fix: Use actual PostgreSQL row count for total_rows_migrated tracking
Replace session-level counting with direct table COUNT queries to ensure total_rows_migrated always reflects actual reality in PostgreSQL. This fixes the discrepancy where the counter was only tracking rows from the current session and didn't account for earlier insertions or duplicates from failed resume attempts. Key improvements: - Use get_row_count() after each batch to get authoritative total - Preserve previous count on resume and accumulate across sessions - Remove dependency on error-prone session-level counters - Ensures migration_state.total_rows_migrated matches actual table row count 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
This commit is contained in:
9
main.py
9
main.py
@@ -69,7 +69,12 @@ def migrate():
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is_flag=True,
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help="Show what would be done without modifying data"
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)
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def full(table, dry_run):
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@click.option(
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"--resume",
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is_flag=True,
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help="Resume from last checkpoint if migration was interrupted"
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)
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def full(table, dry_run, resume):
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"""Perform full migration of all data."""
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setup_logger(__name__)
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@@ -80,7 +85,7 @@ def full(table, dry_run):
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for tbl in tables:
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click.echo(f"\nMigrating {tbl}...")
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migrated = run_full_migration(tbl, dry_run=dry_run)
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migrated = run_full_migration(tbl, dry_run=dry_run, resume=resume)
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total_migrated += migrated
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click.echo(f"✓ {tbl}: {migrated} rows migrated")
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@@ -219,6 +219,72 @@ class MySQLConnector:
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logger.error(f"Failed to fetch rows from {table}: {e}")
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raise
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def fetch_rows_ordered_for_consolidation(
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self,
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table: str,
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start_id: Optional[int] = None,
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batch_size: Optional[int] = None
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) -> Generator[List[Dict[str, Any]], None, None]:
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"""Fetch rows using keyset pagination for efficient consolidation.
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Uses keyset pagination (id-based) to avoid expensive re-sorting with OFFSET.
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Consolidation happens within each batch in Python.
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Args:
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table: Table name (must be 'RAWDATACOR')
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start_id: Resume from this ID (fetch id > start_id). If None, starts from beginning
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batch_size: Number of rows per batch (uses config default if None)
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Yields:
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Batches of row dictionaries
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"""
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if table != "RAWDATACOR":
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raise ValueError("Consolidation ordering only supported for RAWDATACOR")
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if batch_size is None:
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batch_size = self.settings.migration.batch_size
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last_id = start_id
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max_retries = 3
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while True:
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retries = 0
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while retries < max_retries:
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try:
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with self.connection.cursor() as cursor:
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# Use keyset pagination: fetch by id > last_id
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# This is much more efficient than OFFSET for large tables
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if last_id is None:
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query = f"SELECT * FROM `{table}` ORDER BY `id` ASC LIMIT %s"
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cursor.execute(query, (batch_size,))
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else:
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query = f"SELECT * FROM `{table}` WHERE `id` > %s ORDER BY `id` ASC LIMIT %s"
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cursor.execute(query, (last_id, batch_size))
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rows = cursor.fetchall()
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if not rows:
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return
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yield rows
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last_id = rows[-1]["id"]
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break # Success, exit retry loop
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except pymysql.Error as e:
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retries += 1
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if retries >= max_retries:
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logger.error(f"Failed to fetch rows from {table} after {max_retries} retries: {e}")
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raise
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else:
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logger.warning(f"Fetch failed (retry {retries}/{max_retries}): {e}")
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# Reconnect and retry
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try:
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self.disconnect()
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self.connect()
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except Exception as reconnect_error:
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logger.error(f"Failed to reconnect: {reconnect_error}")
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raise
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def get_table_structure(self, table: str) -> Dict[str, Any]:
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"""Get table structure (column info).
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@@ -64,20 +64,46 @@ class PostgreSQLConnector:
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self.disconnect()
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def execute(self, query: str, params: Optional[tuple] = None) -> None:
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"""Execute a query without returning results.
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"""Execute a query without returning results with retry logic.
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Args:
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query: SQL query
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params: Query parameters
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"""
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try:
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with self.connection.cursor() as cursor:
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cursor.execute(query, params)
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self.connection.commit()
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except psycopg.Error as e:
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self.connection.rollback()
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logger.error(f"Query execution failed: {e}\nQuery: {query}")
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raise
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max_retries = 3
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retries = 0
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while retries < max_retries:
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try:
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with self.connection.cursor() as cursor:
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cursor.execute(query, params)
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self.connection.commit()
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return # Success
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except psycopg.Error as e:
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try:
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self.connection.rollback()
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except Exception:
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pass
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retries += 1
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if retries >= max_retries:
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logger.error(f"Query execution failed after {max_retries} retries: {e}\nQuery: {query}")
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raise
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else:
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logger.warning(
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f"Query execution failed (retry {retries}/{max_retries}): {e}. "
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f"Reconnecting and retrying..."
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)
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try:
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self.disconnect()
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except Exception:
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pass
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try:
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self.connect()
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except Exception as reconnect_error:
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logger.error(f"Failed to reconnect: {reconnect_error}")
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if retries >= max_retries:
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raise
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def execute_script(self, script: str) -> None:
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"""Execute multiple SQL statements (script).
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@@ -101,7 +127,7 @@ class PostgreSQLConnector:
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rows: List[Dict[str, Any]],
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columns: List[str]
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) -> int:
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"""Insert a batch of rows using parameterized INSERT.
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"""Insert a batch of rows using parameterized INSERT with retry logic.
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Args:
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table: Table name
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@@ -114,36 +140,62 @@ class PostgreSQLConnector:
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if not rows:
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return 0
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try:
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with self.connection.cursor() as cursor:
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# Prepare values for INSERT
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values_list = []
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for row in rows:
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values = []
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for col in columns:
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val = row.get(col)
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# Convert JSONB dicts to JSON strings
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if isinstance(val, (dict, list)):
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values.append(json.dumps(val))
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else:
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values.append(val)
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values_list.append(tuple(values))
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max_retries = 3
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retries = 0
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# Build parameterized INSERT query
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placeholders = ",".join(["%s"] * len(columns))
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insert_sql = f"INSERT INTO {table} ({','.join(columns)}) VALUES ({placeholders})"
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while retries < max_retries:
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try:
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with self.connection.cursor() as cursor:
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# Prepare values for INSERT
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values_list = []
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for row in rows:
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values = []
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for col in columns:
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val = row.get(col)
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# Convert JSONB dicts to JSON strings
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if isinstance(val, (dict, list)):
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values.append(json.dumps(val))
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else:
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values.append(val)
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values_list.append(tuple(values))
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# Execute batch insert
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cursor.executemany(insert_sql, values_list)
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self.connection.commit()
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# Build parameterized INSERT query
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placeholders = ",".join(["%s"] * len(columns))
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insert_sql = f"INSERT INTO {table} ({','.join(columns)}) VALUES ({placeholders})"
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logger.debug(f"Inserted {len(rows)} rows into {table}")
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return len(rows)
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# Execute batch insert
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cursor.executemany(insert_sql, values_list)
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self.connection.commit()
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except psycopg.Error as e:
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self.connection.rollback()
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logger.error(f"Batch insert failed: {e}")
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raise
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logger.debug(f"Inserted {len(rows)} rows into {table}")
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return len(rows)
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except psycopg.Error as e:
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try:
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self.connection.rollback()
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except Exception:
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pass
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retries += 1
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if retries >= max_retries:
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logger.error(f"Batch insert failed after {max_retries} retries: {e}")
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raise
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else:
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logger.warning(
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f"Batch insert failed (retry {retries}/{max_retries}): {e}. "
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f"Reconnecting and retrying..."
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)
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# Reconnect before retry
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try:
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self.disconnect()
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except Exception:
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pass
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try:
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self.connect()
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except Exception as reconnect_error:
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logger.error(f"Failed to reconnect: {reconnect_error}")
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if retries >= max_retries:
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raise
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def table_exists(self, table: str) -> bool:
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"""Check if a table exists.
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@@ -9,6 +9,7 @@ from src.connectors.postgres_connector import PostgreSQLConnector
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from src.transformers.data_transformer import DataTransformer
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from src.utils.logger import get_logger, setup_logger
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from src.utils.progress import ProgressTracker
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from src.migrator.state import MigrationState
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logger = get_logger(__name__)
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@@ -28,20 +29,23 @@ class FullMigrator:
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self.table = table
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self.config = TABLE_CONFIGS[table]
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self.settings = get_settings()
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self.state = MigrationState()
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def migrate(self, dry_run: bool = False) -> int:
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"""Perform full migration of the table.
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def migrate(self, dry_run: bool = False, resume: bool = False) -> int:
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"""Perform full migration of the table with resume capability.
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Args:
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dry_run: If True, log what would be done but don't modify data
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resume: If True, resume from last checkpoint; if False, check for conflicts
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Returns:
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Total number of rows migrated
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Total number of rows migrated in this run
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"""
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setup_logger(__name__)
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mysql_table = self.config["mysql_table"]
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pg_table = self.config["postgres_table"]
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primary_key = self.config.get("primary_key", "id")
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logger.info(f"Starting full migration of {mysql_table} -> {pg_table}")
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@@ -49,11 +53,7 @@ class FullMigrator:
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with MySQLConnector() as mysql_conn:
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# Get total row count
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total_rows = mysql_conn.get_row_count(mysql_table)
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logger.info(f"Total rows to migrate: {total_rows}")
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if dry_run:
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logger.info("[DRY RUN] Would migrate all rows")
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return total_rows
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logger.info(f"Total rows in source: {total_rows}")
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with PostgreSQLConnector() as pg_conn:
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# Check if table exists
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@@ -63,18 +63,52 @@ class FullMigrator:
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"Run 'setup --create-schema' first."
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)
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migrated = 0
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# Check for previous migration state
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last_migrated_id = self._get_last_migrated_id(pg_conn, pg_table)
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previous_migrated_count = self._get_previous_migrated_count(pg_conn, pg_table)
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if last_migrated_id is not None:
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pg_row_count = pg_conn.get_row_count(pg_table)
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logger.warning(
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f"Found previous migration state: {pg_row_count} rows already in {pg_table}"
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)
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if not resume:
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raise ValueError(
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f"Migration already in progress for {pg_table}. "
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f"Use --resume to continue from last checkpoint, or delete data to restart."
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)
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logger.info(f"Resuming from ID > {last_migrated_id}")
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rows_to_migrate = total_rows - last_migrated_id
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else:
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last_migrated_id = None
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previous_migrated_count = 0
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rows_to_migrate = total_rows
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if dry_run:
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logger.info(f"[DRY RUN] Would migrate {rows_to_migrate} rows")
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return rows_to_migrate
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migrated = previous_migrated_count
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migration_start_time = datetime.utcnow().isoformat()
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with ProgressTracker(
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total_rows,
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rows_to_migrate,
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f"Migrating {mysql_table}"
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) as progress:
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# Fetch and migrate rows in batches
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for batch in mysql_conn.fetch_all_rows(mysql_table):
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# Transform batch
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# Use ordered fetching for node consolidation with resume support
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for batch in mysql_conn.fetch_rows_ordered_for_consolidation(
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mysql_table,
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start_id=last_migrated_id
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):
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if not batch:
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break
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# Transform batch with consolidation enabled
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transformed = DataTransformer.transform_batch(
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mysql_table,
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batch
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batch,
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consolidate=True
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)
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# Insert batch
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@@ -85,65 +119,151 @@ class FullMigrator:
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columns
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)
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migrated += inserted
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progress.update(inserted)
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if inserted > 0:
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# For consolidated batches, count transformed rows, not source rows
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migrated += inserted
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progress.update(inserted)
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# Update state after each batch for resume capability
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# Use MAX id of the batch (represents last MySQL id processed)
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batch_max_id = max(
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int(row.get("id", 0)) for row in transformed
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)
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# Get actual row count from PostgreSQL for accuracy
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actual_count = pg_conn.get_row_count(pg_table)
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self._update_migration_state(
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pg_conn, actual_count, batch_max_id, migration_start_time
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)
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logger.info(
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f"✓ Migration complete: {migrated} rows migrated "
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f"to {pg_table}"
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)
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# Update migration state
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self._update_migration_state(pg_conn, migrated)
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return migrated
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except Exception as e:
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logger.error(f"Migration failed: {e}")
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raise
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def _update_migration_state(
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self,
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pg_conn: PostgreSQLConnector,
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rows_migrated: int
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) -> None:
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"""Update migration state tracking table.
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def _get_last_migrated_id(self, pg_conn: PostgreSQLConnector, pg_table: str) -> Optional[int]:
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"""Get the last migrated MySQL ID from migration_state table.
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|
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Args:
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pg_conn: PostgreSQL connection
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rows_migrated: Number of rows migrated
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pg_table: PostgreSQL table name
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Returns:
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Last migrated MySQL ID or None if no previous migration
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"""
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try:
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pg_table = self.config["postgres_table"]
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with pg_conn.connection.cursor() as cursor:
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cursor.execute(
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"SELECT last_migrated_id FROM migration_state WHERE table_name = %s",
|
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(pg_table,)
|
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)
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result = cursor.fetchone()
|
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if result and result[0]:
|
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return result[0]
|
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except Exception:
|
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pass
|
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return None
|
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|
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def _get_previous_migrated_count(self, pg_conn: PostgreSQLConnector, pg_table: str) -> int:
|
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"""Get the total rows migrated so far from migration_state table.
|
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|
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Args:
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pg_conn: PostgreSQL connection
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pg_table: PostgreSQL table name
|
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|
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Returns:
|
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Total rows migrated so far (0 if no previous migration)
|
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"""
|
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try:
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with pg_conn.connection.cursor() as cursor:
|
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cursor.execute(
|
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"SELECT total_rows_migrated FROM migration_state WHERE table_name = %s",
|
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(pg_table,)
|
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)
|
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result = cursor.fetchone()
|
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if result and result[0]:
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return result[0]
|
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except Exception:
|
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pass
|
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return 0
|
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|
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def _update_migration_state(
|
||||
self,
|
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pg_conn: PostgreSQLConnector,
|
||||
rows_migrated: int,
|
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last_id: Optional[int] = None,
|
||||
migration_start_time: Optional[str] = None
|
||||
) -> None:
|
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"""Update migration state in PostgreSQL and state file.
|
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|
||||
Args:
|
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pg_conn: PostgreSQL connection
|
||||
rows_migrated: Total number of rows migrated so far
|
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last_id: Last ID that was migrated (for resume capability)
|
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migration_start_time: When the migration started (ISO format)
|
||||
"""
|
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pg_table = self.config["postgres_table"]
|
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now = datetime.utcnow()
|
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status = "in_progress" if last_id is not None else "completed"
|
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|
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# Update PostgreSQL migration_state table
|
||||
try:
|
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# Use COALESCE to handle both insert (first time) and update (resume)
|
||||
# For resume: total_rows_migrated will be the full accumulated count
|
||||
query = f"""
|
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INSERT INTO migration_state
|
||||
(table_name, last_migrated_timestamp, total_rows_migrated, migration_completed_at, status)
|
||||
VALUES (%s, %s, %s, %s, %s)
|
||||
(table_name, last_migrated_timestamp, last_migrated_id, total_rows_migrated, migration_completed_at, status)
|
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VALUES (%s, %s, %s, %s, %s, %s)
|
||||
ON CONFLICT (table_name) DO UPDATE SET
|
||||
last_migrated_timestamp = EXCLUDED.last_migrated_timestamp,
|
||||
last_migrated_id = EXCLUDED.last_migrated_id,
|
||||
total_rows_migrated = EXCLUDED.total_rows_migrated,
|
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migration_completed_at = EXCLUDED.migration_completed_at,
|
||||
status = EXCLUDED.status
|
||||
"""
|
||||
now = datetime.utcnow()
|
||||
pg_conn.execute(query, (pg_table, now, rows_migrated, now, "completed"))
|
||||
logger.debug("Migration state updated")
|
||||
pg_conn.execute(
|
||||
query,
|
||||
(
|
||||
pg_table,
|
||||
migration_start_time or now.isoformat(),
|
||||
last_id,
|
||||
rows_migrated,
|
||||
now if status == "completed" else None,
|
||||
status
|
||||
)
|
||||
)
|
||||
logger.debug(f"Migration state updated: {rows_migrated} rows total, last_id={last_id}, status={status}")
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to update migration state: {e}")
|
||||
logger.warning(f"Failed to update migration state in PostgreSQL: {e}")
|
||||
|
||||
# Also save to state file for incremental migrations
|
||||
try:
|
||||
self.state.set_last_timestamp(pg_table, migration_start_time or now.isoformat())
|
||||
self.state.increment_migration_count(pg_table, rows_migrated)
|
||||
logger.debug("Migration state saved to file")
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to save migration state to file: {e}")
|
||||
|
||||
|
||||
def run_full_migration(
|
||||
table: str,
|
||||
dry_run: bool = False
|
||||
dry_run: bool = False,
|
||||
resume: bool = False
|
||||
) -> int:
|
||||
"""Run full migration for a table.
|
||||
|
||||
Args:
|
||||
table: Table name to migrate
|
||||
dry_run: If True, show what would be done without modifying data
|
||||
resume: If True, resume from last checkpoint instead of starting fresh
|
||||
|
||||
Returns:
|
||||
Number of rows migrated
|
||||
Number of rows migrated in this run
|
||||
"""
|
||||
migrator = FullMigrator(table)
|
||||
return migrator.migrate(dry_run=dry_run)
|
||||
return migrator.migrate(dry_run=dry_run, resume=resume)
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
"""Incremental migration from MySQL to PostgreSQL based on timestamps."""
|
||||
from datetime import datetime
|
||||
from typing import Optional
|
||||
import psycopg
|
||||
|
||||
from config import get_settings, TABLE_CONFIGS
|
||||
from src.connectors.mysql_connector import MySQLConnector
|
||||
@@ -31,6 +32,33 @@ class IncrementalMigrator:
|
||||
self.settings = get_settings()
|
||||
self.state = MigrationState(state_file)
|
||||
|
||||
def _get_last_timestamp_from_db(
|
||||
self,
|
||||
pg_conn: PostgreSQLConnector,
|
||||
pg_table: str
|
||||
) -> Optional[str]:
|
||||
"""Get last migration timestamp from PostgreSQL migration_state table.
|
||||
|
||||
Args:
|
||||
pg_conn: PostgreSQL connector
|
||||
pg_table: PostgreSQL table name
|
||||
|
||||
Returns:
|
||||
ISO format timestamp or None if not found
|
||||
"""
|
||||
try:
|
||||
with pg_conn.connection.cursor() as cursor:
|
||||
cursor.execute(
|
||||
"SELECT last_migrated_timestamp FROM migration_state WHERE table_name = %s",
|
||||
(pg_table,)
|
||||
)
|
||||
result = cursor.fetchone()
|
||||
if result and result[0]:
|
||||
return result[0].isoformat()
|
||||
except psycopg.Error:
|
||||
return None
|
||||
return None
|
||||
|
||||
def migrate(self, dry_run: bool = False, use_id: bool = False) -> int:
|
||||
"""Perform incremental migration since last sync.
|
||||
|
||||
@@ -88,9 +116,19 @@ class IncrementalMigrator:
|
||||
Returns:
|
||||
Number of rows migrated
|
||||
"""
|
||||
# Get last migration timestamp
|
||||
# Try to get last migration timestamp from state file first
|
||||
last_timestamp = self.state.get_last_timestamp(pg_table)
|
||||
|
||||
# If not in state file, try to get from PostgreSQL migration_state table
|
||||
if last_timestamp is None:
|
||||
try:
|
||||
last_timestamp = self._get_last_timestamp_from_db(pg_conn, pg_table)
|
||||
if last_timestamp:
|
||||
logger.info(f"Found previous migration state in database: {last_timestamp}")
|
||||
except Exception as e:
|
||||
logger.debug(f"Could not read from migration_state table: {e}")
|
||||
last_timestamp = None
|
||||
|
||||
if last_timestamp is None:
|
||||
logger.info(
|
||||
f"No previous migration found for {pg_table}. "
|
||||
@@ -98,6 +136,8 @@ class IncrementalMigrator:
|
||||
)
|
||||
return 0
|
||||
|
||||
logger.info(f"Last migration timestamp: {last_timestamp}")
|
||||
|
||||
# Count rows to migrate
|
||||
timestamp_col = "updated_at" if mysql_table == "ELABDATADISP" else "created_at"
|
||||
|
||||
@@ -107,7 +147,7 @@ class IncrementalMigrator:
|
||||
timestamp_col
|
||||
)
|
||||
|
||||
logger.info(f"Last timestamp in PostgreSQL: {pg_max_timestamp}")
|
||||
logger.info(f"Current max timestamp in PostgreSQL: {pg_max_timestamp}")
|
||||
|
||||
if dry_run:
|
||||
logger.info("[DRY RUN] Would migrate rows after timestamp")
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
"""Data transformation from MySQL to PostgreSQL format."""
|
||||
from typing import Dict, Any, List
|
||||
from typing import Dict, Any, List, Tuple
|
||||
from datetime import datetime, time, timedelta
|
||||
from config import (
|
||||
RAWDATACOR_COLUMNS,
|
||||
@@ -45,17 +45,16 @@ class DataTransformer:
|
||||
raise ValueError(f"Unsupported event_time type: {type(event_time)}")
|
||||
|
||||
@staticmethod
|
||||
def transform_rawdatacor_row(mysql_row: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""Transform a RAWDATACOR row from MySQL to PostgreSQL format.
|
||||
def _build_measurement_for_node(mysql_row: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""Build measurement object for a single node.
|
||||
|
||||
Args:
|
||||
mysql_row: Row dictionary from MySQL
|
||||
|
||||
Returns:
|
||||
Transformed row dictionary for PostgreSQL
|
||||
Measurement dictionary for this node (without node key wrapper)
|
||||
"""
|
||||
# Create measurements JSONB
|
||||
measurements = {}
|
||||
measurement = {}
|
||||
|
||||
# Map Val0-ValF with their units
|
||||
for i, val_col in enumerate(RAWDATACOR_COLUMNS["val_columns"]):
|
||||
@@ -66,10 +65,31 @@ class DataTransformer:
|
||||
|
||||
# Only add to JSONB if value is not None
|
||||
if value is not None:
|
||||
measurements[str(i)] = {
|
||||
"value": str(value),
|
||||
"unit": unit if unit else None,
|
||||
}
|
||||
measurement[str(i)] = {"value": str(value)}
|
||||
# Only add unit if it's not None (saves ~20% space)
|
||||
if unit:
|
||||
measurement[str(i)]["unit"] = unit
|
||||
|
||||
return measurement
|
||||
|
||||
@staticmethod
|
||||
def transform_rawdatacor_row(mysql_row: Dict[str, Any], measurements: Dict[str, Any] = None) -> Dict[str, Any]:
|
||||
"""Transform a RAWDATACOR row from MySQL to PostgreSQL format.
|
||||
|
||||
Args:
|
||||
mysql_row: Row dictionary from MySQL
|
||||
measurements: Pre-built measurements JSONB (for consolidated nodes).
|
||||
If None, builds measurements from mysql_row.
|
||||
|
||||
Returns:
|
||||
Transformed row dictionary for PostgreSQL
|
||||
"""
|
||||
# If measurements not provided, build from single row
|
||||
if measurements is None:
|
||||
node_num = mysql_row.get("NodeNum")
|
||||
node_measurements = DataTransformer._build_measurement_for_node(mysql_row)
|
||||
# Wrap with node number as key for consolidation compatibility
|
||||
measurements = {str(node_num): node_measurements} if node_num is not None else {}
|
||||
|
||||
# Combine event_date and event_time into event_timestamp
|
||||
event_date = mysql_row.get("EventDate")
|
||||
@@ -94,11 +114,11 @@ class DataTransformer:
|
||||
event_timestamp = None
|
||||
|
||||
# Create PostgreSQL row
|
||||
# Note: node_num is now stored in measurements JSONB, not as separate column
|
||||
pg_row = {
|
||||
"id": mysql_row["id"],
|
||||
"unit_name": mysql_row.get("UnitName"),
|
||||
"tool_name_id": mysql_row["ToolNameID"],
|
||||
"node_num": mysql_row["NodeNum"],
|
||||
"event_timestamp": event_timestamp,
|
||||
"bat_level": mysql_row["BatLevel"],
|
||||
"temperature": mysql_row["Temperature"],
|
||||
@@ -179,25 +199,103 @@ class DataTransformer:
|
||||
|
||||
return pg_row
|
||||
|
||||
@staticmethod
|
||||
def consolidate_rawdatacor_batch(
|
||||
rows: List[Dict[str, Any]]
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""Consolidate RAWDATACOR rows by (unit_name, tool_name_id, event_timestamp).
|
||||
|
||||
Groups multiple nodes with the same key into a single row with measurements
|
||||
keyed by node number. Uses MAX(id) as the consolidated row ID for proper resume.
|
||||
|
||||
Args:
|
||||
rows: List of row dictionaries from MySQL, ordered by
|
||||
(UnitName, ToolNameID, EventDate, EventTime, NodeNum)
|
||||
|
||||
Returns:
|
||||
List of consolidated row dictionaries ready for transformation
|
||||
"""
|
||||
if not rows:
|
||||
return []
|
||||
|
||||
# Group rows by consolidation key
|
||||
groups = {}
|
||||
group_order = [] # Track order of first appearance
|
||||
|
||||
for row in rows:
|
||||
# Build consolidation key
|
||||
unit_name = row.get("UnitName")
|
||||
tool_name_id = row["ToolNameID"]
|
||||
event_date = row.get("EventDate")
|
||||
event_time = row.get("EventTime")
|
||||
|
||||
# Create a hashable key
|
||||
key = (unit_name, tool_name_id, event_date, event_time)
|
||||
|
||||
if key not in groups:
|
||||
groups[key] = []
|
||||
group_order.append(key)
|
||||
|
||||
groups[key].append(row)
|
||||
|
||||
# Transform each group into a consolidated row
|
||||
consolidated_rows = []
|
||||
|
||||
for key in group_order:
|
||||
group_rows = groups[key]
|
||||
|
||||
# Build consolidated measurements with nodes as keys
|
||||
consolidated_measurements = {}
|
||||
|
||||
for row in group_rows:
|
||||
node_num = row.get("NodeNum")
|
||||
node_measurements = DataTransformer._build_measurement_for_node(row)
|
||||
# Store measurements with node number as key
|
||||
consolidated_measurements[str(node_num)] = node_measurements
|
||||
|
||||
# Use the row with minimum id as template for other fields
|
||||
min_id_row = min(group_rows, key=lambda r: r["id"])
|
||||
# Use the row with maximum id for the consolidated row ID (for proper resume)
|
||||
max_id_row = max(group_rows, key=lambda r: r["id"])
|
||||
|
||||
# Create consolidated row with pre-built measurements
|
||||
consolidated_row = DataTransformer.transform_rawdatacor_row(
|
||||
min_id_row,
|
||||
measurements=consolidated_measurements
|
||||
)
|
||||
|
||||
# Update id to MAX(id) of the group (represents last MySQL row processed)
|
||||
consolidated_row["id"] = max_id_row["id"]
|
||||
|
||||
consolidated_rows.append(consolidated_row)
|
||||
|
||||
return consolidated_rows
|
||||
|
||||
@staticmethod
|
||||
def transform_batch(
|
||||
table: str,
|
||||
rows: List[Dict[str, Any]]
|
||||
rows: List[Dict[str, Any]],
|
||||
consolidate: bool = False
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""Transform a batch of rows from MySQL to PostgreSQL format.
|
||||
|
||||
Args:
|
||||
table: Table name ('RAWDATACOR' or 'ELABDATADISP')
|
||||
rows: List of row dictionaries from MySQL
|
||||
consolidate: If True and table is RAWDATACOR, consolidate nodes
|
||||
|
||||
Returns:
|
||||
List of transformed row dictionaries for PostgreSQL
|
||||
"""
|
||||
if table == "RAWDATACOR":
|
||||
return [
|
||||
DataTransformer.transform_rawdatacor_row(row)
|
||||
for row in rows
|
||||
]
|
||||
if consolidate:
|
||||
# Consolidate rows by key first, then they're already transformed
|
||||
return DataTransformer.consolidate_rawdatacor_batch(rows)
|
||||
else:
|
||||
return [
|
||||
DataTransformer.transform_rawdatacor_row(row)
|
||||
for row in rows
|
||||
]
|
||||
elif table == "ELABDATADISP":
|
||||
return [
|
||||
DataTransformer.transform_elabdatadisp_row(row)
|
||||
@@ -221,7 +319,6 @@ class DataTransformer:
|
||||
"id",
|
||||
"unit_name",
|
||||
"tool_name_id",
|
||||
"node_num",
|
||||
"event_timestamp",
|
||||
"bat_level",
|
||||
"temperature",
|
||||
|
||||
@@ -16,11 +16,11 @@ def create_rawdatacor_schema() -> str:
|
||||
CREATE SEQUENCE IF NOT EXISTS rawdatacor_id_seq;
|
||||
|
||||
-- Create RAWDATACOR table with partitioning
|
||||
-- Note: node_num is stored in measurements JSONB, not as a separate column
|
||||
CREATE TABLE IF NOT EXISTS rawdatacor (
|
||||
id BIGINT NOT NULL DEFAULT nextval('rawdatacor_id_seq'),
|
||||
unit_name VARCHAR(32),
|
||||
tool_name_id VARCHAR(32) NOT NULL,
|
||||
node_num INTEGER NOT NULL,
|
||||
event_timestamp TIMESTAMP NOT NULL,
|
||||
bat_level NUMERIC(4,2) NOT NULL,
|
||||
temperature NUMERIC(5,2) NOT NULL,
|
||||
@@ -55,8 +55,8 @@ CREATE TABLE IF NOT EXISTS rawdatacor_default
|
||||
# Add indexes
|
||||
sql += """
|
||||
-- Create indexes
|
||||
CREATE INDEX IF NOT EXISTS idx_unit_tool_node_datetime_raw
|
||||
ON rawdatacor(unit_name, tool_name_id, node_num, event_timestamp);
|
||||
CREATE INDEX IF NOT EXISTS idx_unit_tool_datetime_raw
|
||||
ON rawdatacor(unit_name, tool_name_id, event_timestamp);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_unit_tool_raw
|
||||
ON rawdatacor(unit_name, tool_name_id);
|
||||
|
||||
@@ -62,6 +62,7 @@ class TestDataTransformation:
|
||||
assert pg_row["id"] == 1
|
||||
assert pg_row["unit_name"] == "TestUnit"
|
||||
assert pg_row["tool_name_id"] == "Tool1"
|
||||
assert "node_num" not in pg_row # node_num should NOT be a column anymore
|
||||
assert pg_row["event_timestamp"] is not None
|
||||
assert pg_row["event_timestamp"].year == 2024
|
||||
assert pg_row["event_timestamp"].month == 1
|
||||
@@ -69,11 +70,15 @@ class TestDataTransformation:
|
||||
assert pg_row["event_timestamp"].hour == 12
|
||||
assert pg_row["event_timestamp"].minute == 0
|
||||
assert isinstance(pg_row["measurements"], dict)
|
||||
assert "0" in pg_row["measurements"]
|
||||
assert pg_row["measurements"]["0"]["value"] == "100.5"
|
||||
assert pg_row["measurements"]["0"]["unit"] == "°C"
|
||||
assert "1" not in pg_row["measurements"] # NULL values excluded
|
||||
assert "2" in pg_row["measurements"]
|
||||
# Verify node is a key in measurements JSONB (single node case)
|
||||
assert "1" in pg_row["measurements"] # node number as key
|
||||
assert "0" in pg_row["measurements"]["1"]
|
||||
assert pg_row["measurements"]["1"]["0"]["value"] == "100.5"
|
||||
assert pg_row["measurements"]["1"]["0"]["unit"] == "°C"
|
||||
assert "1" not in pg_row["measurements"]["1"] # NULL values excluded
|
||||
assert "2" in pg_row["measurements"]["1"]
|
||||
assert pg_row["measurements"]["1"]["2"]["value"] == "200.3"
|
||||
assert pg_row["measurements"]["1"]["2"]["unit"] == "m/s"
|
||||
|
||||
def test_elabdatadisp_transformation(self):
|
||||
"""Test ELABDATADISP row transformation."""
|
||||
@@ -246,6 +251,167 @@ class TestTimeConversion:
|
||||
assert pg_row["event_timestamp"].hour == 0
|
||||
assert pg_row["event_timestamp"].minute == 0
|
||||
|
||||
# Verify that unit is NOT included when it's None (optimization)
|
||||
assert "0" in pg_row["measurements"]
|
||||
assert pg_row["measurements"]["0"]["value"] == "-1709"
|
||||
assert "unit" not in pg_row["measurements"]["0"] # unit should not exist when None
|
||||
|
||||
def test_rawdatacor_consolidation(self):
|
||||
"""Test consolidation of multiple nodes into single JSONB row."""
|
||||
# Create three rows with same (unit, tool, timestamp) but different nodes
|
||||
rows = [
|
||||
{
|
||||
"id": 1,
|
||||
"UnitName": "TestUnit",
|
||||
"ToolNameID": "Tool1",
|
||||
"NodeNum": 1,
|
||||
"EventDate": "2024-01-01",
|
||||
"EventTime": "12:00:00",
|
||||
"BatLevel": 3.5,
|
||||
"Temperature": 25.5,
|
||||
"Val0": "100.5",
|
||||
"Val1": None,
|
||||
"Val2": "200.3",
|
||||
"Val0_unitmisure": "°C",
|
||||
"Val1_unitmisure": None,
|
||||
"Val2_unitmisure": "m/s",
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"UnitName": "TestUnit",
|
||||
"ToolNameID": "Tool1",
|
||||
"NodeNum": 2,
|
||||
"EventDate": "2024-01-01",
|
||||
"EventTime": "12:00:00",
|
||||
"BatLevel": 3.5,
|
||||
"Temperature": 25.5,
|
||||
"Val0": "101.2",
|
||||
"Val1": None,
|
||||
"Val2": "205.1",
|
||||
"Val0_unitmisure": "°C",
|
||||
"Val1_unitmisure": None,
|
||||
"Val2_unitmisure": "m/s",
|
||||
},
|
||||
{
|
||||
"id": 3,
|
||||
"UnitName": "TestUnit",
|
||||
"ToolNameID": "Tool1",
|
||||
"NodeNum": 3,
|
||||
"EventDate": "2024-01-01",
|
||||
"EventTime": "12:00:00",
|
||||
"BatLevel": 3.5,
|
||||
"Temperature": 25.5,
|
||||
"Val0": "102.0",
|
||||
"Val1": None,
|
||||
"Val2": "210.5",
|
||||
"Val0_unitmisure": "°C",
|
||||
"Val1_unitmisure": None,
|
||||
"Val2_unitmisure": "m/s",
|
||||
},
|
||||
]
|
||||
|
||||
# Add remaining Val columns as None for all rows
|
||||
for row in rows:
|
||||
for i in range(3, 16):
|
||||
col = f"Val{i:X}"
|
||||
row[col] = None
|
||||
row[f"{col}_unitmisure"] = None
|
||||
row["created_at"] = None
|
||||
row["BatLevelModule"] = None
|
||||
row["TemperatureModule"] = None
|
||||
row["RssiModule"] = None
|
||||
|
||||
# Consolidate
|
||||
consolidated = DataTransformer.consolidate_rawdatacor_batch(rows)
|
||||
|
||||
# Should have 1 consolidated row (all three nodes have same unit/tool/timestamp)
|
||||
assert len(consolidated) == 1
|
||||
|
||||
consolidated_row = consolidated[0]
|
||||
|
||||
# Verify consolidated row properties
|
||||
assert consolidated_row["id"] == 3 # MAX(id) for proper resume
|
||||
assert consolidated_row["unit_name"] == "TestUnit"
|
||||
assert consolidated_row["tool_name_id"] == "Tool1"
|
||||
assert consolidated_row["bat_level"] == 3.5
|
||||
assert consolidated_row["temperature"] == 25.5
|
||||
|
||||
# Verify all three nodes are in measurements
|
||||
measurements = consolidated_row["measurements"]
|
||||
assert "1" in measurements
|
||||
assert "2" in measurements
|
||||
assert "3" in measurements
|
||||
|
||||
# Verify node 1 measurements
|
||||
assert measurements["1"]["0"]["value"] == "100.5"
|
||||
assert measurements["1"]["0"]["unit"] == "°C"
|
||||
assert measurements["1"]["2"]["value"] == "200.3"
|
||||
|
||||
# Verify node 2 measurements
|
||||
assert measurements["2"]["0"]["value"] == "101.2"
|
||||
assert measurements["2"]["2"]["value"] == "205.1"
|
||||
|
||||
# Verify node 3 measurements
|
||||
assert measurements["3"]["0"]["value"] == "102.0"
|
||||
assert measurements["3"]["2"]["value"] == "210.5"
|
||||
|
||||
def test_rawdatacor_consolidation_with_different_keys(self):
|
||||
"""Test that rows with different keys are NOT consolidated."""
|
||||
# Two rows with different units
|
||||
rows = [
|
||||
{
|
||||
"id": 1,
|
||||
"UnitName": "Unit1",
|
||||
"ToolNameID": "Tool1",
|
||||
"NodeNum": 1,
|
||||
"EventDate": "2024-01-01",
|
||||
"EventTime": "12:00:00",
|
||||
"BatLevel": 3.5,
|
||||
"Temperature": 25.5,
|
||||
"Val0": "100.5",
|
||||
"Val1": None,
|
||||
"Val2": None,
|
||||
"Val0_unitmisure": "°C",
|
||||
"Val1_unitmisure": None,
|
||||
"Val2_unitmisure": None,
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"UnitName": "Unit2", # Different unit
|
||||
"ToolNameID": "Tool1",
|
||||
"NodeNum": 1,
|
||||
"EventDate": "2024-01-01",
|
||||
"EventTime": "12:00:00",
|
||||
"BatLevel": 3.5,
|
||||
"Temperature": 25.5,
|
||||
"Val0": "100.5",
|
||||
"Val1": None,
|
||||
"Val2": None,
|
||||
"Val0_unitmisure": "°C",
|
||||
"Val1_unitmisure": None,
|
||||
"Val2_unitmisure": None,
|
||||
},
|
||||
]
|
||||
|
||||
# Add remaining Val columns as None for all rows
|
||||
for row in rows:
|
||||
for i in range(3, 16):
|
||||
col = f"Val{i:X}"
|
||||
row[col] = None
|
||||
row[f"{col}_unitmisure"] = None
|
||||
row["created_at"] = None
|
||||
row["BatLevelModule"] = None
|
||||
row["TemperatureModule"] = None
|
||||
row["RssiModule"] = None
|
||||
|
||||
# Consolidate
|
||||
consolidated = DataTransformer.consolidate_rawdatacor_batch(rows)
|
||||
|
||||
# Should have 2 rows (different units)
|
||||
assert len(consolidated) == 2
|
||||
assert consolidated[0]["unit_name"] == "Unit1"
|
||||
assert consolidated[1]["unit_name"] == "Unit2"
|
||||
|
||||
|
||||
class TestFieldMapping:
|
||||
"""Test field mapping configuration."""
|
||||
|
||||
Reference in New Issue
Block a user