Willi Raschkowski created SPARK-35324:
-----------------------------------------
Summary: Time parser policy not respected in RDD
Key: SPARK-35324
URL: https://issues.apache.org/jira/browse/SPARK-35324
Project: Spark
Issue Type: Task
Components: Input/Output
Affects Versions: 3.1.1, 3.0.2
Reporter: Willi Raschkowski
When reading a CSV file, {{spark.sql.timeParserPolicy}} is respected in actions
on the resulting dataframe. But it's ignored in actions on dataframe's RDD.
E.g. say to parse dates in a CSV you need {{spark.sql.timeParserPolicy}} to be
set to {{LEGACY}}. If you set the config, {{df.count}} will work as you'd
expect. However, {{df.count.rdd}} will fail because it'll ignore the override
and read the config value as {{EXCEPTION}}.
For instance:
{code:java|title=test.csv}
date
2/6/18
{code}
{code:java}
scala> spark.conf.set("spark.sql.legacy.timeParserPolicy", "legacy")
scala> val df = {
| spark.read
| .option("header", "true")
| .option("dateFormat", "MM/dd/yy")
| .schema("date date")
| .csv("/Users/wraschkowski/Downloads/test.csv")
| }
df: org.apache.spark.sql.DataFrame = [date: date]
scala> df.show
+----------+
| date|
+----------+
|2018-02-06|
+----------+
scala> df.count
res3: Long = 1
scala> df.rdd.count
21/05/06 00:06:18 ERROR Executor: Exception in task 0.0 in stage 4.0 (TID 4)
org.apache.spark.SparkUpgradeException: You may get a different result due to
the upgrading of Spark 3.0: Fail to parse '2/6/18' in the new parser. You can
set spark.sql.legacy.timeParserPolicy to LEGACY to restore the behavior before
Spark 3.0, or set to CORRECTED and treat it as an invalid datetime string.
at
org.apache.spark.sql.catalyst.util.DateTimeFormatterHelper$$anonfun$checkParsedDiff$1.applyOrElse(DateTimeFormatterHelper.scala:150)
at
org.apache.spark.sql.catalyst.util.DateTimeFormatterHelper$$anonfun$checkParsedDiff$1.applyOrElse(DateTimeFormatterHelper.scala:141)
at
scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
at
org.apache.spark.sql.catalyst.util.Iso8601DateFormatter.$anonfun$parse$1(DateFormatter.scala:61)
at
scala.runtime.java8.JFunction0$mcI$sp.apply(JFunction0$mcI$sp.java:23)
at scala.Option.getOrElse(Option.scala:189)
at
org.apache.spark.sql.catalyst.util.Iso8601DateFormatter.parse(DateFormatter.scala:58)
at
org.apache.spark.sql.catalyst.csv.UnivocityParser.$anonfun$makeConverter$21(UnivocityParser.scala:202)
at
org.apache.spark.sql.catalyst.csv.UnivocityParser.nullSafeDatum(UnivocityParser.scala:238)
at
org.apache.spark.sql.catalyst.csv.UnivocityParser.$anonfun$makeConverter$20(UnivocityParser.scala:200)
at
org.apache.spark.sql.catalyst.csv.UnivocityParser.org$apache$spark$sql$catalyst$csv$UnivocityParser$$convert(UnivocityParser.scala:291)
at
org.apache.spark.sql.catalyst.csv.UnivocityParser.$anonfun$parse$2(UnivocityParser.scala:254)
at
org.apache.spark.sql.catalyst.csv.UnivocityParser$.$anonfun$parseIterator$1(UnivocityParser.scala:396)
at
org.apache.spark.sql.catalyst.util.FailureSafeParser.parse(FailureSafeParser.scala:60)
at
org.apache.spark.sql.catalyst.csv.UnivocityParser$.$anonfun$parseIterator$2(UnivocityParser.scala:400)
at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:93)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:173)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:93)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1866)
at org.apache.spark.rdd.RDD.$anonfun$count$1(RDD.scala:1253)
at org.apache.spark.rdd.RDD.$anonfun$count$1$adapted(RDD.scala:1253)
at
org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2242)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at
java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at
java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.time.format.DateTimeParseException: Text '2/6/18' could not be
parsed at index 0
at
java.base/java.time.format.DateTimeFormatter.parseResolved0(DateTimeFormatter.java:2046)
at
java.base/java.time.format.DateTimeFormatter.parse(DateTimeFormatter.java:1874)
at
org.apache.spark.sql.catalyst.util.Iso8601DateFormatter.$anonfun$parse$1(DateFormatter.scala:59)
... 32 more
{code}
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
