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https://issues.apache.org/jira/browse/SPARK-14223?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-14223:
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Assignee: (was: Apache Spark)
> Cannot project all columns from a parquet files with ~1,100 columns
> -------------------------------------------------------------------
>
> Key: SPARK-14223
> URL: https://issues.apache.org/jira/browse/SPARK-14223
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Hossein Falaki
> Priority: Critical
> Attachments: 1000genomes.gz.parquet
>
>
> The parquet file is generated by saving first 10 rows of the 1000 genomes
> dataset. When I try to run "select * from" a temp table created from the file
> I get following error:
> {code}
> val vcfData = sqlContext.read.format("csv").options(Map(
> "comment" -> "#", "header" -> "false", "delimiter" -> "\t"
> )).load("/1000genomes/phase1/analysis_results/integrated_call_sets/ALL.chr1.integrated_phase1_v3.20101123.snps_indels_svs.genotypes.vcf")
> data.registerTempTable("genomesTable")
> sql("select * from genomesTable limit
> 10").write.format("parquet").save("/tmp/test-genome.parquet")
> sqlContext.read.format("parquet").load("/tmp/test-genome.parquet").registerTempTable("parquetTable")
> %sql select * from parquetTable
> SparkException: Job aborted due to stage failure: Task 0 in stage 31.0 failed
> 4 times, most recent failure: Lost task 0.3 in stage 31.0 (TID 4695,
> ip-10-0-251-144.us-west-2.compute.internal): java.lang.ClassCastException:
> org.apache.spark.sql.execution.vectorized.ColumnarBatch cannot be cast to
> org.apache.spark.sql.catalyst.InternalRow
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
> Source)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$3.apply(SparkPlan.scala:237)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$3.apply(SparkPlan.scala:230)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$23.apply(RDD.scala:772)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$23.apply(RDD.scala:772)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:282)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:69)
> at org.apache.spark.scheduler.Task.run(Task.scala:82)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:231)
> 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)
> {code}
> cc [~rxin]
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