbl_app_id_w_rnd as select app_id, dbms_random.value rnd from CELL_PHONE_SERVICE_APPS;
Step 2. Create a view that contains 30% of the records.
create view v_data_testing as select a.* from CELL_PHONE_SERVICE_APPS a, tbl_app_id_w_rnd b where a.app_id=b.app_id and rnd <=0.3;