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pushing pg2pg ods replication scripts
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vishreddy01 committed Apr 12, 2024
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65 changes: 65 additions & 0 deletions .github/workflows/docker-pg2pg.yaml
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name: Push to GHCR

on:
push:
branches: [ "ods-replication-pg2pg" ]

env:
# DF-NOTE: pull ghcr.io/bcgov/nr-dap-ods-trino:main
REGISTRY: ghcr.io
DOCKERFILE_PATH: shared/ods_replication_pg2pg
IMAGE_NAME: ${{ github.repository }}-ods-pg2pg

jobs:
build:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
id-token: write

steps:
- name: Checkout repository
uses: actions/checkout@v3

- name: Install cosign
if: github.event_name != 'pull_request'
uses: sigstore/cosign-installer@v3.3.0

- name: Set up Docker Buildx
uses: docker/setup-buildx-action@f95db51fddba0c2d1ec667646a06c2ce06100226 # v3.0.0

- name: Log into registry ${{ env.REGISTRY }}
if: github.event_name != 'pull_request'
uses: docker/login-action@343f7c4344506bcbf9b4de18042ae17996df046d # v3.0.0
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}

- name: Extract Docker metadata
id: meta
uses: docker/metadata-action@96383f45573cb7f253c731d3b3ab81c87ef81934 # v5.0.0
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}

- name: Build and push Docker image
id: build-and-push
uses: docker/build-push-action@0565240e2d4ab88bba5387d719585280857ece09 # v5.0.0
with:
# DF-NOTE: to help the action find the Dockerfile to build from
context: ${{ env.DOCKERFILE_PATH }}/
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max

#- name: Sign the published Docker image
#if: ${{ github.event_name != 'pull_request' }}
#env:
# https://docs.github.com/en/actions/security-guides/security-hardening-for-github-actions#using-an-intermediate-environment-variable
#TAGS: ${{ steps.meta.outputs.tags }}
#DIGEST: ${{ steps.build-and-push.outputs.digest }}

#run: echo "${TAGS}" | xargs -I {} cosign sign --yes {}@${DIGEST}
17 changes: 17 additions & 0 deletions shared/ods_replication_pg2pg/Dockerfile
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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"]
224 changes: 224 additions & 0 deletions shared/ods_replication_pg2pg/data_replication_pg2pg.py
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#!/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")

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