Sergey Rubtsov created SPARK-19228:
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Summary: inferSchema function processed csv date column as string
and "dateFormat" DataSource option is ignored
Key: SPARK-19228
URL: https://issues.apache.org/jira/browse/SPARK-19228
Project: Spark
Issue Type: Bug
Components: Input/Output, SQL
Affects Versions: 2.1.0
Reporter: Sergey Rubtsov
I need to process user.csv like this:
{code}
id,project,started,ended
sergey.rubtsov,project0,12/12/2012,10/10/2015
{code}
When I add date format options:
{code}
Dataset<Row> users = spark.read().format("csv").option("mode",
"PERMISSIVE").option("header", "true")
.option("inferSchema",
"true").option("dateFormat", "dd/MM/yyyy").load("src/main/resources/user.csv");
users.printSchema();
{code}
expected scheme should be
{code}
root
|-- id: string (nullable = true)
|-- project: string (nullable = true)
|-- started: date (nullable = true)
|-- ended: date (nullable = true)
{code}
but the actual result is:
{code}
root
|-- id: string (nullable = true)
|-- project: string (nullable = true)
|-- started: string (nullable = true)
|-- ended: string (nullable = true)
This mean that date processed as string and "dateFormat" option is ignored and
date processed as string.
If I add option
{code}
.option("timestampFormat", "dd/MM/yyyy")
{code}
result is:
{code}
root
|-- id: string (nullable = true)
|-- project: string (nullable = true)
|-- started: timestamp (nullable = true)
|-- ended: timestamp (nullable = true)
{code}
I think, the issue is somewhere in object CSVInferSchema, function inferField,
lines 80-97 and
method "tryParseDate" need to be added before/after "tryParseTimestamp", or
date/timestamp process logic need to be changed.
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