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Regular Expression Support in Oracle (REGEXP_COUNT, REGEXP_INSTR, REGEXP_REPLACE, REGEXP_SUBSTR, REGEXP_LIKE)

Related articles.

Introduction

Oracle 10g introduced support support for regular expressions in SQL and PL/SQL with the following functions.

Oracle 11g introduced two new features related to regular expressions.

Learning to write regular expressions takes a little time. If you don't do it regularly, it can be a voyage of discovery each time. The general rules for writing regular expressions are available here. You can read the Oracle Regular Expression Support here.

Rather than trying to repeat the formal definitions, I'll present a number of problems I've been asked to look at over the years, where a solution using a regular expression has been appropriate.

Example 1 : REGEXP_SUBSTR

The data in a column is free text, but may include a 4 digit year.

DROP TABLE t1;
CREATE TABLE t1 (
  data VARCHAR2(50)
);

INSERT INTO t1 VALUES ('FALL 2014');
INSERT INTO t1 VALUES ('2014 CODE-B');
INSERT INTO t1 VALUES ('CODE-A 2014 CODE-D');
INSERT INTO t1 VALUES ('ADSHLHSALK');
INSERT INTO t1 VALUES ('FALL 2004');
COMMIT;

SELECT * FROM t1;

DATA
----------------------------------------------------------------------------------------------------
FALL 2014
2014 CODE-B
CODE-A 2014 CODE-D
ADSHLHSALK
FALL 2004

5 rows selected.

SQL>

If we needed to return rows containing a specific year we could use the LIKE operator (WHERE data LIKE '%2014%'), but how do we return rows using a comparison (<, <=, >, >=, <>)?

One way to approach this is to pull out the 4 figure year and convert it to a number, so we don't accidentally do an ASCII comparison. That's pretty easy using regular expressions.

We can identify digits using the "\d" or "[0-9]" operators. We want a group of four of them, which is represented by the "{4}" operator. So our regular expression will be "\d{4}" or "[0-9]{4}". The REGEXP_SUBSTR function returns the string matching the regular expression, so that can be used to extract the text of interest. We then just need to convert it to a number and perform our comparison.

SELECT *
FROM   t1
WHERE  TO_NUMBER(REGEXP_SUBSTR(data, '\d{4}')) >= 2014;

DATA
----------------------------------------------------------------------------------------------------
FALL 2014
2014 CODE-B
CODE-A 2014 CODE-D

3 rows selected.

SQL>

Example 2 : REGEXP_SUBSTR

Given a source string, how do we split it up into separate columns, based on changes of case and alpha-to-numeric, such that this.

ArtADB1234567e9876540 

Becomes this.

Art ADB 1234567 e 9876540

The source data is set up like this.

DROP TABLE t1;
CREATE TABLE t1 (
  data VARCHAR2(50)
);

INSERT INTO t1 VALUES ('ArtADB1234567e9876540');
COMMIT;

The first part of the string is an initcap word, so it starts with a capital letter between "A" and "Z". We identify a single character using the "[]" operator, and ranges are represented using "-", like "A-Z", "a-z" or "0-9". So if we are looking for a single character that is a capital letter, we need to look for "[A-Z]". That needs to be followed by lower case letters, which we now know is "[a-z]", but we need 1 or more of them, which is signified by the "+" operator. So to find an initcap word, we need to search for "[A-Z][a-z]+". Since we want the first occurrence of this, we can use the following.

REGEXP_SUBSTR(data, '[A-Z][a-z]+', 1, 1)

The second part of the string is a group of 1 or more uppercase letters. We know we need to use the "[A-Z]+" pattern, but we need to make sure we don't get the first capital letter, so we look for the second occurrence.

REGEXP_SUBSTR(data, '[A-Z]+', 1, 2)

The next part is the first occurrence of a group of numbers.

REGEXP_SUBSTR(data, '[0-9]+', 1, 1)

The next part is a group of lower case letters. We don't to pick up those from the initcap word, so we must look for the second occurrence of lower case letters.

REGEXP_SUBSTR(data, '[a-z]+', 1, 2)

Finally, we have a group of numbers, which is the second occurrence of this pattern.

REGEXP_SUBSTR(data, '[0-9]+', 1, 2)

Putting that all together, we have the following query, which splits the data into separate columns.

COLUMN col1 FORMAT A15
COLUMN col2 FORMAT A15
COLUMN col3 FORMAT A15
COLUMN col4 FORMAT A15
COLUMN col5 FORMAT A15

SELECT REGEXP_SUBSTR(data, '[A-Z][a-z]+', 1, 1) col1,
       REGEXP_SUBSTR(data, '[A-Z]+', 1, 2) col2,
       REGEXP_SUBSTR(data, '[0-9]+', 1, 1) col3,
       REGEXP_SUBSTR(data, '[a-z]+', 1, 2) col4,
       REGEXP_SUBSTR(data, '[0-9]+', 1, 2) col5
FROM   t1;

COL1            COL2            COL3            COL4            COL5
--------------- --------------- --------------- --------------- ---------------
Art             ADB             1234567         e               9876540

1 row selected.

SQL>

Example 3 : REGEXP_SUBSTR

We need to pull out a group of characters from a "/" delimited string, optionally enclosed by double quotes. The data looks like this.

DROP TABLE t1;
CREATE TABLE t1 (
  data VARCHAR2(50)
);

INSERT INTO t1 VALUES ('978/955086/GZ120804/10-FEB-12');
INSERT INTO t1 VALUES ('97/95508/BANANA/10-FEB-12');
INSERT INTO t1 VALUES ('97/95508/"APPLE"/10-FEB-12');
COMMIT;

We are looking for 1 or more characters that are not "/", which we do using "[^/]+". The "^" in the brackets represents NOT and "+" means 1 or more. We also want to remove optional double quotes, so we add that as a character we don't want, giving us "[^/"]+". So if we want the data from the third column, we need the third occurrence of this pattern.

SELECT REGEXP_SUBSTR(data, '[^/"]+', 1, 3) AS element3
FROM   t1;

ELEMENT3
----------------------------------------------------------------------------------------------------
GZ120804
BANANA
APPLE

3 rows selected.

SQL>

Example 4 : REGEXP_REPLACE

We need to take an initcap string and separate the words. The data looks like this.

DROP TABLE t1;
CREATE TABLE t1 (
  data VARCHAR2(50)
);

INSERT INTO t1 VALUES ('SocialSecurityNumber');
INSERT INTO t1 VALUES ('HouseNumber');
COMMIT;

We need to find each uppercase character "[A-Z]". We want to keep that character we find, so we will make that pattern a sub-expression "([A-Z])", allowing us to refer to it later. For each match, we want to replace it with a space, plus the matching character. The space is pretty obvious, but we need to use "\1" to signify the text matching the first sub expression. So we will replace the matching pattern with a space and itself, " \1". We don't want to replace the first letter of the string, so we will start at the second occurrence.

SELECT REGEXP_REPLACE(data, '([A-Z])', ' \1', 2) AS hyphen_text
FROM   t1;
  
HYPHEN_TEXT
----------------------------------------------------------------------------------------------------
Social Security Number
House Number

2 rows selected.

SQL>

Example 5 : REGEXP_INSTR

We have a specific pattern of digits (9 99:99:99) and we want to know the location of the pattern in our data.

DROP TABLE t1;
CREATE TABLE t1 (
  data VARCHAR2(50)
);

INSERT INTO t1 VALUES ('1 01:01:01');
INSERT INTO t1 VALUES ('.2 02:02:02');
INSERT INTO t1 VALUES ('..3 03:03:03');
COMMIT;

We know we are looking for groups of numbers, so we can use "[0-9]" or "\d". We know the amount of digits in each group, which we can indicate using the "{n}" operator, so we simply describe the pattern we are looking for.

SELECT REGEXP_INSTR(data, '[0-9] [0-9]{2}:[0-9]{2}:[0-9]{2}') AS string_loc_1,
       REGEXP_INSTR(data, '\d \d{2}:\d{2}:\d{2}') AS string_loc_2
FROM   t1;

STRING_LOC_1 STRING_LOC_2
------------ ------------
           1            1
           2            2
           3            3

3 rows selected.

SQL>

Example 6 : REGEXP_LIKE and REGEXP_SUBSTR

We have strings containing parentheses. We want to return the text within the parentheses for those rows that contain parentheses.

DROP TABLE t1;
CREATE TABLE t1 (
  data VARCHAR2(50)
);

INSERT INTO t1 VALUES ('This is some text (with parentheses) in it.');
INSERT INTO t1 VALUES ('This text has no parentheses.');
INSERT INTO t1 VALUES ('This text has (parentheses too).');
COMMIT;

The basic pattern for text between parentheses is "\(.*\)". The "\" characters are escapes for the parentheses, making them literals. Without the escapes they would be assumed to define a sub-expression. That pattern alone is fine to identify the rows of interest using a REGEXP_LIKE operator, but it is not appropriate in a REGEXP_SUBSTR, as it would return the parentheses also. To omit the parentheses we need to include a sub-expression inside the literal parentheses "\((.*)\)". We can then REGEXP_SUBSTR using the first sub expression.

COLUMN with_parentheses FORMAT A20
COLUMN without_parentheses FORMAT A20

SELECT data,
       REGEXP_SUBSTR(data, '\(.*\)') AS with_parentheses,
       REGEXP_SUBSTR(data, '\((.*)\)', 1, 1, 'i', 1) AS without_parentheses
FROM   t1
WHERE  REGEXP_LIKE(data, '\(.*\)');

DATA                                               WITH_PARENTHESES     WITHOUT_PARENTHESES
-------------------------------------------------- -------------------- --------------------
This is some text (with parentheses) in it.        (with parentheses)   with parentheses
This text has (parentheses too).                   (parentheses too)    parentheses too

2 rows selected.

SQL>

Example 7 : REGEXP_COUNT

We need to know how many times a block of 4 digits appears in text. The data looks like this.

DROP TABLE t1;
CREATE TABLE t1 (
  data VARCHAR2(50)
);

INSERT INTO t1 VALUES ('1234');
INSERT INTO t1 VALUES ('1234 1234');
INSERT INTO t1 VALUES ('1234 1234 1234');
COMMIT;

We can identify digits using "\d" or "[0-9]" and the "{4}" operator signifies 4 of them, so using "\d{4}" or "[0-9]{4}" with the REGEXP_COUNT function seems to be a valid option.

SELECT REGEXP_COUNT(data, '[0-9]{4}') AS pattern_count_1,
       REGEXP_COUNT(data, '\d{4}') AS pattern_count_2
FROM   t1;

PATTERN_COUNT_1 PATTERN_COUNT_2
--------------- ---------------
              1               1
              2               2
              3               3

3 rows selected.

SQL>

Example 8 : REGEXP_LIKE

We need to identify invalid email addresses. The data looks like this.

DROP TABLE t1;
CREATE TABLE t1 (
  data VARCHAR2(50)
);

INSERT INTO t1 VALUES ('me@example.com');
INSERT INTO t1 VALUES ('me@example');
INSERT INTO t1 VALUES ('@example.com');
INSERT INTO t1 VALUES ('me.me@example.com');
INSERT INTO t1 VALUES ('me.me@ example.com');
INSERT INTO t1 VALUES ('me.me@example-example.com');
COMMIT;

The following test gives us email addresses that approximate to invalid email address formats.

SELECT data
FROM   t1
WHERE  NOT REGEXP_LIKE(data, '[A-Z0-9._%+-]+@[A-Z0-9.-]+\.[A-Z]{2,4}', 'i');

DATA
--------------------------------------------------
me@example
@example.com
me.me@ example.com

3 rows selected.

SQL>

For more information see:

Hope this helps. Regards Tim...

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