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Posted to issues@spark.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2018/12/18 10:03:00 UTC
[jira] [Commented] (SPARK-26384) CSV schema inferring does not
respect spark.sql.legacy.timeParser.enabled
[ https://issues.apache.org/jira/browse/SPARK-26384?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16723886#comment-16723886 ]
ASF GitHub Bot commented on SPARK-26384:
----------------------------------------
MaxGekk opened a new pull request #23345: [SPARK-26384][SQL] Propagate SQL configs for CSV schema inferring
URL: https://github.com/apache/spark/pull/23345
## What changes were proposed in this pull request?
Currently, SQL configs are not propagated to executors while schema inferring in CSV datasource. For example, changing of `spark.sql.legacy.timeParser.enabled` does not impact on inferring timestamp types. In the PR, I propose to fix the issue by wrapping schema inferring action using `SQLExecution.withSQLConfPropagated`.
## How was this patch tested?
Added logging to `TimestampFormatter`:
```patch
-object TimestampFormatter {
+object TimestampFormatter extends Logging {
def apply(format: String, timeZone: TimeZone, locale: Locale): TimestampFormatter = {
if (SQLConf.get.legacyTimeParserEnabled) {
+ logError("LegacyFallbackTimestampFormatter is being used")
new LegacyFallbackTimestampFormatter(format, timeZone, locale)
} else {
+ logError("Iso8601TimestampFormatter is being used")
new Iso8601TimestampFormatter(format, timeZone, locale)
}
}
```
and run the command in `spark-shell`:
```shell
$ ./bin/spark-shell --conf spark.sql.legacy.timeParser.enabled=true
```
```scala
scala> Seq("2010|10|10").toDF.repartition(1).write.mode("overwrite").text("/tmp/foo")
scala> spark.read.option("inferSchema", "true").option("header", "false").option("timestampFormat", "yyyy|MM|dd").csv("/tmp/foo").printSchema()
18/12/18 10:47:27 ERROR TimestampFormatter: LegacyFallbackTimestampFormatter is being used
root
|-- _c0: timestamp (nullable = true)
```
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> CSV schema inferring does not respect spark.sql.legacy.timeParser.enabled
> -------------------------------------------------------------------------
>
> Key: SPARK-26384
> URL: https://issues.apache.org/jira/browse/SPARK-26384
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Maxim Gekk
> Priority: Major
>
> Starting from the commit [https://github.com/apache/spark/commit/f982ca07e80074bdc1e3b742c5e21cf368e4ede2] , add logging like in the comment https://github.com/apache/spark/pull/23150#discussion_r242021998 and run:
> {code:shell}
> $ ./bin/spark-shell --conf spark.sql.legacy.timeParser.enabled=true
> {code}
> and in the shell:
> {code:scala}
> scala> spark.conf.get("spark.sql.legacy.timeParser.enabled")
> res0: String = true
> scala> Seq("2010|10|10").toDF.repartition(1).write.mode("overwrite").text("/tmp/foo")
> scala> spark.read.option("inferSchema", "true").option("header", "false").option("timestampFormat", "yyyy|MM|dd").csv("/tmp/foo").printSchema()
> 18/12/17 12:11:47 ERROR TimestampFormatter: Iso8601TimestampFormatter is being used
> root
> |-- _c0: timestamp (nullable = true)
> {code}
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