MacLochlainns Weblog

Magic WITH Clause

Learning Outcomes

• Learn how to use the WITH clause.
• Learn how to join the results of two WITH clauses.

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.

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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.

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;

My students working in Linux would have a series of labs to negotiate and I’d have them log the activities of their Oracle SQL scripts. Many of them would suffer quite a bit because they didn’t know how to find the errors in the log files.

I wrote this SQL function for them to put in their .bashrc files. It searches all the .txt files for errors and organizes them by log file, line number, and descriptive error message.

errors () 
{ 
  label="File Name:Line Number:Error Code";
  list=`ls ./*.$1 | wc -l`;
  if [[ ${list} -eq 1 ]]; then
    echo ${label};
    echo "----------------------------------------";
    filename=`ls *.txt`;
    echo ${filename}:`find . -type f | grep -in *.txt -e ora\- -e pls\- -e sp2\-`;
  else
    if [[ ${list} -gt 1 ]]; then
      echo ${label};
      echo "----------------------------------------";
      find . -type f | grep --color=auto -in *.txt -e ora\- -e pls\- -e sp2\-;
    fi;
  fi
}

I hope it helps others now too.

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.

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.

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# 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

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.

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.

Selective Aggregation

Learning Outcomes

• Learn how to combine CASE operators and aggregation functions.
• Learn how to selective aggregate values.
• Learn how to use SQL to format report output.

Selective aggregation is the combination of the CASE operator and aggregation functions. Any aggregation function adds, sums, or averages the numbers that it finds; and when you embed the results of a CASE operator inside an aggregation function you get a selective result. The selectivity is determined by the WHEN clause of a CASE operator, which is more or less like an IF statement in an imperative programming language.

The prototype for selective aggregation is illustrated with a SUM function below:

SELECT   SUM(CASE
               WHEN left_operand = right_operand THEN result
               WHEN left_operand > right_operand THEN result
               WHEN left_operand IN (SET OF comma-delimited VALUES) THEN result
               WHEN left_operand IN (query OF results) THEN result
               ELSE alt_result
             END) AS selective_aggregate
FROM     some_table;

A small example let’s you see how selective aggregation works. You create a PAYMENT table and PAYMENT_S sequence for this example, as follows:

-- Create a PAYMENT table.
CREATE TABLE payment
( payment_id     NUMBER
, payment_date   DATE	      CONSTRAINT nn_payment_1 NOT NULL
, payment_amount NUMBER(20,2) CONSTRAINT nn_payment_2 NOT NULL
, CONSTRAINT pk_payment PRIMARY KEY (payment_id));
 
-- Create a PAYMENT_S sequence.
CREATE SEQUENCE payment_s;

After you create the table and sequence, you should insert some data. You can match the values below or choose your own values. You should just insert values for a bunch of rows.

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DECLARE
  -- Create local collection data types.
  TYPE pmtval IS TABLE OF NUMBER(20,2);
  TYPE smonth IS TABLE OF VARCHAR2(3);
 
  -- Create variable to hold the list of payments.
  payments PMTVAL := pmtval();
 
  -- Declare month arrays.
  short_month SMONTH := smonth('JAN','FEB','MAR','APR','MAY','JUN'
                              ,'JUL','AUG','SEP','OCT','NOV','DEC');
 
  -- Declare variable values.
  month      VARCHAR2(3);
  year       NUMBER := '2019';
  pmt_date   DATE; 
  tpmt_date  VARCHAR2(11);
 
  -- Declare default number of random payments.
  payment_number  NUMBER := 10000;
BEGIN
  -- Populate payment list. 
  FOR i IN 1..payment_number LOOP
    payments.EXTEND;
    SELECT   ROUND(dbms_random.value() * 1000,0)
    ||       '.'
    ||       ROUND(dbms_random.value() * 100,0)
    INTO     payments(payments.COUNT)
    FROM     dual;
  END LOOP;
 
  -- Create and populate payment date and amount.
  FOR i IN 1..payment_number LOOP
    -- Assign random month value.
    month := short_month(dbms_random.value(1,short_month.COUNT));
 
    -- Assign random day of the month value and assemble random date.
    IF month IN ('JAN','MAR','MAY','JUL','AUG','OCT','DEC') THEN
      pmt_date := ROUND(dbms_random.value(1,31),0) || '-' || month || '-' || year;
    ELSIF month IN ('APR','JUN','SEP','NOV') THEN
      pmt_date := ROUND(dbms_random.value(1,30),0) || '-' || month || '-' || year;
    ELSE
      pmt_date := ROUND(dbms_random.value(1,28),0) || '-' || month || '-' || year;
    END IF;
 
    -- Insert values into the PAYMENT table.
    INSERT INTO payment
    ( payment_id, payment_date, payment_amount )
    VALUES
    ( payment_s.NEXTVAL, pmt_date, payments(i));
  END LOOP;
 
  -- Commit the writes.
  COMMIT;
END;
/

After inserting 10,000 rows, you can get an unformatted total with the following query:

-- Query total amount.
SELECT   SUM(payment_amount) AS payment_total
FROM     payment;

It outputs the following:

PAYMENT_TOTAL
-------------
   5011091.75

You can nest the result inside the TO_CHAR function to format the output, like

-- Query total formatted amount.
SELECT   TO_CHAR(SUM(payment_amount),'999,999,999.00') AS payment_total
FROM     payment;

It outputs the following:

PAYMENT_TOTAL
---------------
   5,011,091.75

Somebody may suggest that you use a PIVOT function to rotate the data into a summary by month but the PIVOT function has limits. The pivoting key must be numeric and the column values will use only those numeric values.

-- Pivoted summaries by numeric monthly value.
SELECT   *
FROM    (SELECT EXTRACT(MONTH FROM payment_date) payment_month
         ,      payment_amount
         FROM   payment)
         PIVOT (SUM(payment_amount) FOR payment_month IN
                 (1,2,3,4,5,6,7,8,9,10,11,12));

It outputs the following:

	 1	    2	       3	  4	     5		6	   7	      8 	 9	   10	      11	 12
---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ----------
 245896.55  430552.36  443742.63  457860.27  470467.18	466370.71  415158.28  439898.72  458998.09  461378.56  474499.22  246269.18

You can use selective aggregation to get the results by a character label, like

SELECT   SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) = 1
             AND  EXTRACT(YEAR FROM payment_date) = 2019  THEN payment_amount
           END) AS "JAN"
,        SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) = 2
             AND  EXTRACT(YEAR FROM payment_date) = 2019  THEN payment_amount
           END) AS "FEB"
,        SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) = 3
             AND  EXTRACT(YEAR FROM payment_date) = 2019  THEN payment_amount
           END) AS "MAR"
,        SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) IN (1,2,3)
             AND  EXTRACT(YEAR FROM payment_date) = 2019 THEN payment_amount
           END) AS "1FQ"
,        SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) = 4
             AND  EXTRACT(YEAR FROM payment_date) = 2019  THEN payment_amount
           END) AS "APR"
FROM     payment;

It outputs the following:

       JAN	  FEB	     MAR	1FQ	   APR
---------- ---------- ---------- ---------- ----------
 245896.55  430552.36  443742.63 1120191.54  457860.27

You can format the output with a combination of the TO_CHAR and LPAD functions. The TO_CHAR allows you to add a formatting mask, complete with commas and two mandatory digits to the right of the decimal point. The reformatted query looks like

COL JAN FORMAT A13 HEADING "Jan"
COL FEB FORMAT A13 HEADING "Feb"
COL MAR FORMAT A13 HEADING "Mar"
COL 1FQ FORMAT A13 HEADING "1FQ"
COL APR FORMAT A13 HEADING "Apr"
SELECT   LPAD(TO_CHAR(SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) = 1
             AND  EXTRACT(YEAR FROM payment_date) = 2019  THEN payment_amount
           END),'9,999,999.00'),13,' ') AS "JAN"
,        LPAD(TO_CHAR(SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) = 2
             AND  EXTRACT(YEAR FROM payment_date) = 2019  THEN payment_amount
           END),'9,999,999.00'),13,' ') AS "FEB"
,        LPAD(TO_CHAR(SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) = 3
             AND  EXTRACT(YEAR FROM payment_date) = 2019  THEN payment_amount
           END),'9,999,999.00'),13,' ') AS "MAR"
,        LPAD(TO_CHAR(SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) IN (1,2,3)
             AND  EXTRACT(YEAR FROM payment_date) = 2019 THEN payment_amount
           END),'9,999,999.00'),13,' ') AS "1FQ"
,        LPAD(TO_CHAR(SUM(
           CASE
             WHEN EXTRACT(MONTH FROM payment_date) = 4
             AND  EXTRACT(YEAR FROM payment_date) = 2019  THEN payment_amount
           END),'9,999,999.00'),13,' ') AS "APR"
FROM     payment;

It displays the formatted output:

Jan	      Feb	    Mar 	  1FQ		Apr
------------- ------------- ------------- ------------- -------------
   245,896.55	 430,552.36    443,742.63  1,120,191.54    457,860.27

INSERT Statement

Learning Outcomes

• Learn how to use positional- and named-notation in INSERT statements.
• Learn how to use the VALUES clause in INSERT statements.
• Learn how to use subqueries in INSERT statements.

The INSERT statement lets you enter data into tables and views in two ways: via an INSERT statement with a VALUES clause and via an INSERT statement with a query. The VALUES clause takes a list of literal values (strings, numbers, and dates represented as strings), expression values (return values from functions), or variable values.

Query values are results from SELECT statements that are subqueries (covered earlier in this appendix). INSERT statements work with scalar, single-row, and multiple-row subqueries. The list of columns in the VALUES clause or SELECT clause of a query (a SELECT list) must map to the positional list of columns that defines the table. That list is found in the data dictionary or catalog. Alternatively to the list of columns from the data catalog, you can provide a named list of those columns. The named list overrides the positional (or default) order from the data catalog and must provide at least all mandatory columns in the table definition. Mandatory columns are those that are not null constrained.

Oracle databases differ from other databases in how they implement the INSERT statement. Oracle doesn’t support multiple-row inserts with a VALUES clause. Oracle does support default and override signatures as qualified in the ANSI SQL standards. Oracle also provides a multiple- table INSERT statement. This section covers how you enter data with an INSERT statement that is based on a VALUES clause or a subquery result statement. It also covers multiple-table INSERT statements.

The INSERT statement has one significant limitation: its default signature. The default signature is the list of columns that defines the table in the data catalog. The list is defined by the position and data type of columns. The CREATE statement defines the initial default signature, and the ALTER statement can change the number, data types, or ordering of columns in the default signature.

The default prototype for an INSERT statement allows for an optional column list that overrides the default list of columns. When you provide the column list you choose to implement named-notation, which is the right way to do it. Relying on the insertion order of the columns is a bad idea. An INSERT statement without a list of column names is a position-notation statement. Position-notation is bad because somebody can alter that order and previously written INSERT statements will break or put data in the wrong columns.

Like methods in OOPLs, an INSERT statement without the optional column list constructs an instance (or row) of the table using the default constructor. The override constructor for a row is defined by any INSERT statement when you provide an optional column list. That’s because it overrides the default constructor.

The generic prototype for an INSERT statement is confusing when it tries to capture both the VALUES clause and the result set from a query. Therefore, I’ve opted to provide two generic prototypes.

Insert by value

The first uses the VALUES clause:

INSERT
INTO table_name
[( column1, column2, column3, ...)] VALUES
( value1, value2, value3, ...);

Notice that the prototype for an INSERT statement with the result set from a query doesn’t use the VALUES clause at all. A parsing error occurs when the VALUES clause and query both occur in an INSERT statement.

The second prototype uses a query and excludes the VALUES clause. The subquery may return one to many rows of data. The operative rule is that all columns in the query return the same number of rows of data, because query results should be rectangles—rectangles made up of one to many rows of columns.

Insert by subquery

Here’s the prototype for an INSERT statement that uses a subquery:

INSERT
INTO table_name
[( column1, column2, column3, ...)]
( SELECT value1, value2, value3, ... FROM table_name WHERE ...);

A query, or SELECT statement, returns a SELECT list. The SELECT list is the list of columns, and it’s evaluated by position and data type. The SELECT list must match the definition of the table or the override signature provided.

Default signatures present a risk of data corruption through insertion anomalies, which occur when you enter bad data in tables. Mistakes transposing or misplacing values can occur more frequently with a default signature, because the underlying table structure can change. As a best practice, always use named notation by providing the optional list of values; this should help you avoid putting the right data in the wrong place.

The following subsections provide examples that use the default and override syntax for INSERT statements in Oracle databases. The subsections also cover multiple-table INSERT statements and a RETURNING INTO clause, which is an extension of the ANSI SQL standard. Oracle uses the RETURNING INTO clause to manage large objects, to return autogenerated identity column values, and to support some of the features of Oracle’s dynamic SQL. Note that Oracle also supports a bulk INSERT statement, which requires knowledge of PL/SQL.

DESCRIBE table_name

Name                                 Null?    Type
------------------------------------ -------- --------
RENTAL_ID                            NOT NULL NUMBER
CUSTOMER_ID                          NOT NULL NUMBER
CHECK_OUT_DATE                       NOT NULL DATE
RETURN_DATE                                   DATE
CREATED_BY                           NOT NULL NUMBER
CREATION_DATE                        NOT NULL DATE
LAST_UPDATED_BY                      NOT NULL NUMBER
LAST_UPDATE_DATE                     NOT NULL DATE

Name                                      Null?    Type
------------------------------------ -------- --------
RENTAL_ID                            NOT NULL NUMBER
CUSTOMER_ID                          NOT NULL NUMBER
CHECK_OUT_DATE                       NOT NULL DATE
RETURN_DATE                                   DATE
CREATED_BY                           NOT NULL NUMBER
CREATION_DATE                        NOT NULL DATE
LAST_UPDATED_BY                      NOT NULL NUMBER
LAST_UPDATE_DATE                     NOT NULL DATE

SQL> INSERT INTO rental
  2  VALUES
  3  ( 1086
  4  , 1009
  5  , SYSDATE
  6  , TRUNC(SYSDATE + 5) 7 ,1
  8  , SYSDATE
  9  , 1
 10  , SYSDATE);

  5  , TO_DATE('15-APR-2011 12:53:01','DD-MON-YYYY HH24:MI:SS')

  5  , CAST('15-APR-2011 12:53:02' AS DATE)

  5  ,  CAST('15-APR-2011 12:53:02' AS DATE) FROM dual
        *
ERROR AT line 1:
ORA-01830: DATE format picture ends before converting entire input string

  5  ,  CAST(CAST('15-APR-2011 12:53:02' AS TIMESTAMP) AS DATE)

SQL> SELECT   rental_s1.NEXTVAL FROM dual;

  3  ( rental_s1.NEXTVAL

SQL> SELECT   contact_id
  2  FROM     contact
  3  WHERE    last_name = 'Potter'
  4  AND      first_name = 'Harry';

SQL> INSERT INTO rental
  2  ( rental_id
  3  , customer_id
  4  , check_out_date
  5  , return_date
  6  , created_by
  7  , creation_date
  8  , last_updated_by
  9  , last_update_date )
10 VALUES
 11  ( rental_s1.NEXTVAL
 12  ,(SELECT   contact_id
 13    FROM     contact
 14    WHERE    last_name = 'Potter'
 15    AND      first_name = 'Harry')
 16  , SYSDATE
 17  , TRUNC(SYSDATE + 5)
 18  , 1
 19  , SYSDATE
 20  , 3
 21  , SYSDATE);

,(SELECT   contact_id
  *
ERROR AT line 3:
ORA-01427: single-ROW subquery returns more than one ROW

Name                             Null?    Type
 ------------------------------- -------- -----------------------
ITEM_DESC                        NOT NULL CLOB
ITEM_ICON                        NOT NULL BLOB
ITEM_PHOTO                                BINARY FILE LOB

EMPTY_BLOB()
EMPTY_CLOB()

 10  , BFILENAME('VIRTUAL_DIRECTORY_NAME', 'file_name.png')

INSERT INTO some_table
[( column1, column2, column3, ...)]
VALUES
( value1, value2, value3, ...)
RETURNING column1 INTO local_variable;

Name                                 Null?    Type
------------------------------------ -------- --------------
PARENT_ID                            NOT NULL NUMBER
PARENT_NAME                                   VARCHAR2(10)

Name                                 Null?    Type
------------------------------------ -------- --------------
CHILD_ID                             NOT NULL NUMBER
PARENT_ID                                     NUMBER
PARENT_NAME                                   VARCHAR2(10)

SQL> INSERT INTO parent
  2  VALUES
  3  ( parent_s1.NEXTVAL 4 ,'One Parent');
 
SQL> INSERT INTO child
  2  VALUES
  3  ( child_s1.NEXTVAL 4 , parent_s1.CURRVAL 5 ,'One Child');

SQL> INSERT INTO child
  2  VALUES
  3  ( child_s1.NEXTVAL -- CHILD_ID
  4  , parent_s1.CURRVAL -- PARENT_ID
  5  ,'One Child') -- CHILD_NAME
  6  /

INSERT
INTO table_name
[( column1, column2, column3, ...)]
( SELECT value1, value2, value3, ... FROM table_name WHERE ...);

If you’re wondering about this post, it shows the basic array of a set of integers and strings before showing you how to create nested tables of data in PostgreSQL. By the way, they’re not called nested tables in PostgreSQL, like they are in Oracle but perform like their Oracle cousins.

Let’s create a table with an auto-incrementing column and two arrays, one array of integers and another of strings:

-- Conditionally drop the demo table.
DROP TABLE IF EXISTS demo;
 
-- Create the test table.
CREATE TABLE demo
( demo_id     serial
, demo_number integer[5]
, demo_string varchar(5)[7]);

You can insert test values like this:

INSERT INTO demo
(demo_number, demo_string)
VALUES
( array[1,2,3,4,5]
, array['One','Two','Three','Four','Five','Six','Seven']);

Then, you can query them with this unnest function, like:

SELECT  unnest(demo_number) AS numbers
,       unnest(demo_string) AS strings
FROM    demo;

It returns:

 numbers | strings
---------+---------
 1       | One
 2       | Two
 3       | Three
 4       | Four
 5       | Five
         | Six
         | Seven
(7 rows)

You may note that the two arrays are asymmetrical. It only becomes an issue when you navigate the result in a PL/pgSQL cursor or imperative programming language, like Python.

Now, let’s do something more interesting like work with a composite user-defined type, like the player structure. You would create the composite user-defined type with this syntax:

-- Conditionally drop the player type.
DROP TYPE IF EXISTS player;
 
-- Create the player type.
CREATE TYPE player AS
( player_no        integer
, player_name      varchar(24)
, player_position  varchar(14)
, ab               integer
, r                integer
, h                integer
, bb               integer
, rbi              integer );

You can create a world_series table that include a players column that uses an array of player type, like

-- Conditionally drop the world_series table.
DROP TABLE IF EXISTS world_series;
 
-- Create the player type.
CREATE TABLE world_series
( world_series_id  serial
, team             varchar(24)
, players          player[30]
, game_no          integer
, year             integer );

If you’re familiar with the Oracle Database, you’d have to specify a tested table in the syntax. Fortunately, PostgreSQL doesn’t require that.

Insert two rows with the following statement:

INSERT INTO world_series
( team
, players
, game_no
, year )
VALUES
('San Francisco Giants'
, array[(24,'Willie Mayes','Center Fielder',5,0,1,0,0)::player
       ,(5,'Tom Haller','Catcher',4,1,2,0,2)::player]
, 4
, 1962 );

You can append to the array with the following syntax. A former student and I have a disagreement on whether this is shown in the PostgreSQL 8.15.4 Modifying Array documentation. I believe it can be inferred from the document and he doesn’t believe so. Anyway, here’s how you add an element to an existing array in a table with the UPDATE statement:

UPDATE world_series
SET    players = (SELECT array_append(players,(7,'Henry Kuenn','Right Fielder',3,0,0,1,0)::player) FROM world_series)
WHERE  team = 'San Francisco Giants'
AND    year = 1962
AND    game_no = 4;

Like Oracle’s nested tables, PostgreSQL’s arrays of composite user-defined types requires writing a PL/pgSQL function. I’ll try to add one of those shortly in another blog entry to show you how to edit and replace entries in stored arrays of composite user-defined types.

You can query the unnested rows and get a return set like a Python tuple with the following query:

SELECT unnest(players) AS player_list
FROM   world_series
WHERE  team = 'San Francisco Giants'
AND    year = 1962
AND    game_no = 4;

It returns the three rows from the players array:

                 player_list
----------------------------------------------
 (24,"Willie Mayes","Center Field",5,0,1,0,0)
 (5,"Tom Haller",Catcher,4,1,2,0,2)
 (7,"Henry Kuenn","Right Fielde",3,0,0,1,0)
(3 rows)

It returns the data set in entry-order. If we step outside of the standard 8.15 Arrays PostgreSQL Documentation, you can do much more with arrays (or nested tables). The balance of this example demonstrates some new syntax that helps you achieve constructive outcomes in PostgreSQL.

You can use a Common Table Expression (CTE) to get the columnar display of the player composite user-defined type. This type of solution is beyond the standard , like:

WITH list AS
 (SELECT unnest(players) AS row_result
  FROM   world_series
  WHERE  team = 'San Francisco Giants'
  AND    year = 1962
  AND    game_no = 4)
SELECT  (row_result).player_name
,       (row_result).player_no
,       (row_result).player_position
FROM     list;

If you’re unfamiliar with accessing composite user-defined types, I wrote a post on that 7 years ago. You can find the older blog entry PostgreSQL Composites on my blog.

It returns only the three requested columns of the player composite user-defined type:

 player_name  | player_no | player_position
--------------+-----------+-----------------
 Willie Mayes |        24 | Center Fielder
 Tom Haller   |         5 | Catcher
 Henry Kuenn  |         7 | Right Fielder
(3 rows)

You should note that the data is presented in an entry-ordered manner when unnested alone in the SELECT-list. That behavior changes when the SELECT-list includes non-array data.

The easiest way to display data from the non-array and array columns is to list them inside the SELECT-list of the CTE, like:

WITH list AS
 (SELECT game_no AS game
  ,      year
  ,      unnest(players) AS row_result
  FROM   world_series
  WHERE  team = 'San Francisco Giants'
  AND    year = 1962
  AND    game_no = 4)
SELECT   game
,        year 
,       (row_result).player_name
,       (row_result).player_no
,       (row_result).player_position
FROM     list;

It returns an ordered set of unnested rows when you include non-array columns, like:

 game | year | player_name  | player_no | player_position
------+------+--------------+-----------+-----------------
    4 | 1962 | Henry Kuenn  |         7 | Right Fielder
    4 | 1962 | Tom Haller   |         5 | Catcher
    4 | 1962 | Willie Mayes |        24 | Center Fielder
(3 rows)

While you can join the world_series table to the unnested array rows (returned as a derived table, its a bad idea. The mechanics to do it require you to return the primary key column in the same SELECT-list of the CTE. Then, you join the CTE list to the world_series table by using the world_series_id primary key.

However, there is no advantage to an inner join approach and it imposes unnecessary processing on the database server. The odd rationale that I heard when I noticed somebody was using a CTE to base-table join was: “That’s necessary so they could use column aliases for the non-array columns.” That’s not true because you can use the aliases inside the CTE, as shown above when game is an alias to the game_no column.

As always, I hope this helps those looking to solve a problem in PostgreSQL.

After you create and provision the Oracle Database 21c Express Edition (XE), you can create a c##student container user with the following two step process.

1. Create a c##student Oracle user account with the following command:

   CREATE USER c##student IDENTIFIED BY student DEFAULT TABLESPACE users QUOTA 200M ON users TEMPORARY TABLESPACE temp;

   CREATE USER c##student IDENTIFIED BY student DEFAULT TABLESPACE users QUOTA 200M ON users TEMPORARY TABLESPACE temp;

2. Grant necessary privileges to the newly created c##student user:

   GRANT CREATE CLUSTER, CREATE INDEXTYPE, CREATE OPERATOR , CREATE PROCEDURE, CREATE SEQUENCE, CREATE SESSION , CREATE TABLE, CREATE TRIGGER, CREATE TYPE , CREATE VIEW TO c##student;

   GRANT CREATE cluster, CREATE indextype, CREATE operator , CREATE PROCEDURE, CREATE SEQUENCE, CREATE SESSION , CREATE TABLE, CREATE TRIGGER, CREATE TYPE , CREATE VIEW TO c##student;

As always, I hope this helps those looking for how to do something that’s less than clear because everybody uses tools.