Archive for the ‘Oracle DBA’ tag
Oracle Partitioned Tables
Oracle Partitioned Tables
Learning Outcomes
- Learn about List Partitioning.
- Learn about Range Partitioning.
- Learn about Hash Partitioning.
- Learn about Composite Partitioning.
Lesson Material
Partitioning is the process of breaking up a data source into a series of data sources. Partitioned tables are faster to access and transact against. Partitioning data becomes necessary as the amount of data grows in any table. It speeds the search to find rows and insert, update, or delete rows.
Oracle Database 21c supports four types of table partitioning: list, range, hash, and composite partitioning.
List Partitioning
A list partition works by identifying a column that contains a value, such as a STATE column in an ADDRESS table. Partitioning clauses follow the list of columns and constraints.
A list partition could use a STATE column, like the following (the complete example is avoided to conserve space, and the three dots represent the balance of partitions not shown):
CREATE TABLE franchise ( franchise_id NUMBER CONSTRAINT pk_franchise PRIMARY KEY , franchise_name VARCHAR(20) , city VARCHAR(20) , state VARCHAR(20)) PARTITION BY LIST(state) ( PARTITION offshore VALUES('Alaska', 'Hawaii') , PARTITION west VALUES('California', 'Oregon', 'Washington') , PARTITION desert VALUES ('Arizona','New Mexico') , PARTITION rockies VALUES ('Colorado', 'Idaho', 'Montana', 'Wyoming') , ... ); |
This can be used with other values such as ZIP codes with great effect, but the maintenance of list partitioning can be considered costly. Cost occurs when the list of values changes over time. Infrequent change means low cost, while frequent change means high costs. In the latter case, you should consider other partitioning strategies. Although an Oracle database supports partitioning on a variable-length string, MySQL performs list partitioning only on integer columns.
Range Partitioning
Range partitioning is very helpful on any column that contains a continuous metric, such as dates or time. It works by stating a minimum set that is less than a certain value, and then a group of sets of higher values until you reach the top most set of values. This type of partition helps you improve performance by letting you search ranges rather than complete data sets. Range partitioning is also available in MySQL.
A range example based on dates could look like this:
PARTITION BY RANGE(rental_date) ( PARTITION rental_jan2011 VALUES LESS THAN TO_DATE('31-JAN-11','DD-MON-YY') , PARTITION rental_feb2011 VALUES LESS THAN TO_DATE('28-FEB-11','DD-MON-YY') , PARTITION rental_mar2011 VALUES LESS THAN TO_DATE('31-MAR-11','DD-MON-YY') , ... ); |
The problem with this type of partitioning, however, is that the new months require constant management. Many North American businesses simply add partitions for all months in the year as an annual maintenance task during the holidays in November or December. Companies that opt for bigger range increments reap search and access benefits from range partitioning, while minimizing ongoing maintenance expenses.
Hash Partitioning
Hash partitioning is much easier to implement than list or range partitioning. Many DBAs favor it because it avoids the manual maintenance of list and range partitioning. Oracle Database 21c documentation recommends that you implement a hash for the following reasons:
- There is no concrete knowledge about how much data maps to a partitioning range.
- The sizes of partitions are unknown at the outset and difficult to balance as data is added to the database.
- A range partition might cluster data in an ineffective way.
This next statement creates eight partitions and stores them respectively in one of the eight tablespaces. The hash partition manages nodes and attempts to balance the distribution of rows across the nodes.
PARTITION BY HASH(store) PARTITIONS 8 STORE IN (tablespace1, tablespace2, tablespace3, tablespace4 ,tablespace5, tablespace6, tablespace7, tablespace8); |
As you can imagine the maintenance for this type of partitioning is low. Some DBAs choose this method to get an initial sizing before adopting a list or range partitioning plan. Maximizing the physical resources of the machine ultimately rests with the DBAs who manage the system. Developers need to stand ready to assist DBAs with analysis and syntax support.
Composite Partitioning
Composite partitioning requires a partition and subpartition. The composites are combinations of two types of partitioning—typically, list and range partitioning, or range and hash composite partitioning. Which of these you should choose depends on a few considerations. List and range composite partitioning is done for historical information and is well suited for data warehouses. This method lets you partition on unordered or unrelated column values.
A composite partition like this uses the range as the partition and the list as the subpartition, like the following:
PARTITION BY RANGE (rental_date) SUBPARTITION BY LIST (state) (PARTITION FQ1_1999 VALUES LESS THAN (TO_DATE('1-APR-2011','DD-MON-YYYY')) (SUBPARTITION offshore VALUES('Alaska', 'Hawaii') , SUBPARTITION west VALUES('California', 'Oregon', 'Washington') , SUBPARTITION desert VALUES ('Arizona','New Mexico') , SUBPARTITION rockies VALUES ('Colorado', 'Idaho', 'Montana', 'Wyoming') , ... ) ,(PARTITION FQ2_1999 VALUES LESS THAN (TO_DATE('1-APR-2011','DD-MON-YYYY')) (SUBPARTITION offshore VALUES('Alaska', 'Hawaii') , SUBPARTITION west VALUES('California', 'Oregon', 'Washington') , SUBPARTITION desert VALUES ('Arizona','New Mexico') , SUBPARTITION rockies VALUES ('Colorado', 'Idaho', 'Montana', 'Wyoming') , ... ) , ... ) |
Range and hash composite partitioning is done for historical information when you also need to stripe data. Striping is the process of creating an attribute in a table that acts as a natural subtype or separator of data. Users typically view data sets of one subtype, which means organizing the data by stripes (subtypes) can speed access based on user access patterns.
Range is typically the partition and the hash is the subpartition in this composite partitioning schema. The syntax for this type of partition is shown next:
PARTITION BY RANGE (rental_date) SUBPARTITION BY HASH(store) SUBPARTITIONS 8 STORE IN (tablespace1, tablespace2, tablespace3 ,tablespace4, tablespace5, tablespace6 ,tablespace7, tablespace8) ( PARTITION rental_jan2011 VALUES LESS THAN TO_DATE('31-JAN-11','DD-MON-YY') , PARTITION rental_feb2011 VALUES LESS THAN TO_DATE('28-FEB-11','DD-MON-YY') , PARTITION rental_mar2011 VALUES LESS THAN TO_DATE('31-MAR-11','DD-MON-YY') , ... ) |
PL/SQL List to Struct
Every now and then, I get questions from folks about how to tune in-memory elements of their PL/SQL programs. This blog post address one of those core issues that some PL/SQL programmers avoid.
Specifically, it addresses how to convert a list of values into a structure (in C/C++ its a struct, in Java its an ArrayList, and PL/SQL it’s a table of scalar or object types). Oracle lingo hides the similarity by calling either an Attribute Definition Type (ADT) or User-Defined Type (UDT). The difference in the Oracle space is that an ADT deals with a type defined in DBMS_STANDARD package, which is more or less like a primitive type in Java.
Oracle does this for two reasons:
- They handle lists of standard types in a difference C++ class than they do UDT types.
- They rigidly adhere to Interface Definition Language (IDL) principles.
The cast_strings function converts a list of strings into a record data structure. It lets the list of strings have either a densely or sparsely populated list of values, and it calls the verify_date function to identify a DATE data type and regular expressions to identify numbers and strings.
You need to build a UDT object type and lists of both ADT and UDT data types.
/* Create a table of strings. */ CREATE OR REPLACE TYPE tre AS TABLE OF VARCHAR2(20); / /* Create a structure of a date, number, and string. */ CREATE OR REPLACE TYPE struct IS OBJECT ( xdate DATE , xnumber NUMBER , xstring VARCHAR2(20)); / /* Create a table of tre type. */ CREATE OR REPLACE TYPE structs IS TABLE OF struct; / |
The cast_strings function is defined below:
CREATE OR REPLACE FUNCTION cast_strings ( pv_list TRE ) RETURN struct IS /* Declare a UDT and initialize an empty struct variable. */ lv_retval STRUCT := struct( xdate => NULL , xnumber => NULL , xstring => NULL); BEGIN /* Loop through list of values to find only the numbers. */ FOR i IN 1..pv_list.LAST LOOP /* Ensure that a sparsely populated list can't fail. */ IF pv_list.EXISTS(i) THEN /* Order if number evaluation before string evaluation. */ CASE WHEN lv_retval.xnumber IS NULL AND REGEXP_LIKE(pv_list(i),'^[[:digit:]]*$') THEN lv_retval.xnumber := pv_list(i); WHEN verify_date(pv_list(i)) THEN IF lv_retval.xdate IS NULL THEN lv_retval.xdate := pv_list(i); ELSE lv_retval.xdate := NULL; END IF; WHEN lv_retval.xstring IS NULL AND REGEXP_LIKE(pv_list(i),'^[[:alnum:]]*$') THEN lv_retval.xstring := pv_list(i); ELSE NULL; END CASE; END IF; END LOOP; /* Print the results. */ RETURN lv_retval; END; / |
There are three test cases for this function:
- The first use-case checks whether the input parameter is a sparsely or densely populated list:
DECLARE /* Declare an input variable of three or more elements. */ lv_list TRE := tre('Berlin','25','09-May-1945','45'); /* Declare a variable to hold the compound type values. */ lv_struct STRUCT; BEGIN /* Make the set sparsely populated. */ lv_list.DELETE(2); /* Test the cast_strings function. */ lv_struct := cast_strings(lv_list); /* Print the values of the compound variable. */ dbms_output.put_line(CHR(10)); dbms_output.put_line('xstring ['||lv_struct.xstring||']'); dbms_output.put_line('xdate ['||TO_CHAR(lv_struct.xdate,'DD-MON-YYYY')||']'); dbms_output.put_line('xnumber ['||lv_struct.xnumber||']'); END; /
It should return:
xstring [Berlin] xdate [09-MAY-1945] xnumber [45]
The program defines two numbers and deletes the first number, which is why it prints the second number.
- The second use-case checks with a list of only one element:
SELECT TO_CHAR(xdate,'DD-MON-YYYY') AS xdate , xnumber , xstring FROM TABLE(structs(cast_strings(tre('catch22','25','25-Nov-1945'))));
It should return:
XDATE XNUMBER XSTRING -------------------- ---------- -------------------- 25-NOV-1945 25 catch22
The program returns a structure with values converted into their appropriate data type.
- The third use-case checks with a list of two elements:
SELECT TO_CHAR(xdate,'DD-MON-YYYY') AS xdate , xnumber , xstring FROM TABLE(structs(cast_strings(tre('catch22','25','25-Nov-1945')) ,cast_strings(tre('31-APR-2017','1918','areodromes'))));
It should return:
XDATE XNUMBER XSTRING -------------------- ---------- -------------------- 25-NOV-1945 25 catch22 1918 areodromes
The program defines calls the cast_strings with a valid set of values and an invalid set of values. The invalid set of values contains a bad date in the set of values.
As always, I hope this helps those looking for how to solve this type of problem.
PL/SQL CASE Not Found
I was working on some test cases for my students and changing the behavior of a verify_date function that I wrote years ago to validate and returns valid dates when they’re passed as strings. The original program returned today’s date when the date was invalid.
The new function returns a BOOLEAN value of false by default and true when the string validates as a date. Unfortunately, I introduced a mistake that didn’t use to exist in Oracle 11g, which was the version when I wrote the original function.
The test cases in Oracle 21c raises the following error when an invalid date is passed to the CASE statement by the cast_strings function that calls the new verify_date function:
FROM TABLE(structs(cast_strings(tre('31-APR-2017','1917','dirk')))) * ERROR AT line 2: ORA-06592: CASE NOT found WHILE executing CASE statement ORA-06512: AT "C##STUDENT.VERIFY_DATE", line 30 ORA-06512: AT "C##STUDENT.CAST_STRINGS", line 18 |
As you can see, the test case uses ’31-APR-2017′ as an incorrect date to verify the use-case. The error occurred because the ELSE clause in the CASE statement wasn’t provided. Previously, the ELSE clause was optional and setting the lv_retval return variable to FALSE in the DECLARE block made it unnecessary.
The fixed code follows:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | CREATE OR REPLACE FUNCTION verify_date ( pv_date_in VARCHAR2) RETURN BOOLEAN IS /* Local variable to ensure case-insensitive comparison. */ lv_date_in VARCHAR2(11); /* Local return variable. */ lv_date BOOLEAN := FALSE; BEGIN /* Convert string input to uppercase month. */ lv_date_in := UPPER(pv_date_in); /* Check for a DD-MON-RR or DD-MON-YYYY string. */ IF REGEXP_LIKE(lv_date_in,'^[0-9]{2,2}-[ADFJMNOS][ACEOPU][BCGLNPRTVY]-([0-9]{2,2}|[0-9]{4,4})$') THEN /* Case statement checks for 28 or 29, 30, or 31 day month. */ CASE /* Valid 31 day month date value. */ WHEN SUBSTR(lv_date_in,4,3) IN ('JAN','MAR','MAY','JUL','AUG','OCT','DEC') AND TO_NUMBER(SUBSTR(pv_date_in,1,2)) BETWEEN 1 AND 31 THEN lv_date := TRUE; /* Valid 30 day month date value. */ WHEN SUBSTR(lv_date_in,4,3) IN ('APR','JUN','SEP','NOV') AND TO_NUMBER(SUBSTR(pv_date_in,1,2)) BETWEEN 1 AND 30 THEN lv_date := TRUE; /* Valid 28 or 29 day month date value. */ WHEN SUBSTR(lv_date_in,4,3) = 'FEB' THEN /* Verify 2-digit or 4-digit year. */ IF (LENGTH(pv_date_in) = 9 AND MOD(TO_NUMBER(SUBSTR(pv_date_in,8,2)) + 2000,4) = 0 OR LENGTH(pv_date_in) = 11 AND MOD(TO_NUMBER(SUBSTR(pv_date_in,8,4)),4) = 0) AND TO_NUMBER(SUBSTR(pv_date_in,1,2)) BETWEEN 1 AND 29 THEN lv_date := TRUE; ELSE /* Not a leap year. */ IF TO_NUMBER(SUBSTR(pv_date_in,1,2)) BETWEEN 1 AND 28 THEN lv_date := TRUE; END IF; END IF; ELSE NULL; END CASE; END IF; /* Return date. */ RETURN lv_date; EXCEPTION WHEN VALUE_ERROR THEN RETURN lv_date; END; / |
The new ELSE clause in on lines 31 and 32, and the converted function works. I also added a local lv_date_in variable to hold an uppercase version of an input string to: ensure a case-insensitive comparison of the month value, and avoid a having to pass the input as an IN OUT mode parameter. Typically, I leave off exception handlers because mistyping or copying for newer programmers becomes easier, but in this case I added an exception handler for strings that are larger than 11-characters.
As always, I hope this helps those looking for a solution to a coding problem.
Oracle DSN Security
Oracle disallows entry of a password value when configuring the ODBC’s Windows Data Source Name (DSN) configurations. As you can see from the dialog’s options:
So, I check the Oracle ODBC’s property list with the following PowerShell command:
Get-Item -Path Registry::HKEY_LOCAL_MACHINE\SOFTWARE\ODBC\ODBC.INI\Oracle | Select-Object |
It returned:
Oracle Driver : C:\app\mclaughlinm\product\18.0.0\dbhomeXE\BIN\SQORA32.DLL
DisableRULEHint : T
Attributes : W
SQLTranslateErrors : F
LobPrefetchSize : 8192
AggregateSQLType : FLOAT
MaxTokenSize : 8192
FetchBufferSize : 64000
NumericSetting : NLS
ForceWCHAR : F
FailoverDelay : 10
FailoverRetryCount : 10
MetadataIdDefault : F
BindAsFLOAT : F
BindAsDATE : F
CloseCursor : F
EXECSchemaOpt :
EXECSyntax : F
Application Attributes : T
QueryTimeout : T
CacheBufferSize : 20
StatementCache : F
ResultSets : T
MaxLargeData : 0
UseOCIDescribeAny : F
Failover : T
Lobs : T
DisableMTS : T
DisableDPM : F
BatchAutocommitMode : IfAllSuccessful
Description : Oracle ODBC
ServerName : xe
Password :
UserID : c##student
DSN : Oracle |
Then, I used this PowerShell command to set the Password property:
Set-ItemProperty -Path Registry::HKEY_LOCAL_MACHINE\SOFTWARE\ODBC\ODBC.INI\Oracle -Name "Password" -Value 'student' |
After setting the Password property’s value, I queried it with the following PowerShell command:
Get-ItemProperty -Path Registry::HKEY_LOCAL_MACHINE\SOFTWARE\ODBC\ODBC.INI\Oracle | Select-Object -Property "Password" |
It returns:
Password : student |
After manually setting the Oracle ODBC DSN’s password value you can now connect without providing a password at runtime. It also means anybody who hacks the Windows environment can access the password through trivial PowerShell command.
I hope this alerts readers to a potential security risk when you use Oracle DSNs.
PL/SQL List Function
Students wanted to see how to write PL/SQL functions that accept, process, and return lists of values. I thought it would be cool to also demonstrate coupling of loop behaviors and wrote the example using the 12-Days of Christmas lyrics.
The twelve_days function accepts two different collections. One is an Attribute Data Type (ADT) and the other a User-Defined Type (UDT). An ADT is based on a scalar data type, and a UDT is based on an object type. Object types are basically data structures, and they support both positional and named notation for variable assignments.
The twelve_days function returns a list of string, which is an ADT of the VARCHAR2 data type. Creating the ADT types is easy and a single step, like:
/* Create a days object type. */ CREATE OR REPLACE TYPE days IS TABLE OF VARCHAR2(8); / /* Create a string object type. */ CREATE OR REPLACE TYPE song IS TABLE OF VARCHAR2(36); / |
Creating the UDT is more complex and requires two steps. You need to create the UDT object type, or structure, and then the list based on the UDT object type, like:
/* Create a lyric object type. */ CREATE OR REPLACE TYPE lyric IS OBJECT ( DAY VARCHAR2(8) , gift VARCHAR2(24)); / /* Create a lyrics object type. */ CREATE OR REPLACE TYPE lyrics IS TABLE OF LYRIC; / |
Now, you can create the twelve_days function that uses these ADT and UDT types, like:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | CREATE OR REPLACE FUNCTION twelve_days ( pv_days DAYS , pv_gifts LYRICS ) RETURN song IS /* Initialize the collection of lyrics. */ lv_retval SONG := song(); /* Local procedure to add to the song. */ PROCEDURE ADD ( pv_input VARCHAR2 ) IS BEGIN lv_retval.EXTEND; lv_retval(lv_retval.COUNT) := pv_input; END ADD; BEGIN /* Read forward through the days. */ FOR i IN 1..pv_days.COUNT LOOP ADD('On the ' || pv_days(i) || ' day of Christmas'); ADD('my true love sent to me:'); /* Read backward through the lyrics based on the ascending value of the day. */ FOR j IN REVERSE 1..i LOOP IF i = 1 THEN ADD('-'||'A'||' '||pv_gifts(j).gift); ELSE ADD('-'||pv_gifts(j).DAY||' '||pv_gifts(j).gift); END IF; END LOOP; /* A line break by verse. */ ADD(CHR(13)); END LOOP; /* Return the song's lyrics. */ RETURN lv_retval; END; / |
You may notice the local add procedure on lines 10 thru 15. It lets you perform the two tasks required for populating an element in a SQL object type list in one line in the main body of the twelve_days function.
The add procedure first uses the EXTEND function to allocate space before assigning the input value to the newly allocated element in the list. Next, you can call the function inside the following SQL query:
SELECT column_value AS "12-Days of Christmas" FROM TABLE(twelve_days(days('first','second','third','fourth' ,'fifth','sixth','seventh','eighth' ,'nineth','tenth','eleventh','twelfth') ,lyrics(lyric(DAY => 'and a', gift => 'Partridge in a pear tree') ,lyric(DAY => 'Two', gift => 'Turtle doves') ,lyric(DAY => 'Three', gift => 'French hens') ,lyric(DAY => 'Four', gift => 'Calling birds') ,lyric(DAY => 'Five', gift => 'Golden rings' ) ,lyric(DAY => 'Six', gift => 'Geese a laying') ,lyric(DAY => 'Seven', gift => 'Swans a swimming') ,lyric(DAY => 'Eight', gift => 'Maids a milking') ,lyric(DAY => 'Nine', gift => 'Ladies dancing') ,lyric(DAY => 'Ten', gift => 'Lords a leaping') ,lyric(DAY => 'Eleven',gift => 'Pipers piping') ,lyric(DAY => 'Twelve',gift => 'Drummers drumming')))); |
It will print:
12-Days of Christmas ------------------------------------ On the first day of Christmas my true love sent to me: -A Partridge in a pear tree On the second day of Christmas my true love sent to me: -Two Turtle doves -and a Partridge in a pear tree On the third day of Christmas my true love sent to me: -Three French hens -Two Turtle doves -and a Partridge in a pear tree ... redacted for space ... On the twelfth day of Christmas my true love sent to me: -Twelve Drummers drumming -Eleven Pipers piping -Ten Lords a leaping -Nine Ladies dancing -Eight Maids a milking -Seven Swans a swimming -Six Geese a laying -Five Golden rings -Four Calling birds -Three French hens -Two Turtle doves -and a Partridge in a pear tree |
As always, I hope the example helps those looking for a solution to this type of problem.
Magic WITH Clause
Magic WITH Clause
Learning Outcomes
- Learn how to use the
WITHclause. - Learn how to join the results of two
WITHclauses.
Lesson Materials
The idea of modularity is important in every programming environment. SQL is no different than other programming languages in that regard. SQL-92 introduced the ability to save queries as views. Views are effectively modular views of data.
A view is a named query that is stored inside the data dictionary. The contents of the view change as the data in the tables that are part of the view changes.
SQL:1999 added the WITH clause, which defines statement scoped views. Statement scoped views are named queries, or queries named as views, only in the scope of a query where they are defined.
The simplest prototype for a WITH clause that contains a statement scoped view is:
WITH query_name [(column1, column2, ...)] AS (SELECT column1, column2, ...) SELECT column1, column2, ... FROM table_name tn INNER JOIN query_name qn ON tn.column_name = qn.column_name WHERE qn.column_name = 'Some literal'; |
You should note that the list of columns after the query name is an optional list. The list of columns must match the SELECT-list, which is the set of comma delimited columns of the SELECT clause.
A more complete prototype for a WITH clause shows you how it can contain two or more statement scoped views. That prototype is:
WITH query_name [(column1, column2, ...)] AS (SELECT column1, column2, ...) , query_name2 [(column1, column2, ...)] AS (SELECT column1, column2, ...) SELECT column1, column2, ... FROM table_name tn INNER JOIN query_name1 qn1 ON tn.column_name = qn1.column_name INNER JOIN query_name2 qn2 ON qn1.column_name = qn2.column_name; WHERE qn1.column_name = 'Some literal'; |
The WITH clause has several advantages over embedded view in the FROM clause or subqueries in various parts of a query or SQL statement. The largest advantage is that a WITH clause is a named subquery and you can reference it from multiple locations in a query; whereas, embedded subqueries are unnamed blocks of code and often results in replicating a single subquery in multiple locations.
A small model of three tables lets you test a WITH clause in the scope of a query. It creates a war, country, and ace tables. The tables are defined as:
WAR
Name NULL? TYPE -------------------------------- -------- ---------------- WAR_ID NUMBER WAR_NAME VARCHAR2(30) |
COUNTRY
Name NULL? TYPE -------------------------------- -------- ---------------- COUNTRY_ID NUMBER COUNTRY_NAME VARCHAR2(20) |
ACE
Name NULL? TYPE -------------------------------- -------- ---------------- ACE_ID NUMBER ACE_NAME VARCHAR2(30) COUNTRY_ID NUMBER WAR_ID NUMBER |
The following WITH clause includes two statement scoped views. One statement scoped view queries results form a single table while the other queries results from a join between the country and ace tables.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | CLEAR COLUMNS CLEAR BREAKS BREAK ON REPORT BREAK ON war_name SKIP PAGE COL ace_id FORMAT 9999 HEADING "Ace|ID #" COL ace_name FORMAT A24 HEADING "Ace Name" COL war_name FORMAT A12 HEADING "War Name" COL country_name FORMAT A14 HEADING "Country Name" WITH wars (war_id, war_name) AS (SELECT w.war_id, war_name FROM war w ) , aces (ace_id, ace_name, country_name, war_id) AS (SELECT a.ace_id , a.ace_name , c.country_name , a.war_id FROM ace a INNER JOIN country c ON a.country_id = c.country_id) SELECT a.ace_id , a.ace_name , w.war_name , a.country_name FROM aces a INNER JOIN wars w ON a.war_id = w.war_id ORDER BY war_name , CASE WHEN REGEXP_INSTR(ace_name,' ',1,2,1) > 0 THEN SUBSTR(ace_name,REGEXP_INSTR(ace_name,' ',1,2,1),LENGTH(ace_name) - REGEXP_INSTR(ace_name,' ',1,2,0)) WHEN REGEXP_INSTR(ace_name,' ',1,1,1) > 0 THEN SUBSTR(ace_name,REGEXP_INSTR(ace_name,' ',1,1,1),LENGTH(ace_name)) END; |
wars is the first statement scoped view of the war table. aces is the second statement scoped view of the inner join between the ace and country tables. You should note that aces statement scoped view has access to the wars scoped view, and the master SELECT statement has scope access to both statement scoped views and any tables in its schema.
The query returns the following with the help of SQL*Plus formatting BREAK statements:
Ace ID # Ace Name War Name Country Name ----- ------------------------ ------------ -------------- 1009 William Terry Badham World War I America 1003 Albert Ball United Kingdom 1010 Charles John Biddle America 1005 William Bishop Canada 1007 Keith Caldwell New Zealand 1006 Georges Guynemer France 1008 Robert Alexander Little Austrailia 1001 Manfred von Richtofen Germany 1002 Eddie Rickenbacker America 1004 Werner Voss Germany Ace ID # Ace Name War Name Country Name ----- ------------------------ ------------ -------------- 1018 Richard Bong World War II America 1015 Edward F Charles Canada 1020 Heinrich Ehrler Germany 1019 Ilmari Juutilainen Finland 1014 Ivan Kozhedub Soviet Union 1012 Thomas McGuire America 1013 Pat Pattle United Kingdom 1011 Erich Rudorffer Germany 1016 Stanislaw Skalski Poland 1017 Teresio Vittorio Italy 20 rows selected. |
The WITH clause is the most effective solution when you have a result set that needs to be consistently used in two or more places in a master query. That’s because the result set becomes a named statement scoped view.
Script Code
Click the Script Code link to open the test case seeding script inside the current webpage.
Script Code →
The following script includes tables that will not conflict with other lab assignments. It creates the war, ace, and country tables; war_s, ace_s, and country_s sequences; and the WITH enabled query from this blog page.
DROP TABLE war; CREATE TABLE war ( war_id NUMBER , war_name VARCHAR2(30)); DROP SEQUENCE war_s; CREATE SEQUENCE war_s START WITH 1001; DROP TABLE ace; CREATE TABLE ace ( ace_id NUMBER , ace_name VARCHAR2(30) , country_id NUMBER , war_id NUMBER); DROP SEQUENCE ace_s; CREATE SEQUENCE ace_s START WITH 1001; DROP TABLE country; CREATE TABLE country ( country_id NUMBER , country_name VARCHAR2(20)); DROP SEQUENCE country_s; CREATE SEQUENCE country_s START WITH 1001; /* || Insert two rows for wars. */ INSERT INTO war ( war_id , war_name ) VALUES ( war_s.NEXTVAL ,'World War I'); INSERT INTO war ( war_id , war_name ) VALUES ( war_s.NEXTVAL ,'World War II'); /* || Insert ten rows for countries. */ INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'Germany'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'Italy'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'Poland'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'United Kingdom'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'France'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'Finland'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'Soviet Union'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'America'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'Austrailia'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'New Zealand'); INSERT INTO country ( country_id , country_name ) VALUES ( country_s.NEXTVAL ,'Canada'); /* || Insert twenty rows for aerial combat aces. */ INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Manfred von Richtofen' ,(SELECT country_id FROM country WHERE country_name = 'Germany') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Eddie Rickenbacker' ,(SELECT country_id FROM country WHERE country_name = 'America') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Albert Ball' ,(SELECT country_id FROM country WHERE country_name = 'United Kingdom') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Werner Voss' ,(SELECT country_id FROM country WHERE country_name = 'Germany') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'William Bishop' ,(SELECT country_id FROM country WHERE country_name = 'Canada') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Georges Guynemer' ,(SELECT country_id FROM country WHERE country_name = 'France') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Keith Caldwell' ,(SELECT country_id FROM country WHERE country_name = 'New Zealand') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Robert Alexander Little' ,(SELECT country_id FROM country WHERE country_name = 'Austrailia') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'William Terry Badham' ,(SELECT country_id FROM country WHERE country_name = 'America') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Charles John Biddle' ,(SELECT country_id FROM country WHERE country_name = 'America') ,(SELECT war_id FROM war WHERE war_name = 'World War I')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Erich Rudorffer' ,(SELECT country_id FROM country WHERE country_name = 'Germany') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Thomas McGuire' ,(SELECT country_id FROM country WHERE country_name = 'America') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Pat Pattle' ,(SELECT country_id FROM country WHERE country_name = 'United Kingdom') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Ivan Kozhedub' ,(SELECT country_id FROM country WHERE country_name = 'Soviet Union') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Edward F Charles' ,(SELECT country_id FROM country WHERE country_name = 'Canada') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Stanislaw Skalski' ,(SELECT country_id FROM country WHERE country_name = 'Poland') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Teresio Vittorio' ,(SELECT country_id FROM country WHERE country_name = 'Italy') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Richard Bong' ,(SELECT country_id FROM country WHERE country_name = 'America') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Ilmari Juutilainen' ,(SELECT country_id FROM country WHERE country_name = 'Finland') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); INSERT INTO ace ( ace_id , ace_name , country_id , war_id ) VALUES ( ace_s.NEXTVAL ,'Heinrich Ehrler' ,(SELECT country_id FROM country WHERE country_name = 'Germany') ,(SELECT war_id FROM war WHERE war_name = 'World War II')); /* || Commit the records. */ COMMIT; /* || Query from statement scoped views. */ CLEAR COLUMNS CLEAR BREAKS BREAK ON REPORT BREAK ON war_name SKIP PAGE COL ace_id FORMAT 9999 HEADING "Ace|ID #" COL ace_name FORMAT A24 HEADING "Ace Name" COL war_name FORMAT A12 HEADING "War Name" COL country_name FORMAT A14 HEADING "Country Name" WITH wars (war_id, war_name) AS (SELECT w.war_id, war_name FROM war w ) , aces (ace_id, ace_name, country_name, war_id) AS (SELECT a.ace_id , a.ace_name , c.country_name , a.war_id FROM ace a INNER JOIN country c ON a.country_id = c.country_id) SELECT a.ace_id , a.ace_name , w.war_name , a.country_name FROM aces a INNER JOIN wars w ON a.war_id = w.war_id ORDER BY war_name , CASE WHEN REGEXP_INSTR(ace_name,' ',1,2,1) > 0 THEN SUBSTR(ace_name,REGEXP_INSTR(ace_name,' ',1,2,1),LENGTH(ace_name) - REGEXP_INSTR(ace_name,' ',1,2,0)) WHEN REGEXP_INSTR(ace_name,' ',1,1,1) > 0 THEN SUBSTR(ace_name,REGEXP_INSTR(ace_name,' ',1,1,1),LENGTH(ace_name)) END; |
You can use the base query as a starting place to experiment with the WITH clause in a query.
What’s up on M1 Chip?
I’ve been trying to sort out what’s up on Oracle’s support of Apple’s M1 (arm64) chip. It really is a niche area. It only applies to those of us who work on a macOS machines with Oracle Database technology; and then only when we want to install a version of Oracle Database 21c or newer in Windows OS for testing. Since bootcamp is now gone, these are only virtualized solutions through a full virtualization product or containerized with Docker of Kubernetes.
The Best Virtual Machine Software for Mac 2022 (4/11/2022) article lets us know that only Parallels fully supports Windows virtualization on the ARM64 chip. Then, there’s the restriction that you must use Monterey or Big Sur (macOS) and Windows 11 arm64.
Instructions were published on On how to run Windows 11 on an Apple M1 a couple weeks ago. They use the free UTM App from the Apple Store and provide the download site for the Windows Insider Program. You can’t get a copy of Windows 11 arm64 without becoming part of the Windows Insider Program.
The next step would be to try and install Oracle Database 21c on Windows 11 arm64, which may or may not work. At least, I haven’t tested it yet and can’t make the promise that it works. After all, I doubt it will work because the Oracle Database 21c documentation says it only supports x64 (or Intel) architecture.
If anybody knows what Oracle has decided, will decide or even their current thinking on the issue, please make a comment.
Oracle ODBC DSN
As I move forward with trying to build an easy to use framework for data analysts who use multiple database backends and work on Windows OS, here’s a complete script that lets you run any query stored in a file to return a CSV file. It makes the assumption that you opted to put the user ID and password in the Windows ODBC DSN, and only provides the ODBC DSN name to make the connection to the ODBC library and database.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 | # A local function for verbose reporting. function Get-Message ($param, $value = $null) { if (!($value)) { Write-Host "Evaluate swtich [" $param "]" } else { Write-Host "Evaluate parameter [" $param "] and [" $value "]" } } # Read SQLStatement file and minimally parse it. function Get-SQLStatement ($sqlStatement) { # Set localvariable for return string value. $statement = "" # Read a file line-by-line. foreach ($line in Get-Content $sqlStatement) { # Use regular expression to replace multiple whitespace. $line = $line -replace '\s+', ' ' # Add a whitespace to avoid joining keywords from different lines; # and remove trailing semicolons which are unneeded. if (!($line.endswith(";"))) { $statement += $line + " " } else { $statement += $line.trimend(";") } } # Returned minimally parsed statement. return $statement } # Set default type of SQL statement value to a query. $stmt = "select" # Set a variable to hold a SQL statement from a file. $query = "" # Set default values for SQL input and output files. $outFile = "output.csv" $sqlFile = "query.sql" # Set default path to: %USERPROFILE%\AppData\Local\Temp folder, but ir # the tilde (~) in lieu of the %USERPROFILE% environment variable value. $path = "~\AppData\Local\Temp" # Set a verbose switch. $verbose = $false # Wrap the Parameter call to avoid a type casting warning. try { param ( [Parameter(Mandatory)][hashtable]$args ) } catch {} # Check for switches and parameters with arguments. for ($i = 0; $i -lt $args.count; $i += 1) { if (($args[$i].startswith("-")) -and ($args[$i + 1].startswith("-"))) { if ($args[$i] = "-v") { $verbose = $true } # Print to verbose console. if ($verbose) { Get-Message $args[$i] }} elseif ($args[$i].startswith("-")) { # Print to verbose console. if ($verbose) { Get-Message $args[$i] $args[$i + 1] } # Evaluate and take action on parameters and values. if ($args[$i] -eq "-o") { $outfile = $args[$i + 1] } elseif ($args[$i] -eq "-q") { $sqlFile = $args[$i + 1] } elseif ($args[$i] -eq "-p") { $path = $args[$i + 1] } } } # Set a PowerShell Virtual Drive. New-PSDrive -Name folder -PSProvider FileSystem -Description 'Forder Location' ` -Root $path | Out-Null # Remove the file only when it exists. if (Test-Path folder:$outFile) { Remove-Item -Path folder:$outFile } # Read SQL file into minimally parsed string. if (Test-Path folder:$sqlFile) { $query = Get-SQLStatement $sqlFile } # Set a ODBC DSN connection string. $ConnectionString = 'DSN=OracleGeneric' # Set an Oracle Command Object for a query. $Connection = New-Object System.Data.Odbc.OdbcConnection; $Connection.ConnectionString = $ConnectionString # Attempt connection. try { $Connection.Open() # Create a SQL command. $Command = $Connection.CreateCommand(); $Command.CommandText = $query; # Attempt to read SQL command. try { $row = $Command.ExecuteReader(); # Read while records are found. while ($row.Read()) { # Initialize output for each row. $output = "" # Navigate across all columns (only two in this example). for ($column = 0; $column -lt $row.FieldCount; $column += 1) { # Mechanic for comma-delimit between last and first name. if ($output.length -eq 0) { $output += $row[$column] } else { $output += ", " + $row[$column] } } # Write the output from the database to a file. Add-Content -Value $output -Path folder:$outFile } } catch { Write-Error "Message: $($_.Exception.Message)" Write-Error "StackTrace: $($_.Exception.StackTrace)" Write-Error "LoaderExceptions: $($_.Exception.LoaderExceptions)" } finally { # Close the reader. $row.Close() } } catch { Write-Error "Message: $($_.Exception.Message)" Write-Error "StackTrace: $($_.Exception.StackTrace)" Write-Error "LoaderExceptions: $($_.Exception.LoaderExceptions)" } finally { $Connection.Close() } |
You can use a command-line call like this:
powershell ./OracleContact.ps1 -v -o output.csv -q script.sql -p . |
It produces the following verbose output to the console:
Evaluate swtich [ -v ] Evaluate parameter [ -o ] and [ output.csv ] Evaluate parameter [ -q ] and [ script.sql ] Evaluate parameter [ -p ] and [ . ] |
You can suppress printing to the console by eliminating the -v switch from the parameter list.
As always, I hope this helps those looking for a solution to less tedious interactions with the Oracle database.
Transaction Management
Transaction Management
Learning Outcomes
- Learn how to use Multiversion Concurrency Control (MVCC).
- Learn how to manage ACID-compliant transactions.
- Learn how to use:
- SAVEPOINT Statement
- COMMIT Statement
- ROLLBACK Statement
Lesson Material
Transaction Management involves two key components. One is Multiversion Concurrency Control (MVCC) so one user doesn’t interfere with another user. The other is data transactions. Data transactions packag SQL statements in the scope of an imperative language that uses Transaction Control Language (TCL) to extend ACID-compliance from single SQL statements to groups of SQL statements.
Multiversion Concurrency Control (MVCC)
Multiversion Concurrency Control (MVCC) uses database snapshots to provide transactions with memory-persistent copies of the database. This means that users, via their SQL statements, interact with the in-memory copies of data rather than directly with physical data. MVCC systems isolate user transactions from each other and guarantee transaction integrity by preventing dirty transactions, writes to the data that shouldn’t happen and that make the data inconsistent. Oracle Database 12c prevents dirty writes by its MVCC and transaction model.
Transaction models depend on transactions, which are ACID-compliant blocks of code. Oracle Database 12c provides an MVCC architecture that guarantees that all changes to data are ACID-compliant, which ensures the integrity of concurrent operations on data—transactions.
ACID-compliant transactions meet four conditions:
- Atomic
- They complete or fail while undoing any partial changes.
- Consistent
- They change from one state to another the same way regardless of whether
the change is made through parallel actions or serial actions. - Isolated
- Partial changes are never seen by other users or processes in the concurrent system.
- Durable
- They are written to disk and made permanent when completed.
Oracle Database 12c manages ACID-compliant transactions by writing them to disk first, as redo log files only or as both redo log files and archive log files. Then it writes them to the database. This multiple-step process with logs ensures that Oracle database’s buffer cache (part of the instance memory) isn’t lost from any completed transaction. Log writes occur before the acknowledgement-of-transactions process occurs.
The smallest transaction in a database is a single SQL statement that inserts, updates, or deletes rows. SQL statements can also change values in one or more columns of a row in a table. Each SQL statement is by itself an ACID-compliant and MVCC-enabled transaction when managed by a transaction-capable database engine. The Oracle database is always a transaction-capable system. Transactions are typically a collection of SQL statements that work in close cooperation to accomplish a business objective. They’re often grouped into stored programs, which are functions, procedures, or triggers. Triggers are specialized programs that audit or protect data. They enforce business rules that prevent unauthorized changes to the data.
SQL statements and stored programs are foundational elements for development of business applications. They contain the interaction points between customers and the data and are collectively called the application programming interface (API) to the database. User forms (typically web forms today) access the API to interact with the data. In well-architected business application software, the API is the only interface that the form developer interacts with.
Database developers, such as you and I, create these code components to enforce business rules while providing options to form developers. In doing so, database developers must guard a few things at all cost. For example, some critical business logic and controls must prevent changes to the data in specific tables, even changes in API programs. That type of critical control is often written in database triggers. SQL statements are events that add, modify, or delete data. Triggers guarantee that API code cannot make certain additions, modifications, or deletions to critical resources, such as tables. Triggers can run before or after SQL statements. Their actions, like the SQL statements themselves, are temporary until the calling scope sends an instruction to commit the work performed.
A database trigger can intercept values before they’re placed in a column, and it can ensure that only certain values can be inserted into or updated in a column. A trigger overrides an INSERT or UPDATE statement value that violates a business rule and then it either raises an error and aborts the transaction or changes the value before it can be inserted or updated into the table. Chapter 12 offers examples of both types of triggers in Oracle Database 12c.
MVCC determines how to manage transactions. MVCC guarantees how multiple users’ SQL statements interact in an ACID compliant manner. The next two sections qualify how data transactions work and how MVCC locks and isolates partial results from data transactions.
Data Transaction
Data Manipulation Language (DML) commands are the SQL statements that transact against the data. They are principally the INSERT, UPDATE, and DELETE statements. The INSERT statement adds new rows in a table, the UPDATE statement modifies columns in existing rows, and the DELETE statement removes a row from a table.
The Oracle MERGE statement transacts against data by providing a conditional insert or update feature. The MERGE statement lets you add new rows when they don’t exist or change column values in rows that do exist.
Inserting data seldom encounters a conflict with other SQL statements because the values become a new row or rows in a table. Updates and deletes, on the other hand, can and do encounter conflicts with other UPDATE and DELETE statements. INSERT statements that encounter conflicts occur when columns in a new row match a preexisting row’s uniquely constrained columns. The insertion is disallowed because only one row can contain the unique column set.
These individual transactions have two phases in transactional databases such as Oracle. The first phase involves making a change that is visible only to the user in the current session. The user then has the option of committing the change, which makes it permanent, or rolling back the change, which undoes the transaction. Developers use Transaction Control Language (TCL) commands to confirm or cancel transactions. The COMMIT statement confirms or makes permanent any change, and the ROLLBACK statement cancels or undoes any change.
A generic transaction lifecycle for a two-table insert process implements a business rule that specifies that neither INSERT statement works unless they both work. Moreover, if the first INSERT statement fails, the second INSERT statement never runs; and if the second INSERT statement fails, the first INSERT statement is undone by a ROLLBACK statement to a SAVEPOINT.
After a failed transaction is unwritten, good development practice requires that you write the failed event(s) to an error log table. The write succeeds because it occurs after the ROLLBACK statement but before the COMMIT statement.
A SQL statement followed by a COMMIT statement is called a transaction process, or a two-phase commit (2PC) protocol. ACID-compliant transactions use a 2PC protocol to manage one SQL statement or collections of SQL statements. In a 2PC protocol model, the INSERT, UPDATE, MERGE, or DELETE DML statement starts the process and submits changes. These DML statements can also act as events that fire database triggers assigned to the table being changed.
Transactions become more complex when they include database triggers because triggers can inject an entire layer of logic within the transaction scope of a DML statement. For example, database triggers can do the following:
- Run code that verifies, changes, or repudiates submitted changes
- Record additional information after validation in other tables (they can’t write to the table being changed—or, in database lexicon, “mutated”
- Throw exceptions to terminate a transaction when the values don’t meet business rules
As a general rule, triggers can’t contain a COMMIT or ROLLBACK statement because they run inside the transaction scope of a DML statement. Oracle databases give developers an alternative to this general rule because they support autonomous transactions. Autonomous transactions run outside the transaction scope of the triggering DML statement. They can contain a COMMIT statement and act independently of the calling scope statement. This means an autonomous trigger can commit a transaction when the calling transaction fails.
As independent statements or collections of statements add, modify, and remove rows, one statement transacts against data only by locking rows: the SELECT statement. A SELECT statement typically doesn’t lock rows when it acts as a cursor in the scope of a stored program. A cursor is a data structure that contains rows of one-to-many columns in a stored program. This is also known as a list of record structures.
Cursors act like ordinary SQL queries, except they’re managed by procedure programs row by row. There are many examples of procedural programming languages. PL/SQL and SQL/PSM programming languages are procedural languages designed to run inside the database. C, C++, C#, Java, Perl, and PHP are procedural languages that interface with the database through well-defined interfaces, such as Java Database Connectivity (JDBC) and Open Database Connectivity (ODBC).
Cursors can query data two ways. One way locks the rows so that they can’t be changed until the cursor is closed; closing the cursor releases the lock. The other way doesn’t lock the rows, which allows them to be changed while the program is working with the data set from the cursor. The safest practice is to lock the rows when you open the cursor, and that should always be the case when you’re inserting, updating, or deleting rows that depend on the values in the cursor not changing until the transaction lifecycle of the program unit completes.
Loops use cursors to process data sets. That means the cursors are generally opened at or near the beginning of program units. Inside the loop the values from the cursor support one to many SQL statements for one to many tables.
Stored and external programs create their operational scope inside a database connection when they’re called by another program. External programs connect to a database and enjoy their own operational scope, known as a session scope. The session defines the programs’ operational scope. The operational scope of a stored program or external program defines the transaction scope. Inside the transaction scope, the programs interact with data in tables by inserting, updating, or deleting data until the operations complete successfully or encounter a critical failure. These stored program units commit changes when everything completes successfully, or they roll back changes when any critical instruction fails. Sometimes, the programs are written to roll back changes when any instruction fails.
In the Oracle Database, the most common clause to lock rows is the FOR UPDATE clause, which is appended to a SELECT statement. An Oracle database also supports a WAIT n seconds or NOWAIT option. The WAIT option is a blessing when you want to reply to an end user form’s request and can’t make the change quickly. Without this option, a change could hang around for a long time, which means virtually indefinitely to a user trying to run your application. The default value in an Oracle database is NOWAIT, WAIT without a timeout, or wait indefinitely.
You should avoid this default behavior when developing program units that interact with customers. The Oracle Database also supports a full table lock with the SQL LOCK TABLE command, but you would need to embed the command inside a stored or external program’s instruction set.
Oracle Unit Test
A unit test script may contain SQL or PL/SQL statements or it may call another script file that contains SQL or PL/SQL statements. Moreover, a script file is a way to bundle several activities into a single file because most unit test programs typically run two or more instructions as unit tests.
Unconditional Script File
You can write a simple unit test like the example program provided in the Lab 1 Help Section, which includes conditional logic. However, you can write a simpler script that is unconditional and raises exceptions when preconditions do not exist.
The following script file creates a one table and one_s sequence. The DROP TABLE and DROP SEQUENCE statements have the same precondition, which is that the table or sequence must previously exist.
-- Drop table one. DROP TABLE one; -- Crete table one. CREATE TABLE one ( one_id NUMBER , one_text VARCHAR2(10)); -- Drop sequence one_s. DROP SEQUENCE one_s; -- Create sequence one_s. CREATE SEQUENCE one_s; |
After writing the script file, you can save it in the lab2 subdirectory as the unconditional.sql file. After you login to the SQL*Plus environment from the lab2 subdirectory. You call the unconditional.sql script file from inside the SQL*Plus environment with the following syntax:
@unconditional.sql |
It will display the following output, which raises an exception when the one table or one_s sequence does not already exist in the schema or database:
DROP TABLE one
*
ERROR at line 1:
ORA-00942: table or view does not exist
Table created.
DROP SEQUENCE one_s
*
ERROR at line 1:
ORA-02289: sequence does not exist
Sequence created. |
An unconditional script raises exceptions when a precondition of the statement does not exist. The precondition is not limited to objects, like the table or sequence; and the precondition may be specific data in one or several rows of one or several tables. You can avoid raising conditional errors by writing conditional scripts.
Conditional Script File
A conditional script file contains statements that check for a precondition before running a statement, which effectively promotes their embedded statements to a lambda function. The following logic recreates the logic of the unconditional.sql script file as a conditional script file:
-- Conditionally drop a table and sequence. BEGIN FOR i IN (SELECT object_name , object_type FROM user_objects WHERE object_name IN ('ONE','ONE_S') ORDER BY object_type ) LOOP IF i.object_type = 'TABLE' THEN EXECUTE IMMEDIATE 'DROP TABLE '||i.object_name||' CASCADE CONSTRAINTS'; ELSE EXECUTE IMMEDIATE 'DROP SEQUENCE '||i.object_name; END IF; END LOOP; END; / -- Crete table one. CREATE TABLE one ( one_id NUMBER , one_text VARCHAR2(10)); -- Create sequence one_s. CREATE SEQUENCE one_s; |
You can save this script in the lab2 subdirectory as conditional.sql and then unit test it in SQL*Plus. You must manually drop the one table and one_s sequence before running the conditional.sql script to test the preconditions.
You will see that the conditional.sql script does not raise an exception because the one table or one_s sequence is missing. It should generate output to the console, like this:
PL/SQL procedure successfully completed. Table created. Sequence created. |
As a rule, you should always write conditional script files. Unconditional script files throw meaningless errors, which may cause your good code to fail a deployment test that requires error free code.
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