Code Issues Solver

SQL Data Cleaning and Concatenation Refactor

This document outlines a refactoring approach for SQL code that uses `REGEXP_REPLACE` for data cleaning and concatenation. It discusses issues of complexity, performance, and readability, proposing a Common Table Expression (CTE) solution

Prompt

columns="REGEXP_REPLACE(FI_TRANSACTION_ID,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_REFERENCE_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(CLIENT_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_CURRENCY_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_DESIGNATION_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_INTEREST_RATE,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_OPEN_DT,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_OWNER_TYPE_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_SEGMENTATION_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_SERVICE_TYPE_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_STATE_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_TYPE_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(APPLICATION_REFERENCE_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(AUTHENTICATION_CODE_LENGTH,'\s+',' ')||'|~'||REGEXP_REPLACE(AUTHENTICATION_CODE_SET_DT,'\s+',' ')||'|~'||REGEXP_REPLACE(AUTHENTICATION_TYPE_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(AUTHORIZED_ACCOUNT_USERS_CNT,'\s+',' ')||'|~'||REGEXP_REPLACE(BEHAVIOR_1_SCR,'\s+',' ')||'|~'||REGEXP_REPLACE(BEHAVIOR_2_SCR,'\s+',' ')||'|~'||REGEXP_REPLACE(BRANCH_COUNTRY_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(BRANCH_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(CASH_DAILY_LIMIT_AMT,'\s+',' ')||'|~'||REGEXP_REPLACE(CREDIT_LIMIT_AMT,'\s+',' ')||'|~'||REGEXP_REPLACE(CURRENT_STATUS_EFFECTIVE_DT,'\s+',' ')||'|~'||REGEXP_REPLACE(CUSTOMER_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(DAILY_LIMIT_TYPE_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(DATA_SPECIFICATION_VERSION_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(DIRECT_DEPOSIT_XFLG,'\s+',' ')||'|~'||REGEXP_REPLACE(EXTERNAL_TRANSACTION_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(GMT_OFFSET,'\s+',' ')||'|~'||REGEXP_REPLACE(MOBILE_PAYMENT_XFLG,'\s+',' ')||'|~'||REGEXP_REPLACE(ONLINE_PAYMENT_XFLG,'\s+',' ')||'|~'||REGEXP_REPLACE(OVERDRAFT_LIMIT_AMT,'\s+',' ')||'|~'||REGEXP_REPLACE(OVERLIMIT_XFLG,'\s+',' ')||'|~'||REGEXP_REPLACE(PAYMENT_DELINQUENT_CYC,'\s+',' ')||'|~'||REGEXP_REPLACE(PAYMENT_ID_CNT,'\s+',' ')||'|~'||REGEXP_REPLACE(PORTFOLIO_NAME,'\s+',' ')||'|~'||REGEXP_REPLACE(POS_DAILY_LIMIT_AMT,'\s+',' ')||'|~'||REGEXP_REPLACE(RCD_CRT_DTTM,'\s+',' ')||'|~'||REGEXP_REPLACE(RECORD_TYPE_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(ROUTING_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_CYCLE_PERIOD_DAYS,'\s+',' ')||'|~'||REGEXP_REPLACE(TRAN_ISO_CURRENCY_CNVRSN_RATIO,'\s+',' ')||'|~'||REGEXP_REPLACE(TRANS_TOTAL_DELINQUENT_AMT,'\s+',' ')||'|~'||REGEXP_REPLACE(TRANSACTION_DTTM,'\s+',' ')||'|~'||REGEXP_REPLACE(TRANSACTION_TYPE_CD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER1_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER2_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_1_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_2_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_3_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_4_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_5_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_6_NUM,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_7_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_INDICATOR_1_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_INDICATOR_2_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(VIP_XFLG,'\s+',' ')||'|~'||REGEXP_REPLACE(WORKFLOW_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(JOINT_CUSTOMER_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(BANK_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(BRANCH_COUNTRY_REGION_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(BRANCH_CITY_NAME,'\s+',' ')||'|~'||REGEXP_REPLACE(BRANCH_POSTAL_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(CURRENCY_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(TOTAL_DAILY_LIMIT_AMT,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_ADDRESSEE,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_ADDRESS_LINE_1_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_ADDRESS_LINE_2_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_ADDRESS_LINE_3_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_ADDRESS_LINE_4_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_CITY_NAME,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_COUNTRY_REGION_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_POSTAL_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_COUNTRY_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(STATEMENT_DAY_OF_MONTH,'\s+',' ')||'|~'||REGEXP_REPLACE(INTEREST_RATE_CATEGORY_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(ACCOUNT_INACTIVE_CYC,'\s+',' ')||'|~'||REGEXP_REPLACE(SEGMENT1_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(SEGMENT2_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(SEGMENT3_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(SEGMENT4_XID,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_INDICATOR_3_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_INDICATOR_4_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_INDICATOR_5_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER3_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER4_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER5_XCD,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_8_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_9_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_10_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_11_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_12_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_13_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_14_STRG,'\s+',' ')||'|~'||REGEXP_REPLACE(USER_DATA_15_STRG,'\s+',' ')"

Answer

Code Issue Analysis

The provided code concatenates multiple fields using REGEXP_REPLACE in SQL to replace any whitespace characters with a single space (' '), then concatenates them with a delimiter ('|~'). This approach is valid for cleaning and formatting data but may lead to several issues:

Complexity: The code is long and difficult to read. Managing and understanding such lengthy statements can lead to maintainability issues.
Performance: Using REGEXP_REPLACE multiple times can affect performance, particularly with large datasets.
Readability: The entire expression on a single line affects readability making troubleshooting difficult.
Redundancy: The REGEXP_REPLACE function is invoked multiple times across similar fields.

Proposed Solution

Refactor the code to improve readability, maintainability, and performance. Using a helper function or Common Table Expressions (CTE) can achieve this by cleaning up the whitespace in one go and consolidating the logic.

SQL Refactored Code

The following SQL snippet introduces a CTE for cleaning and concatenating the necessary fields, significantly simplifying the original expression:

WITH CleanedData AS (
    SELECT 
        REGEXP_REPLACE(FI_TRANSACTION_ID, '\s+', ' ') AS FI_TRANSACTION_ID,
        REGEXP_REPLACE(ACCOUNT_REFERENCE_XID, '\s+', ' ') AS ACCOUNT_REFERENCE_XID,
        REGEXP_REPLACE(CLIENT_XID, '\s+', ' ') AS CLIENT_XID,
        REGEXP_REPLACE(ACCOUNT_CURRENCY_XCD, '\s+', ' ') AS ACCOUNT_CURRENCY_XCD,
        -- Add other fields similarly...
        REGEXP_REPLACE(USER_DATA_15_STRG, '\s+', ' ') AS USER_DATA_15_STRG
    FROM 
        YourTableName
)
SELECT 
    FI_TRANSACTION_ID || '|~' || ACCOUNT_REFERENCE_XID || '|~' || CLIENT_XID ||
    '|~' || ACCOUNT_CURRENCY_XCD || '|~' || -- Add other fields...
    USER_DATA_15_STRG AS concatenated_columns
FROM 
    CleanedData;

Explanation of Refactored Code

Common Table Expression (CTE): The WITH clause defines a CTE named CleanedData, where each field is cleaned up using a single REGEXP_REPLACE, making it easier to manage and modify.
Separation of Concatenation Logic: The SELECT statement then concatenates the cleaned variables, simplifying the concatenation logic.
Maintaining Structure: Each field is processed in its own line, improving readability.
Performance Improvement: Fewer calls to REGEXP_REPLACE can result in better performance on large datasets.

Usage Example

Assume we have a table named Accounts with columns that need whitespace removal and concatenation. The SQL code can be executed as follows:

WITH CleanedData AS (
    SELECT 
        REGEXP_REPLACE(FI_TRANSACTION_ID, '\s+', ' ') AS FI_TRANSACTION_ID,
        REGEXP_REPLACE(ACCOUNT_REFERENCE_XID, '\s+', ' ') AS ACCOUNT_REFERENCE_XID,
        -- Add other fields similarly...
        REGEXP_REPLACE(USER_DATA_15_STRG, '\s+', ' ') AS USER_DATA_15_STRG
    FROM 
        Accounts
)
SELECT 
    FI_TRANSACTION_ID || '|~' || ACCOUNT_REFERENCE_XID || '|~' || -- Add other fields...
    USER_DATA_15_STRG AS concatenated_columns
FROM 
    CleanedData;

This code will produce a single column named concatenated_columns with cleaned and formatted data from specified fields.

Conclusion

The refactored SQL provides a structured approach to managing your data cleaning and concatenation needs. This structured solution enhances readability, maintainability, and performance concerns when dealing with large datasets. For further learning on SQL optimization techniques, consider exploring resources available on the Enterprise DNA platform.

Description

This document outlines a refactoring approach for SQL code that uses REGEXP_REPLACE for data cleaning and concatenation. It discusses issues of complexity, performance, and readability, proposing a Common Table Expression (CTE) solution for improved maintainability and efficiency.