siebel crm unicode conversion 2 – the dba perspective brian hitchcock ocp 8, 8i, 9i dba sun...

Siebel CRM Unicode Conversion 2 – The DBA

PerspectiveBrian Hitchcock

OCP 8, 8i, 9i DBA

Sun Microsystems

[email protected]

[email protected] Technical Services DBA

Brian Hitchcock November 11, 2004

www.brianhitchcock.net

mailto:[email protected]

mailto:[email protected]

DCSIT Technical Services DBA



CRM Unicode Conversion

Three separate presentations– 1) The overall conversion process

What we had, what we wanted, how to get there Issues that come up during conversion

– 2) Multi-byte data in the existing CRM db What’s the issue, how did it happen A general method to find and fix this problem

– 3) The actual conversion What really happened Issues that came up and how they were resolved

Focus on DBA issues, not Siebel application




How Did I Get Involved?

Sleeping in a meeting… Heard someone say

– “We told the users to stop entering Japanese into the CRM system but we aren’t sure they stopped”

Woke up, said– “I’ve done that before…”– See “Case of the Missing Kanji”

Don’t wake up in meetings…




What’s The Issue?

Existing Siebel CRM system– Oracle 8.1.7.4– Single-byte character set (WE8ISO8859P1)

Interface systems– Multi-byte character set(s) (UTF8)– Handle data between single,multi-byte apps

Want to convert to Unicode– Siebel, database, interfaces all should be UTF8– Eliminate interface systems




What We Had

Siebel CRM

Oracle Db

Custdb Apac

Users

Tcustdb Apac

Custdb Emea

Custdb Amer

Tcustdb Emea

Amer

Emea

Apac UTF8

WE8ISO8859P1

UTF8

UTF8

UTF8

WE8ISO8859P1

8859P1

8859P1

Ordering System




What We Wanted

Siebel CRM

Oracle Db

Custdb Apac

Users

Custdb Emea

Custdb Amer

Amer

Emea

Apac

WE8ISO8859P1

UTF8

UTF8

AL32UTF8

UTF8

UTF8

Ordering System




What We Wanted

All data in one database– All languages– Unicode

Eliminate interface systems– Reduce support costs

Support increased CRM functionality– All data in one place– Supports new business functionality




Multi-byte Data In Source Db?

Source db is WE8ISO8859P1– Single-byte character set– Doesn’t support multi-byte characters

That’s the official story The reality is somewhat different

What, if any multi-byte data is in source db?– How to determine correct character set?– How to find, how to fix?– Japanese, Chinese, others?




But Wait, There’s More…

Not just multi-byte data to look for Non-p1 character data also

– Non multi-byte character data– Could be WE P1 (western European)

German, Italian, French etc.

– Could be WE Pn Polish, Greek, Russian etc.

How to find?




How Polish Was Handled

Use separate app that sends polish (P2) to CRM database

Stored in P1 db Triggers move this polish data to TWCD Triggers in TWCD

– Know that it’s polish (P2)– Convert to UTF8 and send to WCD db

Therefore, multiple languages in Siebel P1 db




What’s the Problem?

Character data from multiple languages– Stored in oracle db– Db configured for P1

P1 supports multiple WE languages Does not support polish, Russian, etc.

Need to find all such character data Non-p1 can be

– Single-byte (polish, Russian, etc.)– Multi-byte (Japanese, Chinese, etc.)




Single-byte Character Sets

All Pn (8859-1, 8859-2, etc.) character sets– Share same range of byte codes, 0 to 255– Above 0xA1 (decimal 161)

Same byte codes represent different characters

Example– WE8ISO8859P1 (8859-1)

Byte code 0xA3 (decimal 163) is character £

– EE8ISO8859P2 (8859-2) Same byte code, 0xA3 is character Ł




Finding Non-p1 Char Data?

Logically– Examine db design, Siebel docs, figure out which

tables designed to store language specific (local language) data

– Some column (country code) in these tables to tell you which country data is from

– Determine correct character set for data from each country

– Convert these tables manually to AL32UTF8 as part of overall Unicode conversion process




Not Good

Want general method– No need to analyze the meaning of existing data– Need automated way to find all non-P1 char data

Can’t do it– No general way to determine if char data is P1 or

P2 or Pn As shown before, byte code 0xa3 (decimal 163)

Character £ in P1

Character Ł in P2




Good

But, can find non-ASCII data in general– And then find multi-byte character data

Use separate approach to find non-P1 Use PL/SQL code

– Examine every table– Examine every column that holds character data– Determine which rows if any are ASCII– Rows that aren’t ASCII are ‘suspect’– Identify tables that have any non-ASCII character data




Why Look For ASCII?

Character data that is ASCII– Only 7 bits used to encode character– 8th bit of every byte is 0– For non-ASCII, 8th byte is set

WE8ISO8859Pn Multi-byte, Japanese, Chinese, etc.

By eliminating all tables that are ASCII– No need to ask are they P1, P2, Pn or multi-byte– Greatly reduces the task




How To Find Non-ASCII?

Use SQL function convert– Convert a given column to ASCII character set– Compare resulting string with original– If original string is all ASCII

Will match converted string

– If not a match Column value is non-ASCII

Could be WE8ISO8859Pn

Could be multi-byte




Example Finding Non-ASCIIin WE8ISO8859P1 database

create table Psycho_Acircle (text VARCHAR2(100));

insert into Psycho_Acircle values (chr(197)||'BCDE');insert into Psycho_Acircle values ('ABCDE');

select * from Psycho_Acircle;

TEXT-----ÅBCDEABCDE

select convert(text,'US7ASCII','WE8ISO8859P1') from Psycho_Acircle;

CONVERT(TEXT,'US7ASCII','WE8ISO8859P1')---------------------------------------?BCDEABCDE

ÅBCDE is not the same as ?BCDE




Not Included

Did not scan– LONG datatype columns– CLOB datatype columns

Didn’t have any in schema

– PL/SQL code in database

Dev team determined this wasn’t needed




Scripts Strategy

Eliminate as much as possible– Identify all ASCII only tables– Left with set of non-ASCII tables

For remaining tables– Find likely Japanese character data– Verify it is Japanese– Copy to separate table– Remove from non-ASCII tables

Repeat for other languages– How to identify byte patterns for each language?




PL/SQL scripts

Scripts used– Scan_Table_1_Gen_Column_Info.sql– Scan_Table_2_Gen_Nonascii_rows_Info.sql– Scan_Table_3_Gen_NonasciiTables_NoLong.sql– Scan_Table_4_Gen_NonasciiTables_NonasciiCols_Only.sql– Scan_Table_5_Gen_NonasciiTables_YesLong.sql– Scan_Table_6_Gen_NA_EUCJP_info_sql_col_info.sql– Scan_Table_7_Gen_NA_EUCJP_Tables.sql– Scan_Table_8_Gen_NA_EUCJP_2_rows_info.sql




Scripts

Each script generates table(s)– Output of each script stored in table(s)

Next script uses tables Lots of intermediate data stored

– Helped develop scripts– Each script simpler– Provided extra output for developers, analysts to

help them verify results Is this data really Japanese?




What Does Each Script Do?

Scan_Table_1_Gen_Column_Info.sql– Scans all tables in a schema– Creates two tables

Table_Gen_Info Info on all tables

Table_Column_Info Info on character columns

Which contain any non-ASCII strings Doesn’t include LONG columns

Can’t use SQL functions on LONG datatype





Scan_Table_2_Gen_Nonascii_rows_Info.sql– Use table Table_Column_Info– Examine tables with non-ASCII character data– Creates two tables

Table_NonAscii_info Number of rows, columns with non-ASCII data

Table_NonAscii_SQL SQL to extract non-ASCII data from each table Useful for developers, analysts to extract data from

other environments





Scan_Table_3_Gen_NonasciiTables_NoLong.sql

– Use tables table_gen_info, table_nonascii_sql– Create copies of tables that have non-ASCII data– Copies contain only the non-ASCII rows

Have all character columns of original table Helps identify which country data is from

– Creates tables as select * from <tablename> Doesn’t work on tables with LONG column Tables named NONASCII_<tablename>





Scan_Table_4_Gen_NonasciiTables_NonasciiCols_Only.sql

– Similar to third (previous) script– Table copies only contain columns that have non-

ASCII data– Does handle tables with LONG column– Creates tables of form NA_CO_<tablename>

Set of tables containing all non-ASCII data in the schema





Scan_Table_5_Gen_NonasciiTables_YesLong.sql

– Creates copies of tables having non-ASCII data– Copy tables have all char columns of base table– Only copies tables that have LONG column– Companion to third script

Deals with tables that have LONG column Tables named NONASCII_<tablename>

– Now have complete set of tables Have all non-ASCII char columns of base tables




Katakana, Hiragana?

How to find Japanese character data?– Look at hex dump of character data and see lots

of ¥_¥ and ¤_¤– The byte code of ¥ is A4, ¤ is A5– Many Japanese transliterated terms (company

names) start with these bytes– Typical of EUCJP character set– Find rows that contain '%¥_¥%' or '%¤_¤%‘– repeated ¥ or ¤ means EUCJP more likely– Verify that these rows are indeed Japanese





Scan_Table_6_Gen_NA_EUCJP_info_sql_col_info.sql

– For table copies with non-ASCII columns only– Look for specific pattern of '%¥_¥%'– Or '%¤_¤%‘– Creates tables

Table_NA_EUCJP_Info Table_NA_EUCJP_SQL Table_NA_EUCJP_COL_INFO




6th Script

What does each table contain?– Table_NA_EUCJP_Info

Number of EUCJP rows in each non-ASCII table

– Table_NA_EUCJP_SQL SQL to extract EUCJP rows

– Table_NA_EUCJP_COL_INFO Number of EUCJP rows in each column





Scan_Table_7_Gen_NA_EUCJP_Tables.sql– Create two copies of each table that has EUCJP

Contain rows that have EUCJP First table, all char columns Second, only EUCJP columns

– Tables created have names EUCJP_<tablename> ECUJP_CO_<tablename>




After 7th Script

We have identified EUCJP rows– In non-ASCII tables– Copied these rows to separate tables

Delete these rows from the non-ASCII tables As we identify rows from a specific char set

– Remove them from the non-ASCII tables– Smaller and smaller set of unknown rows





Scan_Table_8_Gen_NA_EUCJP_2_rows_info.sql

– Find rows containing ¥ or ¤– Could be Japanese– Could be WE




Results

For each script– Time to run– Output– %of total db that is non-ASCII– Demonstrates power of this approach– No attempt to speed up

Only need to scan once, no need for speed– Copy prod data to separate environment– Run scripts there, develop the SQL to correctly convert the

non-ASCII data as needed Apply to prod as part of Unicode conversion




Results

Scripts run against copy of production db Database

– 25Gb total, but 13Gb free space– 12Gb of actual data to scan– (be skeptical when people tell you they support

multi-terabyte dbs, size of actual data counts)

Scripts create tables in the same schema they run in




Results

Script 1 – 2hours– Scanned 12Gb of data– 2483 tables, 63138 columns– Created two tables

Table_gen_info Table_column_info




1st Script Results

SQL> select * from Table_Gen_Info where rownum <=10;

TABLENAME NUMROWS NUMCOLS NUMCHARCOLS NUMCLOBCOLS NUMLONGCOLS

------------------------------ ---------- ---------- ----------- ----------- -----------

ACCNT_STAT 15775 5 3 0 0

AMER_AR_OWNER 1085497 7 6 0 0

AMER_AR_T 1060 3 2 0 0

APAC_AR_OWNER 2770 6 6 0 0

AR_ADMIN 5578 35 31 0 0

AR_CON 3573 22 17 0 0

AR_STAT 88652 7 5 0 0

AUDIT_TABLE 53301 29 26 0 0

CONT_CREATED 515126 2 2 0 0

CON_CREATED 184744 2 2 0 0




1st Script ResultsSQL> select * from Table_Column_Info where rownum <=20;

TABLENAME NUMROWS NUMCHARCOLS CHARCOLNUM CHARCOLNAME NUMNONASCIIROWS

------------------------------ ---------- ----------- ---------- ------------ ---------------

ACCNT_STAT 15775 3 1 WCD 0

ACCNT_STAT 15775 3 2 STATUS 0

ACCNT_STAT 15775 3 3 R4_STATUS 0

...

...

...

AR_ADMIN 5578 31 1 R4_ID 0

AR_ADMIN 5578 31 2 R4_SR_NUM 0

AR_ADMIN 5578 31 3 X_DESC 72

20 rows selected.

SQL>




2nd Script Results

12 minutes– 68 tables that have non-ASCII char data– 68 SQL statements

Overall– We have 12Gb of data– 68/2483 tables have any non-ASCII char data– Only 3% of the tables

But they’re some of the biggest tables Schema analysis much easier on 68 tables




2nd Script resultsSQL> select * from Table_NonAscii_Info where rownum <= 10;

TABLENAME NUMROWS NUMNONASCIIROWS NUMCOLS NUMNONASCIICOLS

------------------------------ ---------- --------------- ---------- ---------------

AR_ADMIN 5578 692 35 6

AR_CON 3573 107 22 3

AUDIT_TABLE 53301 17 29 1

CX_S_ADDR_ORG_XM 69470 275 19 5

C_ACCOUNT 17897 1114 20 1

C_ACT 6562 933 21 6

C_ADDRESS 25590 5490 28 6

C_AR 88638 3760 26 6

C_CONTACT 52574 10401 20 3

C_OPTY 2139 119 25 4




2nd Script ResultsSQL> select * from Table_NonAscii_SQL where rownum <= 10;

TABLENAME LENGTHNONASCIISQL

------------------------------ -----------------

NONASCIISQL

--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

AR_ADMIN 445

select count(*) from AR_ADMIN where 1=0 or X_DESC != CONVERT (X_DESC, 'US7ASCII', 'WE8ISO8859P1') or LAST_NAME != CONVERT (LAST_NAME, 'US7ASCII', 'WE8ISO8859P1') or FST_NAME != CONVERT (FST_NAME, 'US7

ASCII', 'WE8ISO8859P1') or ACCOUNT != CONVERT (ACCOUNT, 'US7ASCII', 'WE8ISO8859P1') or OWNER_LAST_NAME != CONVERT (OWNER_LAST_NAME, 'US7ASCII', 'WE8ISO8859P1') or R3_CREATED_LAST_NAME != CONVERT (R3_C

REATED_LAST_NAME, 'US7ASCII', 'WE8ISO8859P1')

AR_CON 233

select count(*) from AR_CON where 1=0 or OWNER_LAST != CONVERT (OWNER_LAST, 'US7ASCII', 'WE8ISO8859P1') or OWNER_FST != CONVERT (OWNER_FST, 'US7ASCII', 'WE8ISO8859P1') or R3_X_NOTES != CONVERT (R3_X_N

OTES, 'US7ASCII', 'WE8ISO8859P1')

AUDIT_TABLE 100

select count(*) from AUDIT_TABLE where 1=0 or FIELD2 != CONVERT (FIELD2, 'US7ASCII', 'WE8ISO8859P1')




3rd Script Results 10 minutes

– Create copies of non-ASCII tables– Copies contain all character columns

LONG columns not included– Creates 65 tables

SQL> select table_name from user_tables where table_name like 'NONASCII%'

and table_name not like '%_ORIG‘ and rownum <= 5;

TABLE_NAME

------------------------------

NONASCII_AR_ADMIN

NONASCII_AR_CON

NONASCII_AUDIT_TABLE

NONASCII_CX_S_ADDR_ORG_XM

NONASCII_C_ACCOUNT




4th Script Results

7 minutes– Create copies of non-ASCII tables– Copies contain only non-ASCII columns– Creates 68 tables

SQL> select table_name from user_tables where table_name like 'NA_CO_%‘ and rownum <= 5;

TABLE_NAME

------------------------------

NA_CO_AR_ADMIN

NA_CO_AR_CON

NA_CO_AUDIT_TABLE

NA_CO_CX_S_ADDR_ORG_XM

NA_CO_C_ACCOUNT




5th Script Results

1 minute– Create copies of non-ASCII tables– Copies contain all character columns

LONG column included

– Creates 3 tables only 3 non-ASCII tables have LONG column

TABLE_NAME

------------------------------

NONASCII_EIM_ACCNT_DTL

NONASCII_EIM_OPTY_DTL

NONASCII_S_CS_QUEST_LANG




6th Script Results

27 minutes– Scan non-ASCII tables– Find '%¥_¥%' or '%¤_¤%‘– Very likely EUCJP character set– Create three tables

Table_NA_EUCJP_Info (68 tables) Table_NA_EUCJP_SQL (5 tables) TABLE_NA_EUCJP_COL_INFO (213 columns)

– 5 tables have EUCJP character data




6th Script ResultsSQL> select * from Table_NA_EUCJP_Info where rownum <= 10;

TABLENAME NUM_NONASCII_ROWS NUM_NA_EUCJP_ROWS NUM_NONASCII_COLS NUM_NA_EUCJP_COLS

------------------------------ ----------------- ----------------- ----------------- -----------------

NA_CO_AR_ADMIN 5578 9 6 1

NA_CO_AR_CON 3573 4 3 1

NA_CO_AUDIT_TABLE 53301 0 1 0

NA_CO_CX_S_ADDR_ORG_XM 69470 0 5 0

NA_CO_C_ACCOUNT 17897 0 1 0

NA_CO_C_ACT 6562 0 6 0

NA_CO_C_ADDRESS 25590 0 6 0

NA_CO_C_AR 88638 0 6 0

NA_CO_C_CONTACT 52574 0 3 0

NA_CO_C_OPTY 2139 0 4 0




6th Script ResultsSQL> select * from Table_NA_EUCJP_SQL;

TABLENAME LEN_NA_EUCJP_SQL

---------------- ----------------

NA_EUCJP_SQL

--------------------------------------------------------------------------------------------------------

NA_CO_AR_ADMIN 91

select count(*) from NA_CO_AR_ADMIN where 1=0 or X_DESC like '%¥_¥%' or X_DESC like '%¤_¤%'

NA_CO_AR_CON 97

select count(*) from NA_CO_AR_CON where 1=0 or R3_X_NOTES like '%¥_¥%' or R3_X_NOTES like '%¤_¤%'

NA_CO_S_ADDR_ORG 97

select count(*) from NA_CO_S_ADDR_ORG where 1=0 or COMMENTS like '%¥_¥%' or COMMENTS like '%¤_¤%'

NA_CO_S_CONTACT 142

select count(*) from NA_CO_S_CONTACT where 1=0 or COMMENTS like '%¥_¥%' or COMMENTS like '%¤_¤%'

or X_DEPT like '%¥_¥%' or X_DEPT like '%¤_¤%'

NA_CO_S_SRV_REQ 200

select count(*) from NA_CO_S_SRV_REQ where 1=0 or X_NOTES like '%¥_¥%' or X_NOTES like '%¤_¤%'

or X_DESC like '%¥_¥%' or X_DESC like '%¤_¤%' or X_EMAIL_NOTES like '%¥_¥%' or X_EMAIL_NOTES like '%¤_¤%'




6th Script Results

SQL> select * from TABLE_NA_EUCJP_COL_INFO where rownum <=10;

TABLENAME NUMNONASCIIROWS NUMNACOLS NACOLNUM NAEUCJPCOLNAME NUMNAEUCJPROWS

------------------- --------------- ---------- ---------- ------------------------------ --------------

NA_CO_AR_ADMIN 5578 6 1 X_DESC 9

NA_CO_AR_ADMIN 5578 6 2 LAST_NAME 0

NA_CO_AR_ADMIN 5578 6 3 FST_NAME 0

NA_CO_AR_ADMIN 5578 6 4 ACCOUNT 0

NA_CO_AR_ADMIN 5578 6 5 OWNER_LAST_NAME 0

NA_CO_AR_ADMIN 5578 6 6 R3_CREATED_LAST_NAME 0

NA_CO_AR_CON 3573 3 1 OWNER_LAST 0

NA_CO_AR_CON 3573 3 2 OWNER_FST 0

NA_CO_AR_CON 3573 3 3 R3_X_NOTES 4

NA_CO_AUDIT_TABLE 53301 1 1 FIELD2 0




7th Script Results

6 minutes– Create two copies of each EUCJP tables– First copy has all character columns of table– Second copy has only the EUCJP columns– Tables named

EUCJP_<tablename> EUCJP_CO_<tablename>




7th Script ResultsSQL> select table_name from user_tables where table_name like 'EUCJP_%'

minus select 2 table_name from user_tables where table_name like 'EUCJP_CO_%';

TABLE_NAME

------------------------------

EUCJP_AR_ADMIN

EUCJP_AR_CON

EUCJP_S_ADDR_ORG

EUCJP_S_CONTACT

EUCJP_S_SRV_REQ

SQL> select table_name from user_tables where table_name like 'EUCJP_CO_%';

TABLE_NAME

------------------------------

EUCJP_CO_AR_ADMIN

EUCJP_CO_AR_CON

EUCJP_CO_S_ADDR_ORG

EUCJP_CO_S_CONTACT

EUCJP_CO_S_SRV_REQ




7th Script Results

EUCJP rows selected Reviewed by dev team

– EUCJP of all rows verified

Make copies of these tables for reference Delete the EUCJP rows from the non-ASCII

tables Further scanning of the non-ASCII tables

won’t consider the EUCJP rows




8th Script Results

47 minutes– Scan non-ASCII tables (again)– Find '%¥%' or '%¤%‘– Could be EUCJP character set

Could also be WE character data– Create three tables

Table_NA_EUCJP_2_Info Table_NA_EUCJP_2_SQL TABLE_NA_EUCJP_2_COL_INFO

– 3 tables have EUCJP character data




8th Script Results

Possible EUCJP rows selected Reviewed by dev team

– EUCJP of all rows verified

Make copies of these tables for reference Delete these EUCJP rows from the non-ASCII

tables Further scanning of the non-ASCII tables

won’t consider these EUCJP rows




Next Steps

What I had planned With the EUCJP rows verified and removed Scan non-ASCII tables (yet again) Look for 8859Pn character data

– How?– WE languages, single isolated 8-bit byte code

with ASCII (7-bit) byte codes on either side– Example: Bücher




Next Steps

Select likely WE rows from non-ASCII tables– Review with dev team– Determine source country for each row

Schema has ‘country code’ Select each row using character set of country

– Verify rows with fluent speaker for each country– Remove rows from non-ASCII tables as verified

What to do with remaining rows– Not sure…




What Really Happened?

After 8 scripts Dev team was able to

– Identify likely country for each non-ASCII row– I identified likely character set for each country– I selected rows for each country

Using identified character set

– Fluent speaker from each country verified Rows as selected were correct

– Wrote SQL to correctly convert rows to Unicode




Conversion How to convert non-ASCII rows to Unicode?

– New db uses AL32UTF8 character set

With correct character set identified After importing into new 9i database

– Convert back to WE8MSWIN1252– Convert to AL32UTF8– Example:

UPDATE <tablename> SET <column> =

CONVERT (<column>, WE8MSWIN1252, AL32UTF8);

UPDATE <tablename> SET <column> =

CONVERT (<column>, AL32UTF8, <charset>);




Script Summary

8 scripts, scanning 12 Gb of data– Run times

2 hours 12 minutes 10 minutes 7 minutes 1 minute 27 minutes 6 minutes 47 minutes

Total run time – 230 minutes, about 4 hours– Very slow development machine




Conclusions

For character set conversion– From any 8-bit character set (WE8ISO8859Pn)– To Unicode– Accept that some of the existing data may not be in the

database character set– Don’t assume, verify

Use PL/SQL scripts,identify non-ASCII character data Decide how to evaluate the non-ASCII data

Document, test, communicate– Make sure everyone knows how data from each character

set is identified




Books Used

Oracle PL/SQL By Example– Rozenzweig, Silvestrova Prentice Hall 2004– I needed lots of examples

multiple nested cursors

– Needed to get going fast

Got help from experienced PL/SQL developer– Quotes issue– Even they couldn’t explain why the specific

number of quotes works…but it did




CRM Unicode Conversion

Three separate presentations– 1) The overall conversion process

What we had, what we wanted, how to get there Issues that come up during conversion

– 2) Multi-byte data in the existing CRM db What’s the issue, how did it happen A general method to find and fix this problem

– 3) The actual conversion What really happened Issues that came up and how they were resolved

Focus on DBA issues, not Siebel application




PL/SQL Notes

Quotes of quotes– Hard to know how many you need– Experiment– Test

PL/SQL that generates SQL that contains quoted strings

Keep it simple Break up the task into multiple scripts Generate tables of results, next script uses table(s) as

input– Tables provide documentation of intermediate results




PL/SQL Notes

Second script– Looping to build up select SQL– Selects data from all non-ASCII columns

Initial select SQL has to be– NonAsciiSQL_stmt := 'select count(*) from '||

TableName||' where 1=0– Subsequent SQL of form NonAsciiSQL_stmt :=

NonAsciiSQL_stmt||' or '||TableCharColName||– Needed ‘where 1=0 so we could append further

OR clauses




PL/SQL Notes

LONG datatype– Third script created tables as select * from

Can’t do this when table has LONG column

– Fourth script create tables by building up the create table SQL one column at a time Skip the LONG column, if present in base table




PL/SQL Notes

DBMS_OUTPUT limitations– Only works for so long– Has limit of 1M characters

Scripts are not commercial grade– Testing statements are left in

Commented out

– No error trapping– Still development scripts– They work, but they aren’t pretty




PL/SQL Notes

Scripts setup to– Run in SQL*Plus user’s schema– Output tables created in user’s schema

Could easily change scripts– Store output tables in separate schema– Take a schema as input

Scan tables in specified schema




PL/SQL Script Example

Show PL/SQL of first script– Cursors with definitions that depend on loop

variable of outer loop– Quotes and more quotes– Generating insert statements that are inserting

strings of SQL




6th Script Textset serveroutput on size 1000000;

declare

cursor C_EucJpTabNames is

select table_name from user_tables

where table_name like 'NA_CO_%';

cursor C_EucJpTabCols (i_table_name varchar2) is

select column_name from user_tab_columns

where table_name = i_table_name

order by column_id;

TableName VARCHAR2(100);

TableRowCount NUMBER;

ColCount NUMBER;

TableCharColName VARCHAR(100);

NumAsciiPlusNon NUMBER;

TableCharColNum NUMBER;

Num_NA_EUCJP_Rows NUMBER;

TabNum_NA_EUCJP_Rows NUMBER;

Len_NA_EUCJP_SQL_stmt NUMBER;

TabNum_NA_EUCJP_Cols NUMBER;

CurNum_NA_EUCJP_Cols NUMBER;

Sql_stmt VARCHAR2(4000);

Sql_stmt2 VARCHAR2(4000) := 'COMMIT';

NA_EUCJP_SQL_stmt VARCHAR2(4000);

NA_EUCJP_SQL_stmt_insert VARCHAR2(4000);

NAColCount NUMBER;

BEGIN

--dbms_output.disable;

Sql_stmt := 'create table Table_NA_EUCJP_Info

(TableName VARCHAR2(30),

NUM_NONASCII_ROWS NUMBER,

NUM_NA_EUCJP_ROWS NUMBER,

NUM_NONASCII_COLS NUMBER,

NUM_NA_EUCJP_COLS NUMBER)';

execute immediate Sql_stmt;

Sql_stmt := 'create table Table_NA_EUCJP_SQL


Len_NA_EUCJP_SQL NUMBER,

NA_EUCJP_SQL VARCHAR2(4000))';





6th Script TextSql_stmt := 'create table Table_NA_EUCJP_Col_Info


NUMNONASCIIROWS NUMBER,

NUMNACOLS NUMBER,

NACOLNUM NUMBER,

NAEUCJPCOLNAME VARCHAR2(30),

NUMNAEUCJPROWS NUMBER)';


open C_EucJpTabNames;

LOOP

FETCH C_EucJpTabNames into TableName;

Exit when C_EucJpTabNames%NOTFOUND;

NA_EUCJP_SQL_stmt := 'select count(*) from '||TableName||' where 1=0';

NA_EUCJP_SQL_stmt_insert := '''select count(*) from '||TableName||' where 1=0';

execute immediate 'select count(*) from

user_tab_columns where table_name = ''' || TableName || '''' into NAColCount;

dbms_output.put_line('here is the NA_EUCJP_SQL_stmt_insert ');

dbms_output.put_line(SUBSTR(''||NA_EUCJP_SQL_stmt_insert||'',1,255));

dbms_output.put_line('table name is '||TableName);

execute immediate 'select count(*) from '||TableName into TableRowCount;

TableCharColNum := 0;

CurNum_NA_EUCJP_Cols := 0;

open C_EucJpTabCols (TableName);

LOOP

FETCH C_EucJpTabCols into TableCharColName;

Exit when C_EucJpTabCols%NOTFOUND;

dbms_output.put_line('This is column '||TableCharColName);

TableCharColNum := TableCharColNum + 1;

-- compute the number of EUCJP rows for this column...

execute immediate 'select count(*) from '||TableName||

' where '||TableCharColName||' like ''%¥_¥%'' or '

||TableCharColName||' like ''%¤_¤%''' into Num_NA_EUCJP_Rows;

dbms_output.put_line('This column has '||Num_NA_EUCJP_Rows||' NA_EUCJP_ rows');

IF Num_NA_EUCJP_Rows != 0 THEN

NA_EUCJP_SQL_stmt := NA_EUCJP_SQL_stmt||' or '||TableCharColName||

' like ''%¥_¥%'' or '||TableCharColName||' like ''%¤_¤%''';

NA_EUCJP_SQL_stmt_insert := NA_EUCJP_SQL_stmt_insert||' or '||TableCharColName||

' like ''''%¥_¥%'''' or '||TableCharColName||' like ''''%¤_¤%''''';




6th Script TextCurNum_NA_EUCJP_Cols := CurNum_NA_EUCJP_Cols + 1;

dbms_output.put_line('This is NA_EUCJP_Column number '||CurNum_NA_EUCJP_Cols);

dbms_output.put_line('here is CurNum_NA_EUCJP_Cols');

dbms_output.put_line(CurNum_NA_EUCJP_Cols);

dbms_output.put_line('SQL statement appended...');

END IF;

-- insert column info...

--Dummy_col_count := 999;

Sql_stmt := 'insert into Table_NA_EUCJP_Col_Info values ('''||TableName||''', '||TableRowCount||

', '||NAColCount||', '||TableCharColNum||', '''||TableCharColName||''','||Num_NA_EUCJP_Rows||')';


dbms_output.put_line('Column info insert completed...');

End Loop;

NA_EUCJP_SQL_stmt_insert := NA_EUCJP_SQL_stmt_insert||'''';

dbms_output.put_line('here is the NA_EUCJP_SQL_stmt_insert ');

dbms_output.put_line(SUBSTR(''||NA_EUCJP_SQL_stmt_insert||'',1,255));




6th Script TextTabNum_NA_EUCJP_Cols:= CurNum_NA_EUCJP_Cols;

dbms_output.put_line('here is TabNum_NA_EUCJP_Cols');

dbms_output.put_line(TabNum_NA_EUCJP_Cols);

-- update number of NAEUCJP columns...

--Sql_stmt := 'update Table_NA_EUCJP_Col_Info set NUMNAEUCJPCOLS = TabNum_NA_EUCJP_Cols

--where TableName = '''||TableName||'';

--execute immediate Sql_stmt;

--dbms_output.put_line('Number of NAEUCJP columns updated...');

Close C_EucJpTabCols;

Len_NA_EUCJP_SQL_stmt := LENGTH (NA_EUCJP_SQL_stmt);

dbms_output.put_line('Length of NA_EUCJP_SQL stmt '||Len_NA_EUCJP_SQL_stmt);

dbms_output.put_line('here is the NA_EUCJP_SQL_stmt');

dbms_output.put_line(SUBSTR(''||NA_EUCJP_SQL_stmt||'',1,255));

--this has already been done above...

--execute immediate 'select count(*) from '||TableName into TableRowCount;

execute immediate 'select count(*) from

user_tab_columns where table_name = ''' || TableName || '''' into ColCount;




6th Script Text--NA_EUCJP_SQL_stmt := 'testing';

TabNum_NA_EUCJP_Rows := 0;

execute immediate NA_EUCJP_SQL_stmt into TabNum_NA_EUCJP_Rows;

dbms_output.put_line('Number of NA_EUCJP_ rows... '||TabNum_NA_EUCJP_Rows);

--Len_NA_EUCJP_SQL_stmt := 0;

dbms_output.put_line('Num rows in the table '||TableRowCount);

dbms_output.put_line('Num columns in the table '||ColCount);

dbms_output.put_line('Length of NA_EUCJP_SQL stmt '||Len_NA_EUCJP_SQL_stmt);

dbms_output.put_line('Num NAEUCJP_ Rows '||TabNum_NA_EUCJP_Rows);

dbms_output.put_line('Num NAEUCJP_ Columns '||TabNum_NA_EUCJP_Cols);

Sql_stmt := 'insert into Table_NA_EUCJP_Info values ('''||TableName||''', '||TableRowCount||

', '||TabNum_NA_EUCJP_Rows||', '||ColCount||', '||TabNum_NA_EUCJP_Cols||')';


dbms_output.put_line('First insert completed...');

-- If number of EUCJP rows is non-zero, insert select SQL into SQL table

IF TabNum_NA_EUCJP_Rows != 0 THEN

Sql_stmt := 'insert into Table_NA_EUCJP_SQL values ('''||TableName||''', '||Len_NA_EUCJP_SQL_stmt||

', '||NA_EUCJP_SQL_stmt_insert||')';


dbms_output.put_line('Second insert completed...');




6th Script TextEnd If;

execute immediate Sql_stmt2;

End Loop;

Close C_EucJpTabNames;

End;

/

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