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From jeff saremi <jeffsar...@hotmail.com>
Subject Re: Continue reading dataframe from file despite errors
Date Tue, 12 Sep 2017 22:32:42 GMT
thanks Suresh. it worked nicely

________________________________
From: Suresh Thalamati <suresh.thalamati@gmail.com>
Sent: Tuesday, September 12, 2017 2:59:29 PM
To: jeff saremi
Cc: user@spark.apache.org
Subject: Re: Continue reading dataframe from file despite errors

Try the CSV   Option(“mode”,  "dropmalformed”), that might skip the error records.


On Sep 12, 2017, at 2:33 PM, jeff saremi <jeffsaremi@hotmail.com<mailto:jeffsaremi@hotmail.com>>
wrote:

should have added some of the exception to be clear:

17/09/12 14:14:17 ERROR TaskSetManager: Task 0 in stage 15.0 failed 1 times; aborting job
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 15.0 failed
1 times, most recent failure: Lost task 0.0 in stage 15.0 (TID 15, localhost, executor driver):
java.lang.NumberFormatException: For input string: "south carolina"
        at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
        at java.lang.Integer.parseInt(Integer.java:580)
        at java.lang.Integer.parseInt(Integer.java:615)
        at scala.collection.immutable.StringLike$class.toInt(StringLike.scala:272)
        at scala.collection.immutable.StringOps.toInt(StringOps.scala:29)
        at org.apache.spark.sql.execution.datasources.csv.CSVTypeCast$.castTo(CSVInferSchema.scala:250)


________________________________
From: jeff saremi <jeffsaremi@hotmail.com<mailto:jeffsaremi@hotmail.com>>
Sent: Tuesday, September 12, 2017 2:32:03 PM
To: user@spark.apache.org<mailto:user@spark.apache.org>
Subject: Continue reading dataframe from file despite errors

I'm using a statement like the following to load my dataframe from some text file
Upon encountering the first error, the whole thing throws an exception and processing stops.
I'd like to continue loading even if that results in zero rows in my dataframe. How can i
do that?
thanks

spark.read.schema(SomeSchema).option("sep", "\t").format("csv").load("somepath")


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