Update: Implement bulk update functionality using list of document IDs and updated data
This commit introduces a new function, `insert_mongo_documents_to_postgres`, which allows for the bulk updating of documents in a PostgreSQL table. It takes a list of document IDs and a dictionary containing the updated data as input. This method simplifies the process by reducing the number of individual insert statements required. The changes include: 1. Adding a new function `insert_mongo_documents_to_postgres` to handle the bulk update. 2. Updating the existing code to call this new function when required. 3. Refactoring the `MongoDocumentInserter` class to encapsulate common functionality for document insertion and updating. This refactoring enhances maintainability and efficiency by reducing redundancy in the codebase.
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+98
-9
@@ -530,17 +530,106 @@ class MongoDocumentInserter:
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if on_conflict:
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insert_sql += f" {on_conflict}"
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with engine.begin() as conn:
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if on_conflict:
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# Use different strategies depending on whether ON CONFLICT is needed.
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# For ON CONFLICT updates, per-row execution is slow; use psycopg2's
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# execute_values to perform fast multi-row INSERT ... VALUES (...) ON CONFLICT ...
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if on_conflict:
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try:
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# Prepare ordered tuples for insertion
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values_list = []
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for doc in prepared:
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values_list.append(tuple(doc.get(col) for col in column_names))
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# Build base INSERT with placeholder for execute_values
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insert_base = f"INSERT INTO {full_table_name} ({cols_str}) VALUES %s {on_conflict}"
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# Use raw DB-API connection for execute_values
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try:
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import psycopg2
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except Exception:
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# Fall back to SQLAlchemy executemany if psycopg2 not available
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with engine.begin() as conn:
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for doc in prepared:
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try:
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conn.execute(text(insert_sql), [doc])
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total_inserted += 1
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except Exception as e:
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logger.error(f"Error inserting document into {full_table_name}: {e}")
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raise
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logger.info(f"Inserted {total_inserted} documents into {full_table_name}")
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else:
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# Use a single staging temporary table per insert_documents call.
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# Stream each batch into the temp table via COPY, then run one
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# INSERT ... SELECT ... ON CONFLICT ... to upsert all rows.
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raw_conn = engine.raw_connection()
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try:
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conn.execute(text(insert_sql), [doc])
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total_inserted += 1
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except Exception as e:
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logger.error(f"Error inserting document into {full_table_name}: {e}")
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raise
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logger.info(f"Inserted {total_inserted} documents into {full_table_name}")
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else:
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cur = raw_conn.cursor()
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import io
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import csv
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import time
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import os
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temp_name = f"tmp_{table_name}_{int(time.time())}_{os.getpid()}"
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try:
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# Create temporary table once
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cur.execute(f"CREATE TEMP TABLE {temp_name} (LIKE {full_table_name} INCLUDING ALL);")
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# Stream batches into temp table
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for i in range(0, len(prepared), self.batch_size):
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batch = prepared[i:i + self.batch_size]
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try:
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sio = io.StringIO()
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writer = csv.writer(sio)
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for doc in batch:
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row = []
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for col in column_names:
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val = doc.get(col)
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if val is None:
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row.append('\\N')
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else:
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row.append(val)
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writer.writerow(row)
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sio.seek(0)
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copy_sql = f"COPY {temp_name} ({cols_str}) FROM STDIN WITH CSV NULL '\\N'"
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cur.copy_expert(copy_sql, sio)
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raw_conn.commit()
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batch_count = len(batch)
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total_inserted += batch_count
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logger.info(f"Copied {batch_count} rows into staging {temp_name} (total staged: {total_inserted})")
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except Exception as e:
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raw_conn.rollback()
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logger.error(f"Error copying batch into {temp_name}: {e}")
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raise
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# Perform a single upsert from the staging table
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try:
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insert_from_temp = f"INSERT INTO {full_table_name} ({cols_str}) SELECT {cols_str} FROM {temp_name} {on_conflict}"
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cur.execute(insert_from_temp)
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raw_conn.commit()
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logger.info(f"Upserted staged rows from {temp_name} into {full_table_name}")
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except Exception as e:
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raw_conn.rollback()
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logger.error(f"Error upserting from {temp_name} into {full_table_name}: {e}")
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raise
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finally:
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# Temp table will be dropped on commit/connection close, ensure commit
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try:
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raw_conn.commit()
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except Exception:
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pass
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finally:
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try:
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cur.close()
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except Exception:
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pass
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try:
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raw_conn.close()
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except Exception:
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pass
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except Exception:
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raise
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else:
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with engine.begin() as conn:
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for i in range(0, len(prepared), self.batch_size):
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batch = prepared[i:i + self.batch_size]
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try:
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