Hi I have a bunch of CSV's located in S3, a crawler setup via AWS Glue, this crawler builds about 10 tables as it scan 10 folders and only 1 of them where the headers are not being detected. The structure of the csv is the same as all the others. Advice please?
You can create the table yourself and instead of crawling point to an s3 path, you can crawl based on an existing table. This is the concept used when a crawler is not detecting the schema especially just column headings.
Also check if the skip.header.line.count=1 is being added automatically, if not you can add manually and it an update the schema to the correct one you require. On your subsequent runs for your crawler, you can change the properties so that it will ignore schema updates and only perform partition updates to your table.
AWs glue crawler interprets header based on multiple rules. if the first line in your file doest satisfy those rules, the crawler wont detect the fist line as a header and you will need to do that manually. its a very common problem and we integrated a fix for this within our code to do it is part of our data pipeline.
Excerpt from aws doco
To be classified as CSV, the table schema must have at least two columns and two rows of data. The CSV classifier uses a number of heuristics to determine whether a header is present in a given file. If the classifier can't determine a header from the first row of data, column headers are displayed as col1, col2, col3, and so on. The built-in CSV classifier determines whether to infer a header by evaluating the following characteristics of the file:
Every column in a potential header parses as a STRING data type.
Except for the last column, every column in a potential header has content that is fewer than 150 characters. To allow for a trailing delimiter, the last column can be empty throughout the file.
Every column in a potential header must meet the AWS Glue regex requirements for a column name.
The header row must be sufficiently different from the data rows. To determine this, one or more of the rows must parse as other than STRING type. If all columns are of type STRING, then the first row of data is not sufficiently different from subsequent rows to be used as the header.
You can create the table yourself and instead of crawling point to an s3 path, you can crawl based on an existing table. This is the concept used when a crawler is not detecting the schema especially just column headings.
Also check if the skip.header.line.count=1 is being added automatically, if not you can add manually and it an update the schema to the correct one you require. On your subsequent runs for your crawler, you can change the properties so that it will ignore schema updates and only perform partition updates to your table.
You could use a custom classifier on your crawler to solve this problem: https://docs.aws.amazon.com/glue/latest/dg/custom-classifier.html
Normally choosing Has headings in the classifier options Column Headings section will do the trick, if not, it may be necessary to enter in a list of headings in text box for that purpose.
because your columns are all classified as strings, it's likely that the columns violate the rules. in my case, i had a column name that was greater than 150 characters so Glue read the first row as data, as opposed to a header, and then assumed all columns were strings.
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