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semantica/cookbook/advanced/snowflake_ingestion_examples.py
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Python

"""
Snowflake Ingestion Examples
This module provides comprehensive examples of using the Snowflake ingestor.
"""
import os
from datetime import datetime, timedelta
from semantica.ingest import SnowflakeIngestor
from semantica.utils.logging import get_logger
logger = get_logger("snowflake_examples")
def example_basic_ingestion():
"""Example: Basic table ingestion."""
print("\n=== Example 1: Basic Table Ingestion ===\n")
# Initialize ingestor with password authentication
ingestor = SnowflakeIngestor(
account=os.getenv("SNOWFLAKE_ACCOUNT"),
user=os.getenv("SNOWFLAKE_USER"),
password=os.getenv("SNOWFLAKE_PASSWORD"),
warehouse="COMPUTE_WH",
database="SAMPLE_DB",
schema="PUBLIC",
)
# Ingest a table
data = ingestor.ingest_table("CUSTOMERS", limit=10)
print(f"Retrieved {data.row_count} rows")
print(f"Columns: {data.columns}")
print(f"\nFirst row:")
print(data.data[0])
ingestor.close()
def example_query_execution():
"""Example: Execute custom SQL queries."""
print("\n=== Example 2: Query Execution ===\n")
ingestor = SnowflakeIngestor()
# Execute aggregation query
query = """
SELECT
COUNTRY,
COUNT(*) AS CUSTOMER_COUNT,
SUM(TOTAL_PURCHASES) AS TOTAL_REVENUE
FROM CUSTOMERS
GROUP BY COUNTRY
ORDER BY TOTAL_REVENUE DESC
LIMIT 10
"""
data = ingestor.ingest_query(query)
print(f"Top 10 countries by revenue:")
for row in data.data:
print(
f" {row['COUNTRY']}: {row['CUSTOMER_COUNT']} customers, "
f"${row['TOTAL_REVENUE']:,.2f} revenue"
)
ingestor.close()
def example_parameterized_query():
"""Example: Parameterized queries."""
print("\n=== Example 3: Parameterized Queries ===\n")
ingestor = SnowflakeIngestor()
# Calculate date range
end_date = datetime.now()
start_date = end_date - timedelta(days=30)
# Execute parameterized query
query = """
SELECT
ORDER_ID,
CUSTOMER_ID,
PRODUCT_NAME,
AMOUNT,
ORDER_DATE
FROM ORDERS
WHERE ORDER_DATE BETWEEN %(start_date)s AND %(end_date)s
AND AMOUNT > %(min_amount)s
ORDER BY ORDER_DATE DESC
"""
data = ingestor.ingest_query(
query,
params={
"start_date": start_date.strftime("%Y-%m-%d"),
"end_date": end_date.strftime("%Y-%m-%d"),
"min_amount": 100.0,
},
)
print(f"Found {data.row_count} orders in the last 30 days over $100")
ingestor.close()
def example_schema_introspection():
"""Example: Table schema introspection."""
print("\n=== Example 4: Schema Introspection ===\n")
ingestor = SnowflakeIngestor()
# Get table schema
schema = ingestor.get_table_schema("CUSTOMERS")
print("Table schema for CUSTOMERS:")
print(f"Primary keys: {schema['primary_keys']}\n")
print("Columns:")
for col in schema["columns"]:
nullable = "NULL" if col["nullable"] else "NOT NULL"
default = f" DEFAULT {col['default']}" if col["default"] else ""
print(f" {col['name']}: {col['type']} {nullable}{default}")
ingestor.close()
def example_list_tables():
"""Example: List all tables in a schema."""
print("\n=== Example 5: List Tables ===\n")
ingestor = SnowflakeIngestor()
# List tables in current schema
tables = ingestor.list_tables()
print(f"Found {len(tables)} tables:")
for table in tables:
print(f" - {table}")
ingestor.close()
def example_pagination():
"""Example: Paginate large result sets."""
print("\n=== Example 6: Pagination ===\n")
ingestor = SnowflakeIngestor()
PAGE_SIZE = 100
total_rows = 0
# Paginate through large table
page = 0
while True:
data = ingestor.ingest_table(
"LARGE_TABLE", limit=PAGE_SIZE, offset=page * PAGE_SIZE
)
if data.row_count == 0:
break
total_rows += data.row_count
print(f"Page {page + 1}: {data.row_count} rows")
# Process page
process_page(data)
page += 1
print(f"\nTotal rows processed: {total_rows}")
ingestor.close()
def example_batch_processing():
"""Example: Batch processing with fetchmany."""
print("\n=== Example 7: Batch Processing ===\n")
ingestor = SnowflakeIngestor()
# Execute query with batching
data = ingestor.ingest_query(
"SELECT * FROM LARGE_TABLE WHERE STATUS = 'ACTIVE'", batch_size=1000
)
print(f"Retrieved {data.row_count} rows in batches of 1000")
ingestor.close()
def example_export_documents():
"""Example: Export to Semantica document format."""
print("\n=== Example 8: Export as Documents ===\n")
ingestor = SnowflakeIngestor()
# Ingest product data
data = ingestor.ingest_table("PRODUCTS", limit=10)
# Convert to documents
documents = ingestor.export_as_documents(
data, id_field="PRODUCT_ID", text_fields=["PRODUCT_NAME", "DESCRIPTION"]
)
print(f"Exported {len(documents)} documents")
print("\nFirst document:")
print(f" ID: {documents[0]['id']}")
print(f" Text: {documents[0]['text'][:100]}...")
print(f" Metadata: {documents[0]['metadata']}")
ingestor.close()
def example_key_pair_auth():
"""Example: Key-pair authentication."""
print("\n=== Example 9: Key-Pair Authentication ===\n")
ingestor = SnowflakeIngestor(
account=os.getenv("SNOWFLAKE_ACCOUNT"),
user=os.getenv("SNOWFLAKE_USER"),
private_key_path=os.getenv("SNOWFLAKE_PRIVATE_KEY_PATH"),
warehouse="COMPUTE_WH",
)
data = ingestor.ingest_table("CUSTOMERS", limit=5)
print(f"Successfully authenticated and retrieved {data.row_count} rows")
ingestor.close()
def example_context_manager():
"""Example: Using context manager."""
print("\n=== Example 10: Context Manager ===\n")
with SnowflakeIngestor() as ingestor:
data = ingestor.ingest_table("CUSTOMERS", limit=5)
print(f"Retrieved {data.row_count} rows")
# Connection automatically closed
print("Connection closed automatically")
def example_multi_schema():
"""Example: Multi-schema ingestion."""
print("\n=== Example 11: Multi-Schema Ingestion ===\n")
ingestor = SnowflakeIngestor()
# Ingest from different schemas
prod_customers = ingestor.ingest_table(
"CUSTOMERS", database="PROD_DB", schema="PUBLIC", limit=10
)
staging_customers = ingestor.ingest_table(
"CUSTOMERS", database="STAGING_DB", schema="PUBLIC", limit=10
)
print(f"Production customers: {prod_customers.row_count}")
print(f"Staging customers: {staging_customers.row_count}")
ingestor.close()
def example_error_handling():
"""Example: Error handling."""
print("\n=== Example 12: Error Handling ===\n")
from semantica.utils.exceptions import ProcessingError, ValidationError
try:
# Try to connect with invalid credentials
ingestor = SnowflakeIngestor(
account="invalid_account", user="invalid_user", password="invalid_password"
)
data = ingestor.ingest_table("CUSTOMERS")
except ValidationError as e:
print(f"Validation error: {e}")
except ProcessingError as e:
print(f"Processing error: {e}")
except Exception as e:
print(f"Unexpected error: {e}")
def example_incremental_load():
"""Example: Incremental data loading."""
print("\n=== Example 13: Incremental Loading ===\n")
ingestor = SnowflakeIngestor()
# Get last load timestamp (from your metadata store)
last_load = get_last_load_timestamp() # Your function
# Query only new/updated records
query = """
SELECT *
FROM CUSTOMERS
WHERE UPDATED_AT > %(last_load)s
ORDER BY UPDATED_AT ASC
"""
data = ingestor.ingest_query(query, params={"last_load": last_load})
print(f"Loaded {data.row_count} new/updated records since {last_load}")
# Update last load timestamp
if data.row_count > 0:
update_last_load_timestamp(datetime.now())
ingestor.close()
def example_etl_pipeline():
"""Example: Full ETL pipeline."""
print("\n=== Example 14: ETL Pipeline ===\n")
# Extract
ingestor = SnowflakeIngestor()
sales_query = """
SELECT
s.ORDER_ID,
s.CUSTOMER_ID,
c.CUSTOMER_NAME,
s.PRODUCT_ID,
p.PRODUCT_NAME,
s.AMOUNT,
s.ORDER_DATE
FROM SALES s
JOIN CUSTOMERS c ON s.CUSTOMER_ID = c.ID
JOIN PRODUCTS p ON s.PRODUCT_ID = p.ID
WHERE s.ORDER_DATE >= CURRENT_DATE - 7
"""
data = ingestor.ingest_query(sales_query)
print(f"Extracted {data.row_count} sales records")
# Transform
documents = ingestor.export_as_documents(
data, id_field="ORDER_ID", text_fields=["CUSTOMER_NAME", "PRODUCT_NAME"]
)
print(f"Transformed to {len(documents)} documents")
# Load (into Semantica)
from semantica.pipeline import Pipeline
pipeline = Pipeline()
for doc in documents:
pipeline.process_document(doc)
print("Loaded documents into Semantica pipeline")
ingestor.close()
# Utility functions for examples
def process_page(data):
"""Process a page of data."""
# Your processing logic here
pass
def get_last_load_timestamp():
"""Get the last load timestamp from metadata store."""
# Your implementation here
return (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d %H:%M:%S")
def update_last_load_timestamp(timestamp):
"""Update the last load timestamp in metadata store."""
# Your implementation here
pass
def main():
"""Run all examples."""
examples = [
example_basic_ingestion,
example_query_execution,
example_parameterized_query,
example_schema_introspection,
example_list_tables,
example_export_documents,
example_context_manager,
example_error_handling,
]
for example_func in examples:
try:
example_func()
except Exception as e:
logger.error(f"Example {example_func.__name__} failed: {e}")
if __name__ == "__main__":
# Set up environment variables
# export SNOWFLAKE_ACCOUNT=your_account
# export SNOWFLAKE_USER=your_user
# export SNOWFLAKE_PASSWORD=your_password
# export SNOWFLAKE_WAREHOUSE=COMPUTE_WH
# export SNOWFLAKE_DATABASE=SAMPLE_DB
# export SNOWFLAKE_SCHEMA=PUBLIC
main()