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From "Ruslan Dautkhanov (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-21978) schemaInference option not to convert strings with leading zeros to int/long
Date Tue, 12 Sep 2017 05:42:00 GMT
Ruslan Dautkhanov created SPARK-21978:
-----------------------------------------

             Summary: schemaInference option not to convert strings with leading zeros to
int/long 
                 Key: SPARK-21978
                 URL: https://issues.apache.org/jira/browse/SPARK-21978
             Project: Spark
          Issue Type: Improvement
          Components: Spark Core
    Affects Versions: 2.2.0, 2.1.1, 2.1.0, 2.3.0
            Reporter: Ruslan Dautkhanov


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.

{code}
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')
            )
{code}



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