Glob Patterns & Multi-File Mode

Several commands support glob patterns for batch processing multiple files.

Supported Commands

Command	Glob Support	Output Behavior
`split`	✅	Creates subdirectory per input file
`analyze`	✅	Aggregates results across all files
`convert`	✅	Requires output directory
`validate`	✅	Validates each file, aggregates results

Basic Patterns

# All SQL files in current directory
sql-splitter analyze "*.sql"

# All SQL files in a directory
sql-splitter validate "dumps/*.sql"

# Recursive (all subdirectories)
sql-splitter analyze "backups/**/*.sql"

# Compressed files
sql-splitter validate "dumps/*.sql.gz"

Important: Quote glob patterns to prevent shell expansion.

Pattern Syntax

Pattern	Matches
`*`	Any characters except `/`
`**`	Any characters including `/` (recursive)
`?`	Any single character
`[abc]`	Any character in brackets
`[a-z]`	Any character in range

Examples

# All .sql files in dumps/
sql-splitter analyze "dumps/*.sql"

# All .sql and .sql.gz files recursively
sql-splitter validate "backups/**/*.sql*"

# Files starting with "prod_"
sql-splitter analyze "prod_*.sql"

# Files from 2024
sql-splitter validate "backup_2024*.sql"

—fail-fast Flag

By default, glob processing continues even if one file fails. Use --fail-fast to stop on first error:

# Stop on first error
sql-splitter validate "*.sql" --fail-fast

# Continue despite errors (default)
sql-splitter validate "*.sql"

Output Behavior

analyze

Outputs aggregate statistics across all files:

sql-splitter analyze "dumps/*.sql" --json

{
  "total_files": 5,
  "succeeded": 5,
  "failed": 0,
  "results": [
    {
      "file": "dumps/users.sql",
      "tables_count": 1,
      "total_inserts": 1000,
      "status": "success"
    },
    {
      "file": "dumps/orders.sql",
      "tables_count": 1,
      "total_inserts": 50000,
      "status": "success"
    }
  ]
}

validate

Reports validation status for each file:

sql-splitter validate "*.sql" --json

{
  "passed": 2,
  "failed": 1,
  "results": [
    {
      "file": "a.sql",
      "passed": true,
      "summary": { "summary": { "errors": 0, "warnings": 0 } }
    },
    {
      "file": "b.sql",
      "passed": true,
      "summary": { "summary": { "errors": 0, "warnings": 1 } }
    },
    {
      "file": "c.sql",
      "passed": false,
      "summary": { "summary": { "errors": 2, "warnings": 0 } }
    }
  ]
}

split

Creates a subdirectory for each input file:

sql-splitter split "dumps/*.sql" -o output/

output/
├── dump1/
│   ├── users.sql
│   └── orders.sql
├── dump2/
│   ├── users.sql
│   └── products.sql

convert

Requires an output directory (not a file):

# Correct: output directory
sql-splitter convert "*.sql" --to postgres -o converted/

# Creates:
# converted/
# ├── file1.sql
# ├── file2.sql

Progress with Globs

The --progress flag shows per-file and overall progress:

sql-splitter validate "backups/**/*.sql.gz" --progress

[1/5] backups/2024/jan.sql.gz ✓
[2/5] backups/2024/feb.sql.gz ✓
[3/5] backups/2024/mar.sql.gz ⚠ 2 warnings
[4/5] backups/2024/apr.sql.gz ✓
[5/5] backups/2024/may.sql.gz ✗ 1 error

Summary: 4 passed, 1 failed

Parallel Processing

For parallel processing of many files, use external tools:

# Process 4 files in parallel
find dumps -name '*.sql.gz' -print0 | \
  xargs -0 -n1 -P4 sql-splitter validate --strict

CI/CD Usage

# GitHub Actions example
- name: Validate all SQL dumps
  run: |
    sql-splitter validate "migrations/*.sql" --strict --json > validation.json
    if jq -e '.failed > 0' validation.json; then
      echo "Validation failed"
      exit 1
    fi