Handling Date-Based Filename Generation in SQLite: CASE, Substr, and Concatenation Issues

Extracting Quarter and Year from MM/DD/YYYY Date Column

Structural Challenges with Date Parsing and String Operations

The core challenge involves transforming date values stored as MM/DD/YYYY strings into quarterly file names formatted as QX-YYYY.csv. This requires precise handling of three distinct operations:

1. Month Extraction: Safely isolating the 2-digit month component from potentially inconsistent date formats
2. Quarter Calculation: Accurately mapping months 01-12 to quarters Q1-Q4
3. Year Extraction and Concatenation: Combining quarter prefixes with 4-digit year suffixes in filename format

Common failure patterns emerge from:

• Hidden date format inconsistencies (e.g., single vs double-digit months)
• SQLite’s type handling in string operations
• Operator precedence in complex expressions
• Identifier quoting with spaces in column names

A complete solution requires addressing all three operations simultaneously while accounting for SQLite’s specific implementation details.

Critical Failure Points in Date Processing and String Concatenation

1. Substring Extraction Precision
MM/DD/YYYY appears straightforward but contains multiple failure vectors:

Single-Digit Month Representation
Dates like ‘9/30/2021′ (instead of ’09/30/2021’) break fixed-position SUBSTR:

substr("accounting period", 1, 2) → '9/' instead of '09'

Variable-Length Month Components
Mixed date formats in same column:

'1/5/2022' (M/DD/YYYY)
'12/31/2022' (MM/DD/YYYY)

Invisible Characters
Leading/trailing spaces or non-printable characters:

' 09/30/2021' (space before month)
'09/30/2021\t' (tab character)

2. Quarter Calculation Methodology
Two primary approaches with different failure modes:

Explicit CASE Enumeration

CASE 
  WHEN month IN ('01','02','03') THEN 'Q1'
  WHEN month IN ('04','05','06') THEN 'Q2' 
  ...
END

Fails when:

• Month extraction returns non-2-digit values
• Input contains null/malformed dates

Mathematical Calculation

((CAST(month AS INTEGER) - 1) / 3) + 1

Fails when:

• Month extraction returns non-numeric strings
• Integer division behaves unexpectedly

3. String Concatenation Mechanics
SQLite’s concatenation operator (||) requires strict operand handling:

Null Propagation
Any null operand makes entire expression null:

'Q' || NULL || '.csv' → NULL

Type Coercion Issues
Implicit casting of numbers to strings:

'Q' || (1 + 2) → 'Q3' (correct)
'Q' || (12/3) → 'Q4' (correct)
'Q' || '12' → 'Q12' (incorrect if expecting quarter)

Comprehensive Validation and Correction Workflow

Step 1: Verify Column Schema and Contents

Confirm actual column name and data format:

-- Check column metadata
PRAGMA table_info(B);

-- Sample raw data with length checks
SELECT 
  "accounting period",
  LENGTH("accounting period") AS len,
  TYPEOF("accounting period") AS type 
FROM B 
LIMIT 10;

Step 2: Develop Robust Month Extraction

Handle variable-length months using INSTR:

-- Find first '/' position
SELECT 
  "accounting period",
  INSTR("accounting period", '/') AS first_slash
FROM B;

-- Extract month with padding
SELECT 
  SUBSTR(
    '0' || SUBSTR(
      "accounting period", 
      1, 
      INSTR("accounting period", '/') - 1
    ),
    -2, 
    2
  ) AS month_padded
FROM B;

Step 3: Implement Quarter Calculation

Combine padded month with mathematical approach:

SELECT 
  'Q' || (
    (CAST(
      SUBSTR(
        '0' || SUBSTR(
          "accounting period", 
          1, 
          INSTR("accounting period", '/') - 1
        ),
        -2, 
        2
      ) AS INTEGER) + 2
    ) / 3
  ) AS quarter
FROM B;

Step 4: Extract 4-Digit Year

Handle year extraction with right-substr:

SELECT
  SUBSTR(
    "accounting period", 
    INSTR("accounting period", '/') + 4, 
    4
  ) AS year_str
FROM B;

Step 5: Full Filename Assembly

Combine components with validation:

SELECT
  'Q' || (
    (CAST(
      SUBSTR(
        '0' || SUBSTR(
          "accounting period", 
          1, 
          INSTR("accounting period", '/') - 1
        ),
        -2, 
        2
      ) AS INTEGER) + 2
    ) / 3
  ) 
  || '-' ||
  SUBSTR(
    "accounting period", 
    INSTR("accounting period", '/') + 4, 
    4
  )
  || '.csv' AS filename
FROM B;

Step 6: Add Error Handling

Implement validation CTE:

WITH validated_dates AS (
  SELECT
    "accounting period",
    CASE WHEN "accounting period" GLOB '[0-9][0-9]/[0-9][0-9]/[0-9][0-9][0-9][0-9]' 
      THEN 1
      ELSE 0 
    END AS is_valid
  FROM B
)
SELECT
  CASE WHEN is_valid = 1 THEN
    'Q' || ((CAST(SUBSTR("accounting period",1,2) AS INTEGER) + 2)/3)
    || '-' || SUBSTR("accounting period",7,4) 
    || '.csv'
  ELSE
    'INVALID_DATE_' || "accounting period"
  END AS filename
FROM validated_dates;

Step 7: Handle Edge Cases

Short Year Formats
Add year validation:

SUBSTR(
  "accounting period", 
  INSTR("accounting period", '/') + 4, 
  4
) BETWEEN '1900' AND '2100'

Month Range Validation
Ensure months 01-12:

BETWEEN '01' AND '12'

Step 8: Performance Optimization

For large datasets, create computed columns:

ALTER TABLE B ADD COLUMN month_str TEXT 
  GENERATED ALWAYS AS (
    SUBSTR(
      '0' || SUBSTR(
        "accounting period", 
        1, 
        INSTR("accounting period", '/') - 1
      ),
      -2, 
      2
    )
  ) VIRTUAL;

CREATE INDEX idx_month ON B(month_str);

Final Production-Grade Query

SELECT 
  'Q' || ((CAST(month_str AS INTEGER) + 2) / 3) 
  || '-' || year_str 
  || '.csv' AS filename
FROM (
  SELECT
    SUBSTR(
      '0' || SUBSTR(
        "accounting period", 
        1, 
        INSTR("accounting period", '/') - 1
      ),
      -2, 
      2
    ) AS month_str,
    SUBSTR(
      "accounting period", 
      INSTR("accounting period", '/') + 4, 
      4
    ) AS year_str
  FROM B
  WHERE "accounting period" GLOB '[0-9][0-9]/[0-9][0-9]/[0-9][0-9][0-9][0-9]'
);

Common Debugging Techniques

1. Component Isolation
   Test each substring operation separately:

SELECT
  "accounting period",
  INSTR("accounting period", '/') AS slash_pos,
  SUBSTR("accounting period",1, slash_pos-1) AS month_part,
  SUBSTR('0' || month_part, -2, 2) AS month_padded
FROM B;

2. Type Checking
   Verify numeric conversions:

SELECT 
  TYPEOF(month_padded),
  CAST(month_padded AS INTEGER) AS month_int
FROM (
  -- month extraction subquery
);

3. Pattern Matching
   Identify non-conforming dates:

SELECT "accounting period"
FROM B
WHERE "accounting period" NOT GLOB '[0-9][0-9]/[0-9][0-9]/[0-9][0-9][0-9][0-9]';

Alternative Approaches

1. SQLite Date Functions
   (Requires date strings in ISO8601 format)

SELECT 
  'Q' || ((CAST(strftime('%m', date_col) AS INTEGER) + 2)/3)
  || '-' || strftime('%Y', date_col)
  || '.csv'
FROM B;

2. User-Defined Functions
   Register custom functions for date handling:

#include <sqlite3ext.h>
SQLITE_EXTENSION_INIT1

static void quarter_func(sqlite3_context *context, int argc, sqlite3_value **argv) {
  const char *date = (const char*)sqlite3_value_text(argv[0]);
  int month = atoi(date);
  int quarter = (month + 2)/3;
  sqlite3_result_text(context, quarter, -1, SQLITE_TRANSIENT);
}

// Register function in extension load

Performance Considerations

1. Expression Indexing
   Create indexes on computed date components:

CREATE INDEX idx_accounting_year 
ON B(SUBSTR("accounting period",7,4));

CREATE INDEX idx_accounting_month 
ON B(SUBSTR("accounting period",1,2));

2. Materialized Views
   For frequent filename generation:

CREATE TABLE filename_cache AS
SELECT 
  rowid,
  -- filename generation expression
FROM B;

CREATE TRIGGER update_filename AFTER UPDATE ON B
BEGIN
  UPDATE filename_cache
  SET filename = -- regeneration logic
  WHERE rowid = NEW.rowid;
END;

Security Considerations

1. SQL Injection Protection
   When using dynamic SQL:

-- UNSAFE
SELECT 'Q3' || '-' || (SELECT user_input FROM params) || '.csv';

-- SAFE: Parameter binding
sqlite3_prepare_v2(db, "SELECT ? || '-' || ? || '.csv'", -1, &stmt, 0);
sqlite3_bind_text(stmt, 1, quarter, -1, SQLITE_STATIC);
sqlite3_bind_text(stmt, 2, year, -1, SQLITE_STATIC);

2. Filename Sanitization
   Prevent directory traversal:

REPLACE(REPLACE(filename, '/', '_'), '\', '_')

Cross-Database Considerations

Conclusion

Robust filename generation from date columns in SQLite requires careful handling of string operations, type conversions, and edge case validation. The presented solutions balance accuracy with performance while accounting for SQLite’s specific behaviors. Production implementations should combine:

• Strict input validation
• Computed columns for frequently-used components
• Comprehensive error logging
• Regular data quality checks

Future enhancements could integrate SQLite’s extension system for custom date handling functions, or migrate to stricter date typing using ISO8601 formats with CHECK constraints.