Saturday, September 19, 2020

HZ_PARTY_V2PUB.UPDATE_ORGANIZATION - API to update Party Organization Details (hz_organization_profiles) in Oracle apps R12

 

 

 

 

 

 

Below API can be used to update the organization details of a party in TCA module.

Base Table: HZ_ORGANIZATION_PROFILES

Test Instance: R12

API: HZ_PARTY_V2PUB.UPDATE_ORGANIZATION

Scope: Public

Test Script:

DECLARE ln_object_version_number NUMBER; lv_init_msg_list VARCHAR2(200) DEFAULT fnd_api.g_true; lr_organization_rec apps.hz_party_v2pub.organization_rec_type; ln_msg_count NUMBER; lv_return_status VARCHAR2(200); lv_msg_data VARCHAR2(200); lv_msg VARCHAR2(200); ln_profile_id NUMBER; ln_party_id NUMBER DEFAULT 123456; BEGIN SELECT MAX(object_version_number) INTO ln_object_version_number FROM hz_parties WHERE party_id = ln_party_id; lr_organization_rec.party_rec.party_id := ln_party_id; lr_organization_rec.year_established := 2020; -- Calling ORGANIZATION update API HZ_PARTY_V2PUB.UPDATE_ORGANIZATION ( p_init_msg_list => lv_init_msg_list, p_organization_rec => lr_organization_rec, p_party_object_version_number => ln_object_version_number, x_profile_id => ln_profile_id, x_return_status => lv_return_status, x_msg_count => ln_msg_count, x_msg_data => lv_msg_data ); IF (lv_return_status <> FND_API.G_RET_STS_SUCCESS) THEN FOR i IN 1 .. FND_MSG_PUB.COUNT_MSG LOOP lv_msg := lv_msg || FND_MSG_PUB.get(p_msg_index => i, p_encoded => FND_API.G_FALSE ) || '; '; END LOOP; DBMS_OUTPUT.PUT_LINE('lv_msg:'||lv_msg); END IF; END;

Saturday, September 19, 2020 by Team search · 0

Saturday, September 12, 2020

How to find similarity between two strings in Oracle (UTL_MATCH) - Levenshtein Distance & Jaro-Winkler algorithm

 

 

 

 

 

 

                In this post, we have given a basic details about an useful Oracle utility named UTL_MATCH. This utility can be used to find the similarity of two strings with two algorithms given below.

Algorithm

Oracle Utilities

Levenshtein Distance

UTL_MATCH.EDIT_DISTANCE(<string1>,<string2>)
UTL_MATCH.EDIT_DISTANCE_SIMILARITY(<string1>,<string2>)

Jaro-Winkler

UTL_MATCH.JARO_WINKLER(<string1>,<string2>)
UTL_MATCH.JARO_WINKLER_SIMILARITY(<string1>,<string2>)

 

Oracle Document Explanation for quick Byte:

Levenshtein Distance:

"Edit Distance" also known as "Levenshtein Distance "(named after the Russian scientist Vladimir Levenshtein, who devised the algorithm in 1965), is a measure of Similarity between two strings, s1 and s2. The distance is the number of insertions, deletions or substitutions required to transform s1 to s2

Jaro-Winkler algorithm:

The "Jaro-Winkler algorithm" is another way of calculating Edit distance between two strings. This method, developed at the U.S. Census, is a String Comparator measure that gives values of partial agreement between two strings. The string comparator accounts for length of strings and partially accounts for typical human errors made in alphanumeric strings.

Lets do some practical:

Just to understand the functionality of the functions, I tried executing the comparison for below strings.

Scenario

STRING 1

STRING 2

One letter not found in String 2 comparing to String 1

TEST

TAST

Two letter not found in String 2 comparing to String 1

TEST

TT

Matching Strings

TEST

TEST

No characters from first string found in second string

TEST

ABCDFG

 Results: 









 

 

 

 

 

 

Oracle Reference:

https://docs.oracle.com/cd/E18283_01/appdev.112/e16760/u_match.htm

Saturday, September 12, 2020 by Team search · 0

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