I have a local csv file having table name as market_date_info. One of the column in this table is market_date. The date is in DD-MM-YYYY format. Below are first 5 rows of the column shown in attached picture. I have taken only 5 rows just for the sake of simplicity.
First_5_rows_of_csv
I uploaded this csv file table on google Big Query by selecting schema Auto Detect. It changed the date format to default YYYY-MM-DD. The uploaded table is shown in the following attached picture. Table_in_bigQuery
Everything is Okay. The table got uploaded as expected. But I have following query:
How does BigQuery decides that in the original csv file format i.e. DD-MM-YYYY which value is for date , and which value is for month? Suppose there is a date 02-03-1999. Here in this 02 can represent a month also. How does bigquery know that 02 is day not a month?
Suppose in the csv or txt file, the date format is MM-DD-YYYY. For eg 3rd Feb,1999 is represented as 02-03-1999. Will Big query still be able to detect that 02 is for month and 03 is for date. Will Bigquery successfully convert it to YYYY-MM-DD format?
What is the underlying process by which Bigquery decides that a value is a day or a month?