Handling load errors in Snowflake - Step-by-Step Execution

Process Flow - Handling load errors

Start Load Data

↓

Attempt Data Load

↓

Error Occurs?

No→Load Success

Yes↓

Capture Error Details

↓

Log or Store Errors

↓

Decide: Retry or Skip

↓

Retry Load

↓

Load Success

↓

Skip Error Rows

↓

End Load Process

This flow shows how Snowflake handles data load errors by detecting errors, capturing details, logging them, and deciding whether to retry or skip problematic rows.

Execution Sample

Snowflake

COPY INTO my_table
FROM @my_stage/file.csv
ON_ERROR = 'CONTINUE';

This command loads data from a staged file into a table, continuing the load even if some rows cause errors.

Process Table

Step	Action	Error Detected	Error Details Captured	Rows Loaded	Rows Skipped
1	Start data load	No	N/A	0	0
2	Load row 1	No	N/A	1	0
3	Load row 2	Yes	Invalid date format	1	1
4	Load row 3	No	N/A	2	1
5	Load row 4	Yes	Null value in NOT NULL column	2	2
6	Load row 5	No	N/A	3	2
7	End load process	N/A	N/A	3	2

💡 All rows processed; load ended with 3 rows loaded and 2 rows skipped due to errors.

Status Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	After Step 5	After Step 6	Final
Rows Loaded	0	1	1	2	2	3	3
Rows Skipped	0	0	1	1	2	2	2
Error Details	[]	[]	["Invalid date format"]	["Invalid date format"]	["Invalid date format", "Null value in NOT NULL column"]	["Invalid date format", "Null value in NOT NULL column"]	["Invalid date format", "Null value in NOT NULL column"]

Key Moments - 3 Insights

Why does the load continue even after errors occur?

Because the ON_ERROR='CONTINUE' option tells Snowflake to skip error rows and keep loading the rest, as shown in steps 3 and 5 where errors are detected but loading proceeds.

How are error details tracked during the load?

Error details are captured and stored in a list each time an error occurs, as seen in the Error Details variable in steps 3 and 5 in the execution_table.

What happens to rows that cause errors during loading?

Rows with errors are skipped and not loaded into the table, increasing the Rows Skipped count, as shown in steps 3 and 5.

Visual Quiz - 3 Questions

Look at the execution table, how many rows were successfully loaded after step 4?

A 2

B 3

C 1

D 4

💡 Hint

Check the 'Rows Loaded' column at step 4 in the execution_table.

At which step does the first error occur during the load?

A Step 2

B Step 3

C Step 4

D Step 5

💡 Hint

Look for the first 'Yes' in the 'Error Detected' column in the execution_table.

If ON_ERROR was set to 'ABORT_STATEMENT', how would the execution_table change?

A Load would stop at first error, fewer rows loaded

B All rows would load regardless of errors

C Errors would be ignored and logged but load continues

D Rows with errors would be retried automatically

💡 Hint

Consider how 'CONTINUE' allows skipping errors; 'ABORT_STATEMENT' stops on error.

Concept Snapshot

Snowflake load errors are handled by options like ON_ERROR.
ON_ERROR='CONTINUE' skips bad rows and logs errors.
Errors are captured during load and rows skipped.
Load continues until all rows processed or aborted.
Use error handling to keep data load smooth and controlled.

Full Transcript

This visual execution shows how Snowflake handles load errors during data import. The process starts by attempting to load each row. When an error occurs, such as invalid data format or null in a required column, Snowflake captures the error details and skips the problematic row if ON_ERROR='CONTINUE' is set. The load continues with the next rows, accumulating counts of loaded and skipped rows. This approach allows partial data loading without stopping the entire process. The execution table tracks each step, showing when errors happen, how many rows load successfully, and how many are skipped. Variables like Rows Loaded, Rows Skipped, and Error Details update after each step. Key moments clarify why loading continues despite errors and how errors are tracked. The quiz tests understanding of when errors occur, how many rows load, and the effect of different ON_ERROR settings. This helps beginners see step-by-step how Snowflake manages load errors to keep data pipelines running smoothly.