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Posted to issues@spark.apache.org by "Ruslan Dautkhanov (JIRA)" <ji...@apache.org> on 2017/09/12 05:42:00 UTC
[jira] [Created] (SPARK-21978) schemaInference option not to
convert strings with leading zeros to int/long
Ruslan Dautkhanov created SPARK-21978:
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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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