Snowsql put command skip modified file

In c:\myFolder, currently I have file myFile1.csv.
I ran the following command in SnowSQL

put file://C:\myFolder\myFile*.csv @my_csv_stage auto_compress=true;

Then, I ran the following command in Snowflake to load the csv file to table MYCSVTABLE

COPY INTO MYCSVTABLE
FROM @my_csv_stage
FILE_FORMAT = (FORMAT_NAME = mycsvformat)
PATTERN = '.*myFile.*[.]CSV.gz'
ON_ERROR = 'skip_file';

C:\myFolder\myFile1.csv was modified today, but "LIST @my_csv_stage" still shows the file last_modified as yesterday.
So, I execute another "put file://C:\myFolder\myFile*.csv @my_csv_stage auto_compress=true;", but under status it says "SKIPPED".

https://docs.snowflake.com/en/sql-reference/sql/put says this
"To overwrite an already-staged file, you must modify the file you are uploading so that its contents are different from the staged file, which results in a new checksum for the newly-staged file."

So, it sounds to me that even without the overwrite=true, if the files changed since the last time it was staged, it should overwrite the file, and NOT Skip the file.

When I use overwrite=true in my put file, and I have other files myFile2.csv and myFile3.csv in c:\myFolder, it also override the other files myFile2.csv and myFile3.csv that were not changed.

So, when I execute COPY INTO, it loads the data for myFile2.csv and myFile3.csv again, which I do not want to do. I only want to load data for files that are changed, in this case myFile1.csv.

COPY INTO MYCSVTABLE
FROM @my_csv_stage
FILE_FORMAT = (FORMAT_NAME = mycsvformat)
PATTERN = '.*myFile.*[.]CSV.gz'
ON_ERROR = 'skip_file';

Thank you

You need to use OVERWRITE = TRUE, as explained in the documentation for the PUT command.

I’m not sure on what basis you thought “the put command will put the file if the checksum is different” as this is not mentioned in the documentation?

Same points as NickW notes:

https://docs.snowflake.com/en/sql-reference/sql/put

> OVERWRITE = TRUE | FALSE
Specifies whether Snowflake overwrites an existing file with the same name during upload:
>
> TRUE: An existing file with the same name is overwritten.
>
>FALSE: An existing file with the same name is not overwritten.
>
>Note that a LIST operation on the stage is performed in the background, which can affect the performance of the PUT operation.
>
>If attempts to PUT a file fail because a file with the same name exists in the target stage, the following options are available:
>
>Load the data from the existing file into one or more tables, and remove the file from the stage. Then PUT a file with new or updated data to the stage.
>
>Rename the local file, and then attempt the PUT operation again.
>
> Set OVERWRITE = TRUE in the PUT statement. Do this only if it is actually safe to overwrite a file with data that might not yet have been loaded into Snowflake.
>
> Note that if your Snowflake account is hosted on Google Cloud Platform, PUT statements do not recognize when the OVERWRITE parameter is set to TRUE. A PUT operation always overwrites any existing files in the target stage with the local files you are uploading.
>
>The following clients support the OVERWRITE option for Snowflake accounts hosted on Amazon Web Services or Microsoft Azure:
>
>SnowSQL
>
>Snowflake ODBC Driver
>
>Snowflake JDBC Driver
>
>Snowflake Connector for Python
>
>Supported values: TRUE, FALSE.
>
>Default: FALSE.

but the Usage Notes section does say:

>The command ignores any duplicate files you attempt to upload to the same stage. A duplicate file is an unmodified file with the same name as an already-staged file.
>
>To overwrite an already-staged file, you must modify the file you are uploading so that its contents are different from the staged file, which results in a new checksum for the newly-staged file.

So this does imply there is checksums created, but it also possible interplays with the OVERRIDE option.