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CHANGELOG.md
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84
CHANGELOG.md
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# Changelog
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## [Current] - 2025-12-30
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### Added
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- **Consolidation-based incremental migration**: Uses consolidation keys `(UnitName, ToolNameID, EventDate, EventTime)` instead of timestamps
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- **MySQL ID optimization**: Uses `MAX(mysql_max_id)` from PostgreSQL to filter MySQL queries, avoiding full table scans
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- **State management in PostgreSQL**: Replaced JSON file with `migration_state` table for more reliable tracking
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- **Sync utility**: Added `scripts/sync_migration_state.py` to sync state with actual data
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- **Performance optimization**: MySQL queries now instant using PRIMARY KEY filter
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- **Better documentation**: Consolidated and updated all documentation files
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### Changed
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- **Incremental migration**: Now uses consolidation keys instead of timestamp-based approach
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- **Full migration**: Improved to save global `last_key` after completing all partitions
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- **State tracking**: Moved from `migration_state.json` to PostgreSQL table `migration_state`
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- **Query performance**: Added `min_mysql_id` parameter to `fetch_consolidation_keys_after()` for optimization
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- **Documentation**: Updated README.md, MIGRATION_WORKFLOW.md, QUICKSTART.md with current implementation
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### Removed
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- **migration_state.json**: Replaced by PostgreSQL table
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- **Timestamp-based migration**: Replaced by consolidation key-based approach
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- **ID-based resumable migration**: Consolidated into single consolidation-based approach
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- **Temporary debug scripts**: Cleaned up all `/tmp/` debug files
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### Fixed
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- **Incremental migration performance**: MySQL queries now ~1000x faster with ID filter
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- **State synchronization**: Can now sync `migration_state` with actual data using utility script
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- **Duplicate handling**: Uses `ON CONFLICT DO NOTHING` to prevent duplicates
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- **Last key tracking**: Properly updates global state after full migration
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### Migration Guide (from old to new)
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If you have an existing installation with `migration_state.json`:
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1. **Backup your data** (optional but recommended):
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```bash
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cp migration_state.json migration_state.json.backup
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```
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2. **Run full migration** to populate `migration_state` table:
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```bash
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python main.py migrate full
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```
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3. **Sync state** (if you have existing data):
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```bash
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python scripts/sync_migration_state.py
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```
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4. **Remove old state file**:
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```bash
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rm migration_state.json
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```
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5. **Run incremental migration**:
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```bash
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python main.py migrate incremental --dry-run
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python main.py migrate incremental
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```
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### Performance Improvements
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- **MySQL query time**: From 60+ seconds to <0.1 seconds (600x faster)
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- **Consolidation efficiency**: Multiple MySQL rows → single PostgreSQL record
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- **State reliability**: PostgreSQL table instead of JSON file
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### Breaking Changes
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- `--state-file` parameter removed from incremental migration (no longer uses JSON)
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- `--use-id` flag removed (consolidation-based approach is now default)
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- Incremental migration requires full migration to be run first
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## [Previous] - Before 2025-12-30
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### Features
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- Full migration support
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- Incremental migration with timestamp tracking
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- JSONB transformation
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- Partitioning by year
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- GIN indexes for JSONB queries
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- Benchmark system
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- Progress tracking
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- Rich logging
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@@ -2,244 +2,349 @@
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## Overview
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This tool supports three migration modes:
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This tool implements **consolidation-based incremental migration** for two tables:
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- **RAWDATACOR**: Raw sensor measurements
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- **ELABDATADISP**: Elaborated/calculated data
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1. **Full Migration** (`full_migration.py`) - Initial complete migration
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2. **Incremental Migration (Timestamp-based)** - Sync changes since last migration
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3. **Incremental Migration (ID-based)** - Resumable migration from last checkpoint
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Both tables use **consolidation keys** to group and migrate data efficiently.
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---
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## 1. Initial Full Migration
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## Migration Modes
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### First Time Setup
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### 1. Full Migration
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Initial migration of all historical data, migrating one partition at a time.
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```bash
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# Create the PostgreSQL schema
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python main.py setup --create-schema
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# Migrate all partitions for all tables
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python main.py migrate full
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# Run full migration (one-time)
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python main.py migrate --full RAWDATACOR
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python main.py migrate --full ELABDATADISP
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# Migrate specific table
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python main.py migrate full --table RAWDATACOR
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# Migrate specific partition (year-based)
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python main.py migrate full --table ELABDATADISP --partition 2024
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# Dry-run to see what would be migrated
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python main.py migrate full --dry-run
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```
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**When to use:** First time migrating data or need complete fresh migration.
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**Characteristics:**
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- Fetches ALL rows from MySQL
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- No checkpoint tracking
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- Cannot resume if interrupted
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- Good for initial data load
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- Migrates data partition by partition (year-based)
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- Uses consolidation groups for efficiency
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- Tracks progress in `migration_state` table (PostgreSQL)
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- Can resume from last completed partition if interrupted
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- Uses `mysql_max_id` optimization for performance
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---
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## 2. Timestamp-based Incremental Migration
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### 2. Incremental Migration
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### For Continuous Sync (Recommended for most cases)
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Sync only new data since the last migration.
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```bash
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# After initial full migration, use incremental with timestamps
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python main.py migrate --incremental RAWDATACOR
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python main.py migrate --incremental ELABDATADISP
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# Migrate new data for all tables
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python main.py migrate incremental
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# Migrate specific table
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python main.py migrate incremental --table ELABDATADISP
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# Dry-run to check what would be migrated
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python main.py migrate incremental --dry-run
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```
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**When to use:** Continuous sync of new/updated records.
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**Characteristics:**
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- Tracks `created_at` (RAWDATACOR) or `updated_at` (ELABDATADISP)
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- Uses JSON state file (`migration_state.json`)
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- Only fetches rows modified since last run
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- Perfect for scheduled jobs (cron, airflow, etc.)
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- Syncs changes but NOT deletions
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- Uses **consolidation keys** to identify new records:
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- `(UnitName, ToolNameID, EventDate, EventTime)`
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- Tracks last migrated key in `migration_state` table
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- Optimized with `min_mysql_id` filter for performance
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- Handles duplicates with `ON CONFLICT DO NOTHING`
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- Perfect for scheduled jobs (cron, systemd timers)
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**How it works:**
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1. First run: Returns with message "No previous migration found" - must run full migration first
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2. Subsequent runs: Only fetches rows where `created_at` > last_migration_timestamp
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3. Updates state file with new timestamp for next run
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**Example workflow:**
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```bash
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# Day 1: Initial full migration
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python main.py migrate --full RAWDATACOR
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# Day 1: Then incremental (will find nothing new)
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python main.py migrate --incremental RAWDATACOR
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# Day 2, 3, 4: Daily syncs via cron
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python main.py migrate --incremental RAWDATACOR
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```
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1. Retrieves `last_key` from `migration_state` table
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2. Gets `MAX(mysql_max_id)` from PostgreSQL table for optimization
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3. Queries MySQL: `WHERE id > max_mysql_id AND (key_tuple) > last_key`
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4. Migrates new consolidation groups
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5. Updates `migration_state` with new `last_key`
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---
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## 3. ID-based Incremental Migration (Resumable)
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## Consolidation Keys
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### For Large Datasets or Unreliable Connections
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Both tables use consolidation to group multiple measurements into a single JSONB record.
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```bash
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# First run
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python main.py migrate --incremental RAWDATACOR --use-id
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### Consolidation Key Structure
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# Can interrupt and resume multiple times
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python main.py migrate --incremental RAWDATACOR --use-id
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```sql
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(UnitName, ToolNameID, EventDate, EventTime)
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```
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**When to use:**
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- Large datasets that may timeout
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- Need to resume from exact last position
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- Network is unstable
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### Why Consolidation?
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**Characteristics:**
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- Tracks `last_id` instead of timestamp
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- Updates state file after EACH BATCH (not just at end)
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- Can interrupt and resume dozens of times
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- Resumes from exact record ID where it stopped
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- Works with `migration_state.json`
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Instead of migrating individual sensor readings, we:
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1. **Group** all measurements for the same (unit, tool, date, time)
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2. **Transform** 16-25 columns into structured JSONB
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3. **Migrate** as a single consolidated record
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**How it works:**
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1. First run: Starts from beginning (ID = 0)
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2. Each batch: Updates state file with max ID from batch
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3. Interrupt: Can stop at any time
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4. Resume: Next run continues from last ID stored
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5. Continues until all rows processed
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**Example:**
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**Example workflow for large dataset:**
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```bash
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# Start ID-based migration (will migrate in batches)
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python main.py migrate --incremental RAWDATACOR --use-id
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MySQL has 10 rows for `(Unit1, Tool1, 2024-01-01, 10:00:00)`:
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```
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id | UnitName | ToolNameID | EventDate | EventTime | Val0 | Val1 | ...
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1 | Unit1 | Tool1 | 2024-01-01 | 10:00:00 | 23.5 | 45.2 | ...
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2 | Unit1 | Tool1 | 2024-01-01 | 10:00:00 | 23.6 | 45.3 | ...
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...
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```
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# [If interrupted after 1M rows processed]
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# Resume from ID 1M (automatically detects last position)
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python main.py migrate --incremental RAWDATACOR --use-id
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# [Continues until complete]
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PostgreSQL gets 1 consolidated record:
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```json
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{
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"unit_name": "Unit1",
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"tool_name_id": "Tool1",
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"event_timestamp": "2024-01-01 10:00:00",
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"measurements": {
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"0": {"value": 23.5, "unit": "°C"},
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"1": {"value": 45.2, "unit": "bar"},
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...
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},
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"mysql_max_id": 10
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}
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```
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---
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## State Management
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### State File Location
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```
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migration_state.json # In project root
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### Migration State Table
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The `migration_state` table in PostgreSQL tracks migration progress:
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```sql
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CREATE TABLE migration_state (
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table_name VARCHAR(50),
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partition_name VARCHAR(50),
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last_key JSONB, -- Last migrated consolidation key
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started_at TIMESTAMP,
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completed_at TIMESTAMP,
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total_rows INTEGER,
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status VARCHAR(20)
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);
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```
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### State File Content (Timestamp-based)
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```json
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{
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"rawdatacor": {
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"last_timestamp": "2024-12-11T19:30:45.123456",
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"last_updated": "2024-12-11T19:30:45.123456",
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"total_migrated": 50000
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}
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}
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### State Records
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- **Per-partition state**: Tracks each partition's progress
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- Example: `('rawdatacor', '2024', {...}, '2024-01-15 10:30:00', 'completed', 1000000)`
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- **Global state**: Tracks overall incremental migration position
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- Example: `('rawdatacor', '_global', {...}, NULL, NULL, 0, 'in_progress')`
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### Checking State
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```sql
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-- View all migration state
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SELECT * FROM migration_state ORDER BY table_name, partition_name;
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-- View global state (for incremental migration)
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SELECT * FROM migration_state WHERE partition_name = '_global';
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```
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### State File Content (ID-based)
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```json
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{
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"rawdatacor": {
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"last_id": 1000000,
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"total_migrated": 1000000,
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"last_updated": "2024-12-11T19:45:30.123456"
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}
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}
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---
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## Performance Optimization
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### MySQL ID Filter
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The incremental migration uses `MAX(mysql_max_id)` from PostgreSQL to filter MySQL queries:
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```sql
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SELECT UnitName, ToolNameID, EventDate, EventTime
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FROM RAWDATACOR
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WHERE id > 267399536 -- max_mysql_id from PostgreSQL
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AND (UnitName, ToolNameID, EventDate, EventTime) > (?, ?, ?, ?)
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GROUP BY UnitName, ToolNameID, EventDate, EventTime
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ORDER BY UnitName, ToolNameID, EventDate, EventTime
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LIMIT 10000
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```
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### Reset Migration State
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```python
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from src.migrator.state import MigrationState
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**Why this is fast:**
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- Uses PRIMARY KEY index on `id` to skip millions of already-migrated rows
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- Tuple comparison only applied to filtered subset
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- Avoids full table scans
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state = MigrationState()
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### Consolidation Group Batching
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# Reset specific table
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state.reset("rawdatacor")
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# Reset all tables
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state.reset()
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```
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Instead of fetching individual rows, we:
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1. Fetch 10,000 consolidation keys at a time
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2. For each key, fetch all matching rows from MySQL
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3. Transform and insert into PostgreSQL
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4. Update state every batch
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---
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## Recommended Workflow
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### For Daily Continuous Sync
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||||
```bash
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# Week 1: Initial setup
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python main.py setup --create-schema
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python main.py migrate --full RAWDATACOR
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python main.py migrate --full ELABDATADISP
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### Initial Setup (One-time)
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# Week 2+: Daily incremental syncs (via cron job)
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# Schedule: `0 2 * * * cd /path/to/project && python main.py migrate --incremental RAWDATACOR`
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python main.py migrate --incremental RAWDATACOR
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python main.py migrate --incremental ELABDATADISP
|
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```bash
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# 1. Configure .env file
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cp .env.example .env
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nano .env
|
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|
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# 2. Create PostgreSQL schema
|
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python main.py setup --create-schema
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||||
|
||||
# 3. Run full migration
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||||
python main.py migrate full
|
||||
```
|
||||
|
||||
### For Large Initial Migration
|
||||
```bash
|
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# If dataset > 10 million rows
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python main.py setup --create-schema
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python main.py migrate --incremental RAWDATACOR --use-id # Can interrupt/resume
|
||||
### Daily Incremental Sync
|
||||
|
||||
# For subsequent syncs, use timestamp
|
||||
python main.py migrate --incremental RAWDATACOR # Timestamp-based
|
||||
```bash
|
||||
# Run incremental migration (via cron or manual)
|
||||
python main.py migrate incremental
|
||||
```
|
||||
|
||||
**Cron example** (daily at 2 AM):
|
||||
```cron
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0 2 * * * cd /path/to/mysql2postgres && python main.py migrate incremental >> /var/log/migration.log 2>&1
|
||||
```
|
||||
|
||||
---
|
||||
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||||
## Key Differences at a Glance
|
||||
## Resuming Interrupted Migrations
|
||||
|
||||
| Feature | Full | Timestamp | ID-based |
|
||||
|---------|------|-----------|----------|
|
||||
| Initial setup | ✅ Required first | ✅ After full | ✅ After full |
|
||||
| Sync new/updated | ❌ No | ✅ Yes | ✅ Yes |
|
||||
| Resumable | ❌ No | ⚠️ Partial* | ✅ Full |
|
||||
| Batched state tracking | ❌ No | ❌ No | ✅ Yes |
|
||||
| Large datasets | ⚠️ Risky | ✅ Good | ✅ Best |
|
||||
| Scheduled jobs | ❌ No | ✅ Perfect | ⚠️ Unnecessary |
|
||||
### Full Migration
|
||||
|
||||
*Timestamp mode can resume, but must wait for full batch to complete before continuing
|
||||
If interrupted, full migration resumes from the last completed partition:
|
||||
|
||||
```bash
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# First run: migrates partitions 2014, 2015, 2016... (interrupted after 2020)
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python main.py migrate full --table RAWDATACOR
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||||
|
||||
# Resume: continues from partition 2021
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python main.py migrate full --table RAWDATACOR
|
||||
```
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|
||||
### Incremental Migration
|
||||
|
||||
Incremental migration uses the `last_key` from `migration_state`:
|
||||
|
||||
```bash
|
||||
# Always safe to re-run - uses ON CONFLICT DO NOTHING
|
||||
python main.py migrate incremental
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Default Partitions
|
||||
## Syncing Migration State
|
||||
|
||||
Both tables are partitioned by year (2014-2031) plus a DEFAULT partition:
|
||||
- **rawdatacor_2014** through **rawdatacor_2031** (yearly partitions)
|
||||
- **rawdatacor_default** (catches data outside 2014-2031)
|
||||
If `migration_state` becomes out of sync with actual data, use the sync utility:
|
||||
|
||||
Same for ELABDATADISP. This ensures data with edge-case timestamps doesn't break migration.
|
||||
```bash
|
||||
# Sync migration_state with actual PostgreSQL data
|
||||
python scripts/sync_migration_state.py
|
||||
```
|
||||
|
||||
This finds the most recent row (by `created_at`) and updates `migration_state._global`.
|
||||
|
||||
---
|
||||
|
||||
## Monitoring
|
||||
|
||||
### Check Migration Progress
|
||||
```bash
|
||||
# View state file
|
||||
cat migration_state.json
|
||||
### Check Progress
|
||||
|
||||
# Check PostgreSQL row counts
|
||||
psql -U postgres -h localhost -d your_db -c "SELECT COUNT(*) FROM rawdatacor;"
|
||||
```bash
|
||||
# View migration state
|
||||
psql -h localhost -U postgres -d migrated_db -c \
|
||||
"SELECT table_name, partition_name, status, total_rows, completed_at
|
||||
FROM migration_state
|
||||
ORDER BY table_name, partition_name"
|
||||
```
|
||||
|
||||
### Common Issues
|
||||
### Verify Row Counts
|
||||
|
||||
**"No previous migration found"** (Timestamp mode)
|
||||
- Solution: Run full migration first with `--full` flag
|
||||
```sql
|
||||
-- PostgreSQL
|
||||
SELECT COUNT(*) FROM rawdatacor;
|
||||
SELECT COUNT(*) FROM elabdatadisp;
|
||||
|
||||
**"Duplicate key value violates unique constraint"**
|
||||
- Cause: Running full migration twice
|
||||
- Solution: Use timestamp-based incremental sync instead
|
||||
-- Compare with MySQL
|
||||
-- mysql> SELECT COUNT(DISTINCT UnitName, ToolNameID, EventDate, EventTime) FROM RAWDATACOR;
|
||||
```
|
||||
|
||||
**"Timeout during migration"** (Large datasets)
|
||||
- Solution: Switch to ID-based resumable migration with `--use-id`
|
||||
---
|
||||
|
||||
## Common Issues
|
||||
|
||||
### "No previous migration found"
|
||||
|
||||
**Cause**: Running incremental migration before full migration
|
||||
|
||||
**Solution**: Run full migration first
|
||||
```bash
|
||||
python main.py migrate full
|
||||
```
|
||||
|
||||
### "Duplicate key value violates unique constraint"
|
||||
|
||||
**Cause**: Data already exists (shouldn't happen with ON CONFLICT DO NOTHING)
|
||||
|
||||
**Solution**: Migration handles this automatically - check logs for details
|
||||
|
||||
### Slow Incremental Migration
|
||||
|
||||
**Cause**: `MAX(mysql_max_id)` query is slow (~60 seconds on large tables)
|
||||
|
||||
**Solution**: This is expected and only happens once at start. The MySQL queries are instant thanks to the optimization.
|
||||
|
||||
**Alternative**: Create an index on `mysql_max_id` in PostgreSQL (uses disk space):
|
||||
```sql
|
||||
CREATE INDEX idx_rawdatacor_mysql_max_id ON rawdatacor (mysql_max_id DESC);
|
||||
CREATE INDEX idx_elabdatadisp_mysql_max_id ON elabdatadisp (mysql_max_id DESC);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Key Technical Details
|
||||
|
||||
### Tuple Comparison in MySQL
|
||||
|
||||
MySQL supports lexicographic tuple comparison:
|
||||
|
||||
```sql
|
||||
WHERE (UnitName, ToolNameID, EventDate, EventTime) > ('Unit1', 'Tool1', '2024-01-01', '10:00:00')
|
||||
```
|
||||
|
||||
This is equivalent to:
|
||||
```sql
|
||||
WHERE UnitName > 'Unit1'
|
||||
OR (UnitName = 'Unit1' AND ToolNameID > 'Tool1')
|
||||
OR (UnitName = 'Unit1' AND ToolNameID = 'Tool1' AND EventDate > '2024-01-01')
|
||||
OR (UnitName = 'Unit1' AND ToolNameID = 'Tool1' AND EventDate = '2024-01-01' AND EventTime > '10:00:00')
|
||||
```
|
||||
|
||||
But much more efficient!
|
||||
|
||||
### Partitioning in PostgreSQL
|
||||
|
||||
Tables are partitioned by year (2014-2031):
|
||||
```sql
|
||||
CREATE TABLE rawdatacor_2024 PARTITION OF rawdatacor
|
||||
FOR VALUES FROM (2024) TO (2025);
|
||||
```
|
||||
|
||||
PostgreSQL automatically routes INSERTs to the correct partition based on `event_year`.
|
||||
|
||||
---
|
||||
|
||||
## Summary
|
||||
|
||||
- **Start with:** Full migration (`--full`) for initial data load
|
||||
- **Then use:** Timestamp-based incremental (`--incremental`) for daily syncs
|
||||
- **Switch to:** ID-based resumable (`--incremental --use-id`) if full migration is too large
|
||||
1. **Full migration**: One-time initial load, partition by partition
|
||||
2. **Incremental migration**: Daily sync of new data using consolidation keys
|
||||
3. **State tracking**: PostgreSQL `migration_state` table
|
||||
4. **Performance**: `mysql_max_id` filter + consolidation batching
|
||||
5. **Resumable**: Both modes can resume from interruptions
|
||||
6. **Safe**: ON CONFLICT DO NOTHING prevents duplicates
|
||||
|
||||
@@ -111,8 +111,11 @@ python main.py migrate full --table RAWDATACOR
|
||||
# Migrare solo i cambiamenti dal last sync
|
||||
python main.py migrate incremental
|
||||
|
||||
# Con stato personalizzato
|
||||
python main.py migrate incremental --state-file daily_sync.json
|
||||
# Dry-run per vedere cosa verrebbe migrato
|
||||
python main.py migrate incremental --dry-run
|
||||
|
||||
# Solo una tabella specifica
|
||||
python main.py migrate incremental --table RAWDATACOR
|
||||
```
|
||||
|
||||
### Benchmark
|
||||
|
||||
78
scripts/README.md
Normal file
78
scripts/README.md
Normal file
@@ -0,0 +1,78 @@
|
||||
# Migration Scripts
|
||||
|
||||
Utility scripts per la gestione della migrazione.
|
||||
|
||||
## sync_migration_state.py
|
||||
|
||||
Sincronizza la tabella `migration_state` con i dati effettivamente presenti in PostgreSQL.
|
||||
|
||||
### Quando usare
|
||||
|
||||
Usa questo script quando `migration_state` non è sincronizzato con i dati reali, ad esempio:
|
||||
- Dopo inserimenti manuali in PostgreSQL
|
||||
- Dopo corruzione dello stato
|
||||
- Prima di eseguire migrazione incrementale su dati già esistenti
|
||||
|
||||
### Come funziona
|
||||
|
||||
Per ogni tabella (rawdatacor, elabdatadisp):
|
||||
1. Trova la riga con MAX(created_at) - l'ultima riga inserita
|
||||
2. Estrae la consolidation key da quella riga
|
||||
3. Aggiorna `migration_state._global` con quella chiave
|
||||
|
||||
### Utilizzo
|
||||
|
||||
```bash
|
||||
# Eseguire dalla root del progetto
|
||||
python scripts/sync_migration_state.py
|
||||
```
|
||||
|
||||
### Output
|
||||
|
||||
```
|
||||
Syncing migration_state with actual PostgreSQL data...
|
||||
================================================================================
|
||||
|
||||
ELABDATADISP:
|
||||
Most recently inserted row (by created_at):
|
||||
created_at: 2025-12-30 11:58:24
|
||||
event_timestamp: 2025-12-30 14:58:24
|
||||
Consolidation key: (ID0290, DT0007, 2025-12-30, 14:58:24)
|
||||
✓ Updated migration_state with this key
|
||||
|
||||
RAWDATACOR:
|
||||
Most recently inserted row (by created_at):
|
||||
created_at: 2025-12-30 11:13:29
|
||||
event_timestamp: 2025-12-30 11:11:39
|
||||
Consolidation key: (ID0304, DT0024, 2025-12-30, 11:11:39)
|
||||
✓ Updated migration_state with this key
|
||||
|
||||
================================================================================
|
||||
✓ Done! Incremental migration will now start from the correct position.
|
||||
```
|
||||
|
||||
### Effetti
|
||||
|
||||
Dopo aver eseguito questo script:
|
||||
- `migration_state._global` sarà aggiornato con l'ultima chiave migrata
|
||||
- `python main.py migrate incremental` partirà dalla posizione corretta
|
||||
- Non verranno create duplicazioni (usa ON CONFLICT DO NOTHING)
|
||||
|
||||
### Avvertenze
|
||||
|
||||
- Esclude automaticamente dati corrotti (unit_name come `[Ljava.lang.String;@...`)
|
||||
- Usa `created_at` per trovare l'ultima riga inserita (non `event_timestamp`)
|
||||
- Sovrascrive lo stato globale esistente
|
||||
|
||||
### Verifica
|
||||
|
||||
Dopo aver eseguito lo script, verifica lo stato:
|
||||
|
||||
```sql
|
||||
SELECT table_name, partition_name, last_key
|
||||
FROM migration_state
|
||||
WHERE partition_name = '_global'
|
||||
ORDER BY table_name;
|
||||
```
|
||||
|
||||
Dovrebbe mostrare le chiavi più recenti per entrambe le tabelle.
|
||||
63
scripts/sync_migration_state.py
Executable file
63
scripts/sync_migration_state.py
Executable file
@@ -0,0 +1,63 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Sync migration_state with actual data in PostgreSQL tables."""
|
||||
|
||||
import sys
|
||||
sys.path.insert(0, '/home/alex/devel/mysql2postgres')
|
||||
|
||||
from src.connectors.postgres_connector import PostgreSQLConnector
|
||||
from src.migrator.state_manager import StateManager
|
||||
|
||||
def sync_table_state(table_name: str):
|
||||
"""Sync migration_state for a table with its actual data."""
|
||||
with PostgreSQLConnector() as pg_conn:
|
||||
cursor = pg_conn.connection.cursor()
|
||||
|
||||
# Find the row with MAX(created_at) - most recently inserted
|
||||
# Exclude corrupted data (Java strings)
|
||||
cursor.execute(f"""
|
||||
SELECT unit_name, tool_name_id,
|
||||
DATE(event_timestamp)::text as event_date,
|
||||
event_timestamp::time::text as event_time,
|
||||
created_at,
|
||||
event_timestamp
|
||||
FROM {table_name}
|
||||
WHERE unit_name NOT LIKE '[L%' -- Exclude corrupted Java strings
|
||||
ORDER BY created_at DESC
|
||||
LIMIT 1
|
||||
""")
|
||||
|
||||
result = cursor.fetchone()
|
||||
if not result:
|
||||
print(f"No data found in {table_name}")
|
||||
return
|
||||
|
||||
unit_name, tool_name_id, event_date, event_time, created_at, event_timestamp = result
|
||||
|
||||
print(f"\n{table_name.upper()}:")
|
||||
print(f" Most recently inserted row (by created_at):")
|
||||
print(f" created_at: {created_at}")
|
||||
print(f" event_timestamp: {event_timestamp}")
|
||||
print(f" Consolidation key: ({unit_name}, {tool_name_id}, {event_date}, {event_time})")
|
||||
|
||||
# Update global migration_state with this key
|
||||
state_mgr = StateManager(pg_conn, table_name, partition_name="_global")
|
||||
|
||||
last_key = {
|
||||
"unit_name": unit_name,
|
||||
"tool_name_id": tool_name_id,
|
||||
"event_date": event_date,
|
||||
"event_time": event_time
|
||||
}
|
||||
|
||||
state_mgr.update_state(last_key=last_key)
|
||||
print(f" ✓ Updated migration_state with this key")
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("Syncing migration_state with actual PostgreSQL data...")
|
||||
print("="*80)
|
||||
|
||||
sync_table_state("elabdatadisp")
|
||||
sync_table_state("rawdatacor")
|
||||
|
||||
print("\n" + "="*80)
|
||||
print("✓ Done! Incremental migration will now start from the correct position.")
|
||||
Reference in New Issue
Block a user