Skip to main content

COPY INTO Command — Complete Guide with All Options

COPY INTO Command — Complete Guide with All Options​

Welcome back to RetailCo, our fictional retail company.
Alice, the data engineer, now has staged data files and needs to load them into Snowflake tables efficiently.

“The COPY INTO command is like a magic wand — it moves data from your stage into tables safely and quickly,” she explains.

Let’s explore how COPY INTO works, all its options, and real-world use cases.

🏗️ What Is COPY INTO?​

The COPY INTO command loads data from a stage (internal or external) into a Snowflake table.

Basic syntax:

COPY INTO <table_name>
FROM <stage_name>
FILE_FORMAT = (TYPE = CSV)
ON_ERROR = 'CONTINUE';
  • <table_name> → destination table
  • <stage_name> → internal or external stage
  • FILE_FORMAT → CSV, JSON, Parquet, etc.
  • ON_ERROR → what to do if errors occur

🔹 Key Options​

1️⃣ FILE_FORMAT​

Specifies how Snowflake interprets files:

FILE_FORMAT = (TYPE = CSV FIELD_OPTIONALLY_ENCLOSED_BY='"' SKIP_HEADER=1)

Other formats: JSON, PARQUET, ORC.

2️⃣ ON_ERROR​

Controls error handling:

OptionBehavior
CONTINUESkip bad files/rows, continue loading
ABORT_STATEMENTStop the load if an error occurs (default)
SKIP_FILESkip the entire file if an error occurs

RetailCo example: Alice uses ON_ERROR='CONTINUE' to skip malformed CSV rows while loading daily sales.

3️⃣ PATTERN​

Load only specific files matching a regex:

COPY INTO SALES
FROM @RAW_SALES_STAGE
FILE_FORMAT = (TYPE=CSV)
PATTERN = '.*_jan.csv';
  • Only files ending with _jan.csv are loaded
  • Useful for incremental loads

4️⃣ FORCE​

Forces reload of files even if they were already loaded:

COPY INTO SALES
FROM @RAW_SALES_STAGE
FILE_FORMAT = (TYPE=CSV)
FORCE = TRUE;
  • Default: Snowflake tracks loaded files to avoid duplicates
  • Use FORCE only if you want to reload intentionally

5️⃣ PURGE​

Deletes files after successful load (internal stages only):

COPY INTO SALES
FROM @%SALES
FILE_FORMAT = (TYPE=CSV)
PURGE = TRUE;
  • Keeps internal stages clean
  • Saves storage costs

6️⃣ VALIDATION_MODE​

Check files without actually loading:

COPY INTO SALES
FROM @RAW_SALES_STAGE
VALIDATION_MODE = RETURN_ERRORS;
  • Useful for pre-checking data quality

🧩 Real-World Use Case — RetailCo​

  1. Daily sales CSVs arrive in @RAW_SALES_STAGE
  2. Alice runs:
COPY INTO SALES
FROM @RAW_SALES_STAGE
FILE_FORMAT=(TYPE=CSV FIELD_OPTIONALLY_ENCLOSED_BY='"' SKIP_HEADER=1)
ON_ERROR='CONTINUE'
PATTERN='.*_2025-11-27.csv';
  1. Bad rows are skipped, valid rows load into table
  2. Stage files are automatically purged after loading:
COPY INTO SALES
FROM @%SALES
PURGE = TRUE;

Result: Clean, efficient, and automated daily data load workflow.

🧠 Best Practices​

  1. Always define a file format matching your data
  2. Use ON_ERROR wisely to handle unexpected data
  3. Apply PATTERN for incremental or selective loads
  4. Use PURGE for internal stages to save storage
  5. Test with VALIDATION_MODE before production load
  6. Leverage FORCE only when necessary to reload

🏁 Quick Summary​

  • COPY INTO = primary command to load data from stages into Snowflake tables
  • Key options: FILE_FORMAT, ON_ERROR, PATTERN, FORCE, PURGE, VALIDATION_MODE
  • Supports internal and external stages
  • Best practices: proper file formats, error handling, incremental loads, and stage cleanup
  • Enables fast, reliable, and production-ready ETL workflows

🚀 Coming Next

👉 Snowpipe — Real-Time Streaming Load with Example Pipeline