Can you try once by creating your own schema file and using it to read the XML.
I had similar issue but got that resolved by custom schema and by specifying each attribute in that. Pradeep > On May 1, 2016, at 9:45 AM, Hyukjin Kwon <gurwls...@gmail.com> wrote: > > To be more clear, > > If you set the rowTag as "book", then it will produces an exception which is > an issue opened here, https://github.com/databricks/spark-xml/issues/92 > > Currently it does not support to parse a single element with only a value as > a row. > > > If you set the rowTag as "bkval", then it should work. I tested the case > below to double check. > > If it does not work as below, please open an issue with some information so > that I can reproduce. > > > I tested the case above with the data below > <root> > <bkval> > <book id="bk113">bk_113</book> > <book id="bk114">bk_114</book> > </bkval> > <bkval> > <book id="bk114">bk_114</book> > <book id="bk115">bk_116</book> > </bkval> > <bkval> > <book id="bk116">bk_115</book> > <book id="bk117">bk_116</book> > </bkval> > </root> > > > I tested this with the codes below > > val path = "path-to-file" > sqlContext.read > .format("xml") > .option("rowTag", "bkval") > .load(path) > .show() > > Thanks! > > > 2016-05-01 15:11 GMT+09:00 Hyukjin Kwon <gurwls...@gmail.com>: >> Hi Sourav, >> >> I think it is an issue. XML will assume the element by the rowTag as object. >> >> Could you please open an issue in >> https://github.com/databricks/spark-xml/issues please? >> >> Thanks! >> >> >> 2016-05-01 5:08 GMT+09:00 Sourav Mazumder <sourav.mazumde...@gmail.com>: >>> Hi, >>> >>> Looks like there is a problem in spark-xml if the xml has multiple >>> attributes with no child element. >>> >>> For example say the xml has a nested object as below >>> <bkval> >>> <book id="bk113">bk_113</book> >>> <book id="bk114">bk_114</book> >>> </bkval> >>> >>> Now if I create a dataframe starting with rowtag bkval and then I do a >>> select on that data frame it gives following error. >>> >>> >>> scala.MatchError: ENDDOCUMENT (of class >>> com.sun.xml.internal.stream.events.EndDocumentEvent) at >>> com.databricks.spark.xml.parsers.StaxXmlParser$.checkEndElement(StaxXmlParser.scala:94) >>> at >>> com.databricks.spark.xml.parsers.StaxXmlParser$.com$databricks$spark$xml$parsers$StaxXmlParser$$convertObject(StaxXmlParser.scala:295) >>> at >>> com.databricks.spark.xml.parsers.StaxXmlParser$$anonfun$parse$1$$anonfun$apply$4.apply(StaxXmlParser.scala:58) >>> at >>> com.databricks.spark.xml.parsers.StaxXmlParser$$anonfun$parse$1$$anonfun$apply$4.apply(StaxXmlParser.scala:46) >>> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) at >>> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) at >>> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) at >>> scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308) at >>> scala.collection.Iterator$class.foreach(Iterator.scala:727) at >>> scala.collection.AbstractIterator.foreach(Iterator.scala:1157) at >>> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) at >>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) >>> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) >>> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) at >>> scala.collection.AbstractIterator.to(Iterator.scala:1157) at >>> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) >>> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) at >>> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) >>> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:215) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:215) >>> at >>> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850) >>> at >>> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850) >>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) at >>> org.apache.spark.scheduler.Task.run(Task.scala:88) at >>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) at >>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) >>> at >>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) >>> at java.lang.Thread.run(Thread.java:745) >>> >>> However if there is only one row like below, it works fine. >>> >>> <bkval> >>> <book id="bk113">bk_113</book> >>> </bkval> >>> >>> Any workaround ? >>> >>> Regards, >>> Sourav >
