fix: Ensure complete node consolidation by ordering MySQL query by consolidation key
Root cause: Nodes 1-11 had IDs in 132M+ range while nodes 12-22 had IDs in 298-308 range, causing them to be fetched in batches thousands apart using keyset pagination by ID. This meant they arrived as separate groups and were never unified into a single consolidated row. Solution: Order MySQL query by (UnitName, ToolNameID, EventDate, EventTime) instead of by ID. This guarantees all rows for the same consolidation key arrive together, ensuring they are grouped and consolidated into a single row with JSONB measurements keyed by node number. Changes: - fetch_consolidation_groups_from_partition(): Changed from keyset pagination by ID to ORDER BY consolidation key. Simplify grouping logic since ORDER BY already ensures consecutive rows have same key. - full_migration.py: Add cleanup of partial partitions on resume. When resuming and a partition was started but not completed, delete its incomplete data before re-processing to avoid duplicates. Also recalculate total_rows_migrated from actual database count. - config.py: Add postgres_pk field to TABLE_CONFIGS to specify correct primary key column names in PostgreSQL (id vs id_elab_data). - Cleanup: Remove temporary test scripts used during debugging Performance note: ORDER BY consolidation key requires index for speed. Index (UnitName, ToolNameID, EventDate, EventTime) created with ALGORITHM=INPLACE LOCK=NONE to avoid blocking reads. 🤖 Generated with Claude Code Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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@@ -222,8 +222,8 @@ class MySQLConnector:
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Reads all rows from partition, sorted by consolidation key.
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Yields rows grouped by (UnitName, ToolNameID, EventDate, EventTime).
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Uses keyset pagination by ID to avoid expensive OFFSET + ORDER BY.
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Buffers incomplete groups at batch boundaries to ensure complete consolidation.
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Uses keyset pagination by consolidation key to ensure all rows of a key
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arrive together, even if they're scattered in ID space.
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Args:
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table: Table name
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@@ -244,76 +244,45 @@ class MySQLConnector:
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# Determine ID column name
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id_column = "idElabData" if table == "ELABDATADISP" else "id"
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max_retries = 3
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last_id = start_id
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# Buffer incomplete groups at batch boundaries when NodeNum hasn't cycled back to 1 yet
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buffered_group = []
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last_buffered_key = None
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last_key = None
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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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# Keyset pagination by ID: much faster than OFFSET + ORDER BY
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if last_id is None:
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# ORDER BY consolidation key (without NodeNum for speed)
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# Ensures all rows of a key arrive together, then we sort by NodeNum in memory
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if last_key is None:
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rows_query = f"""
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SELECT * FROM `{table}` PARTITION (`{partition}`)
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ORDER BY `{id_column}` ASC
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ORDER BY UnitName ASC, ToolNameID ASC, EventDate ASC, EventTime ASC
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LIMIT %s
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"""
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cursor.execute(rows_query, (limit,))
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else:
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# Resume after last key using tuple comparison
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rows_query = f"""
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SELECT * FROM `{table}` PARTITION (`{partition}`)
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WHERE `{id_column}` > %s
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ORDER BY `{id_column}` ASC
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WHERE (UnitName, ToolNameID, EventDate, EventTime) > (%s, %s, %s, %s)
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ORDER BY UnitName ASC, ToolNameID ASC, EventDate ASC, EventTime ASC
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LIMIT %s
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"""
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cursor.execute(rows_query, (last_id, limit))
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cursor.execute(rows_query, (last_key[0], last_key[1], last_key[2], last_key[3], limit))
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rows = cursor.fetchall()
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if not rows:
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# End of partition: yield any buffered group
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if buffered_group:
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yield buffered_group
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return
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# Sort by consolidation key THEN by NodeNum
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# This ensures all nodes of the same measurement are together,
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# and when NodeNum decreases, we know we've started a new measurement
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sorted_rows = sorted(rows, key=lambda r: (
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r.get("UnitName") or "",
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r.get("ToolNameID") or "",
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str(r.get("EventDate") or ""),
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str(r.get("EventTime") or ""),
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int(r.get("NodeNum") or 0)
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))
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# Sort rows by NodeNum within the batch
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# (rows already grouped by consolidation key from ORDER BY)
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sorted_rows = sorted(rows, key=lambda r: int(r.get("NodeNum") or 0))
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# Prepend any buffered group that belongs to the same consolidation key
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if buffered_group and sorted_rows:
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first_row_key = (
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sorted_rows[0].get("UnitName"),
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sorted_rows[0].get("ToolNameID"),
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sorted_rows[0].get("EventDate"),
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sorted_rows[0].get("EventTime")
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)
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if first_row_key == last_buffered_key:
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# Merge buffered rows with current batch (same consolidation key continues)
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sorted_rows = buffered_group + sorted_rows
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buffered_group = []
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else:
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# Buffered group belongs to different key - yield it first
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yield buffered_group
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buffered_group = []
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last_buffered_key = None
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# Group rows by consolidation key + detect group boundaries by NodeNum
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# When NodeNum decreases, we've moved to a new measurement
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# Group rows by consolidation key
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# Since rows are already ordered by key, all rows with same key are consecutive
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current_group = []
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current_key = None
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last_node_num = None
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for row in sorted_rows:
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key = (
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@@ -322,30 +291,32 @@ class MySQLConnector:
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row.get("EventDate"),
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row.get("EventTime")
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)
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node_num = int(row.get("NodeNum") or 0)
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# Detect group boundary: key changed OR NodeNum decreased (new measurement started)
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if current_key is not None and (key != current_key or (last_node_num is not None and node_num < last_node_num)):
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# Yield group when key changes
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if current_key is not None and key != current_key:
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if current_group:
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yield current_group
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current_group = []
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current_group.append(row)
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current_key = key
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last_node_num = node_num
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# At end of batch: handle the final group
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# At end of batch: handle final group
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if not rows or len(rows) < limit:
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# This is the last batch - yield the remaining group
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# Last batch - yield remaining group and finish
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if current_group:
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yield current_group
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return
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else:
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# More rows might exist - buffer the last group for next batch
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# More rows might exist - yield the last group only if key changed
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# If not, it will be continued/merged in next iteration
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if current_group:
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buffered_group = current_group
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last_buffered_key = current_key
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yield current_group
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# Update last_key for next iteration
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if current_key:
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last_key = current_key
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last_id = rows[-1][id_column]
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break # Success, exit retry loop
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except pymysql.Error as e:
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@@ -120,12 +120,43 @@ class FullMigrator:
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logger.info(f"[{partition_idx}/{len(partitions)}] Processing partition {partition}...")
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partition_group_count = 0
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# Determine resume point within this partition
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# If resuming and this is the last completed partition, start from last_id
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# If resuming and this is NOT the last completed partition,
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# it means it was only partially processed - clean it up first
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start_id = None
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if last_completed_partition == partition and previous_migrated_count > 0:
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# For resume within same partition, we need to query the last ID inserted
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# This is a simplified approach: just continue from ID tracking
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if resume and last_completed_partition and partition > last_completed_partition:
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# This partition was started but not completed - delete its partial data
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logger.warning(
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f"Partition {partition} was partially processed in previous run. "
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f"Cleaning up partial data before resume..."
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)
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try:
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with pg_conn.connection.cursor() as cursor:
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# Get the primary key column name for this table
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pk_column = self.config.get("postgres_pk", "id")
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# Delete rows from this partition that were inserted from MySQL rows
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# We identify them by looking for rows inserted after the migration started
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# This is safe because we're re-processing the entire partition
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# Note: This is a simplified approach - in production you might want more granular tracking
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last_id = self._get_last_migrated_id(pg_conn, pg_table)
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if last_id:
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cursor.execute(
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f"DELETE FROM {pg_table} WHERE {pk_column} > %s",
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(last_id,)
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)
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pg_conn.connection.commit()
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logger.info(f"Cleaned up partial data for partition {partition}")
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# Recalculate migrated count based on actual data in database
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cursor.execute(f"SELECT COUNT(*) FROM {pg_table}")
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actual_count = cursor.fetchone()[0]
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migrated = actual_count
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logger.info(f"Recalculated total_rows_migrated: {migrated} (actual rows in database)")
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except Exception as e:
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logger.warning(f"Failed to clean up partial data: {e}")
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# Continue anyway - might be able to deduplicate later
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elif resume and last_completed_partition == partition and previous_migrated_count > 0:
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# Resuming within the same partition - continue from last ID
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start_id = self._get_last_migrated_id(pg_conn, pg_table)
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if start_id:
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logger.info(f"Resuming partition {partition} from ID > {start_id}")
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@@ -330,6 +361,7 @@ class FullMigrator:
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# Update PostgreSQL migration_state table
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try:
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with pg_conn.connection.cursor() as cursor:
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logger.info(f"About to update migration_state: table={pg_table}, last_partition={last_partition}, last_id={last_id}, rows={rows_migrated}")
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query = f"""
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INSERT INTO migration_state
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(table_name, last_migrated_timestamp, last_migrated_id, total_rows_migrated,
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@@ -356,9 +388,10 @@ class FullMigrator:
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)
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)
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pg_conn.connection.commit()
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logger.debug(f"Migration state updated: {rows_migrated} rows total, last_id={last_id}, status={status}")
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logger.info(f"Migration state updated successfully: {rows_migrated} rows, last_partition={last_partition}, last_id={last_id}")
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except Exception as e:
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logger.warning(f"Failed to update migration state in PostgreSQL: {e}")
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logger.error(f"Failed to update migration state in PostgreSQL: {e}")
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raise
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# Also save to state file for incremental migrations
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try:
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