[SPARK-21978] schemaInference option not to convert strings with leading zeros to int/long

• Type: Improvement
• Status: Resolved
• Priority: Major
• Resolution: Won't Fix
• Affects Version/s: 2.1.0, 2.1.1, 2.2.0, 2.3.0
• Component/s: Spark Core
• Labels: csv csvparser easy-fix inference ramp-up schema
• Assignee: Unassigned
• Reporter: Ruslan Dautkhanov
• Created: 12/Sep/17 05:41
• Updated: 12/Dec/22 18:11
• Resolved: 11/Oct/17 14:47

Description

It would be great to have an option in Spark's schema inference to not to convert to int/long datatype a column that has leading zeros. Think zip codes, for example.

df = (sqlc.read.format('csv')
              .option('inferSchema', True)
              .option('header', True)
              .option('delimiter', '|')
              .option('leadingZeros', 'KEEP')       # this is the new proposed option
              .option('mode', 'FAILFAST')
              .load('csvfile_withzipcodes_to_ingest.csv')
            )

Issue Links

• is cloned by: SPARK-29316 CLONE - schemaInference option not to convert strings with leading zeros to int/long