pushing pg2pg changes

.github/workflows/docker-image.yml → .github/workflows/docker-image-pg2pg.yml

@@ -15,4 +15,4 @@ jobs:
     steps:
     - uses: actions/checkout@v3
     - name: Build the Docker image
-      run: docker build . --file Dockerfile --tag permitting-audit-replication:v1
+      run: docker build . --file Dockerfile_pg2pg --tag dap-pg2pg-replication:v1

.github/workflows/docker-publish.yml → .github/workflows/docker-publish-pg2pg.yml

@@ -4,9 +4,9 @@ on:
   # schedule:
     # - cron: '19 22 * * *'
   push:
-    branches: [ "main" ]
+    branches: [ "pg2pg_replication" ]
   pull_request:
-    branches: [ "main" ]
+    branches: [ "pg2pg_replication" ]
 
 env:
   REGISTRY: ghcr.io

Dockerfile_pg2pg

@@ -0,0 +1,17 @@
+FROM python:3.11.4-slim-buster
+
+WORKDIR    /app
+
+# PostgreSQL library 
+
+RUN apt-get update \
+    && apt-get -y install libpq-dev gcc \
+    && pip install psycopg2
+
+ADD *.py .
+
+COPY requirements.txt requirements.txt
+
+RUN pip3 install -r requirements.txt
+
+CMD ["python3", "./data_replication_pg2pg.py"]

data_replication_pg2pg.py

@@ -0,0 +1,224 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[1]: Imports
+# refer if block at line 38, some imports are conditional
+import psycopg2
+import psycopg2.pool
+import psycopg2.extras
+from psycopg2.extras import execute_batch
+import configparser
+import time
+import json
+import concurrent.futures
+from datetime import datetime
+import sys
+import os
+import argparse
+
+
+start = time.time()
+
+# In[3]: Retrieve Oracle database configuration
+src_postgres_username = os.environ['DB_USERNAME']
+src_postgres_password = os.environ['DB_PASSWORD']
+src_postgres_host = os.environ['DB_HOST']
+src_postgres_port = os.environ['DB_PORT']
+src_postgres_database = os.environ['DATABASE']
+# In[4]: Retrieve Postgres database configuration
+postgres_username = os.environ['ODS_USERNAME']
+postgres_password = os.environ['ODS_PASSWORD']
+postgres_host = os.environ['ODS_HOST']
+postgres_port = os.environ['ODS_PORT']
+postgres_database = os.environ['ODS_DATABASE']
+# In[5]: Script parameters
+mstr_schema = os.environ['MSTR_SCHEMA']
+app_name = os.environ['APP_NAME']
+concurrent_tasks = int(os.environ['CONCUR_TASKS'])
+audit_table = 'audit_batch_status'
+current_date = datetime.now().strftime('%Y-%m-%d')
+
+#concurrent_tasks = int(concurrent_tasks)    
+#In[5]: Concurrent tasks - number of tables to be replicated in parallel
+#concurrent_tasks = 5
+
+# In[6]: Set up Oracle connection pool
+# In[7]: Setup Postgres Pool 
+SrcPgresPool = psycopg2.pool.ThreadedConnectionPool(
+    minconn = concurrent_tasks, maxconn = concurrent_tasks,host=src_postgres_host, port=src_postgres_port, dbname=src_postgres_database, user=src_postgres_username, password=src_postgres_password
+)
+print('Source Postgres Connection Successful')
+
+# In[7]: Setup Postgres Pool 
+PgresPool = psycopg2.pool.ThreadedConnectionPool(
+    minconn = concurrent_tasks, maxconn = concurrent_tasks,host=postgres_host, port=postgres_port, dbname=postgres_database, user=postgres_username, password=postgres_password
+)
+print('Target Postgres Connection Successful')
+
+def del_audit_entries_rerun(current_date):
+  postgres_connection  = PgresPool.getconn()  
+  postgres_cursor = postgres_connection.cursor()
+  del_sql = f"""
+  DELETE FROM {mstr_schema}.{audit_table} c
+  where application_name='{app_name}' and batch_run_date='{current_date}'
+  """
+  postgres_cursor.execute(del_sql)
+  postgres_connection.commit()
+  postgres_cursor.close()
+  PgresPool.putconn(postgres_connection)
+  return print(del_sql)
+
+# Function to insert the audit batch status entry
+def audit_batch_status_insert(table_name,status):
+  postgres_connection  = PgresPool.getconn()  
+  postgres_cursor = postgres_connection.cursor()
+  try:
+    audit_batch_status_query = f"""INSERT INTO {mstr_schema}.{audit_table} VALUES ('{table_name}','{app_name}','replication','{status}',current_date)"""
+    print(audit_batch_status_query)
+    postgres_cursor.execute(audit_batch_status_query)
+    postgres_connection.commit()
+    print(f"Record inserted into audit batch status table")
+    return None
+  except Exception as e:
+      print(f"Error inserting record into to audit batch status table: {str(e)}")
+      return None
+  finally:
+        # Return the connection to the pool
+        if postgres_connection:
+            postgres_cursor.close()
+            PgresPool.putconn(postgres_connection)
+
+# In[8]: Function to get active rows from master table
+def get_active_tables(mstr_schema,app_name):
+  postgres_connection  = PgresPool.getconn()  
+  postgres_cursor = postgres_connection.cursor()
+  list_sql = f"""
+  SELECT application_name,source_schema_name,source_table_name,target_schema_name,target_table_name,truncate_flag,cdc_flag,full_inc_flag,cdc_column,replication_order,customsql_ind,customsql_query
+  from {mstr_schema}.cdc_master_table_list c
+  where  active_ind = 'Y' and application_name='{app_name}'
+  order by replication_order, source_table_name
+  """
+  with postgres_connection.cursor() as curs:
+            curs.execute(list_sql)
+            rows = curs.fetchall()
+  postgres_connection.commit()
+  postgres_cursor.close()
+  PgresPool.putconn(postgres_connection)
+  return rows
+
+# In[9]: Function to extract data from Oracle
+def extract_from_srcpg(table_name,source_schema,customsql_ind,customsql_query):
+    # Acquire a connection from the pool
+    srcpostgres_connection = SrcPgresPool.getconn()
+    srcpostgres_cursor = srcpostgres_connection.cursor()   
+    try:
+        if customsql_ind == "Y":
+            # Use placeholders in the query and bind the table name as a parameter
+            sql_query=customsql_query
+            print(sql_query)
+            srcpostgres_cursor.execute(sql_query)
+            rows = srcpostgres_cursor.fetchall()
+            #OrcPool.release(oracle_connection)
+            return rows  
+        else:
+            sql_query = f'SELECT * FROM {source_schema}.{table_name}'
+            print(sql_query)
+            srcpostgres_cursor.execute(sql_query)
+            rows = srcpostgres_cursor.fetchall()
+            #OrcPool.release(oracle_connection)
+            return rows
+
+    except Exception as e:
+        audit_batch_status_insert(table_name,'failed')
+        print(f"Error extracting data from SrcPostgres: {str(e)}")
+        #OrcPool.release(oracle_connection)  #Temporary change
+        return []
+
+    finally:
+        # Return the connection to the pool
+        if srcpostgres_connection:
+            srcpostgres_cursor.close()
+            SrcPgresPool.putconn(srcpostgres_connection)
+# In[10]: Function to load data into Target PostgreSQL using data from Source Oracle
+def load_into_postgres(table_name, data,target_schema):
+    postgres_connection = PgresPool.getconn()
+    postgres_cursor = postgres_connection.cursor()
+    try:
+        # Delete existing data in the target table
+        delete_query = f'TRUNCATE TABLE {target_schema}.{table_name}'
+        postgres_cursor.execute(delete_query)
+
+        # Build the INSERT query with placeholders
+        insert_query = f'INSERT INTO {target_schema}.{table_name} VALUES ({", ".join(["%s"] * len(data[0]))})'
+        #insert_query = f'INSERT INTO {target_schema}.{table_name} VALUES %s'
+
+        # Use execute_batch for efficient batch insert
+        with postgres_connection.cursor() as cursor:
+            # Prepare the data as a list of tuples
+            data_to_insert = [(tuple(row)) for row in data]
+            execute_batch(cursor, insert_query, data_to_insert)
+            postgres_connection.commit()
+            # Insert record to audit batch table        
+            audit_batch_status_insert(table_name,'success')
+
+
+    except Exception as e:
+        print(f"Error loading data into PostgreSQL: {str(e)}")
+        audit_batch_status_insert(table_name,'failed')
+    finally:
+        # Return the connection to the pool
+        if postgres_connection:
+            postgres_cursor.close()
+            PgresPool.putconn(postgres_connection)
+
+# In[11]: Function to call both extract and load functions
+def load_data_from_src_tgt(table_name,source_schema,target_schema,customsql_ind,customsql_query):
+        # Extract data from Oracle
+        print(f'Source: Thread {table_name} started at ' + datetime.now().strftime("%H:%M:%S"))
+        srcpg_data = extract_from_srcpg(table_name,source_schema,customsql_ind,customsql_query)  # Ensure table name is in uppercase
+        print(f'Source: Extraction for {table_name} completed at ' + datetime.now().strftime("%H:%M:%S"))
+
+        if srcpg_data:
+            # Load data into PostgreSQL
+            load_into_postgres(table_name, srcpg_data, target_schema)
+            print(f"Target: Data loaded into table: {table_name}")
+            print(f'Target: Thread {table_name} ended at ' + datetime.now().strftime("%H:%M:%S"))
+
+# In[12]: Initializing concurrency
+if __name__ == '__main__':
+    # Main ETL process
+    active_tables_rows =get_active_tables(mstr_schema,app_name) 
+    #print(active_tables_rows)
+    tables_to_extract = [(row[2],row[1],row[3],row[10],row[11]) for row in active_tables_rows]
+
+    print(f"tables to extract are {tables_to_extract}")
+    print(f'No of concurrent tasks:{concurrent_tasks}')
+     #Delete audit entries for rerun on same day
+    del_audit_entries_rerun(current_date)
+    # Using ThreadPoolExecutor to run tasks concurrently
+    with concurrent.futures.ThreadPoolExecutor(max_workers=concurrent_tasks) as executor:
+        # Submit tasks to the executor
+        future_to_table = {executor.submit(load_data_from_src_tgt, table[0],table[1],table[2],table[3],table[4]): table for table in tables_to_extract}
+
+        # Wait for all tasks to complete
+        concurrent.futures.wait(future_to_table)
+
+        # Print results
+        for future in future_to_table:
+            table_name = future_to_table[future]
+            try:
+                # Get the result of the task, if any
+                future.result()
+            except Exception as e:
+                # Handle exceptions that occurred during the task
+                print(f"Error replicating {table_name}: {e}")
+                audit_batch_status_insert(table_name[0],'failed')
+
+    # record end time
+    end = time.time()
+    SrcPgresPool.closeall()
+    PgresPool.closeall()
+
+    print("ETL process completed successfully.")
+    print("The time of execution of the program is:", (end - start) , "secs")
+