Hari Sekhon created HIVE-11558:
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Summary: Hive generates Parquet files with broken footers, causes
NullPointerException in Spark / Drill / Parquet tools
Key: HIVE-11558
URL: https://issues.apache.org/jira/browse/HIVE-11558
Project: Hive
Issue Type: Bug
Components: File Formats, StorageHandler
Affects Versions: 1.2.1
Environment: HDP 2.3
Reporter: Hari Sekhon
Priority: Critical
When creating a Parquet table in Hive from a table in another format (in this
case JSON) using CTAS, the generated parquet files are created with broken
footers and cause NullPointerExceptions in both Parquet tools and Spark when
reading the files directly.
Here is the error from parquet tools:
{code}Could not read footer: java.lang.NullPointerException{code}
Here is the error from Spark reading the parquet file back:
{code}java.lang.NullPointerException
at
parquet.format.converter.ParquetMetadataConverter.fromParquetStatistics(ParquetMetadataConverter.java:249)
at
parquet.format.converter.ParquetMetadataConverter.fromParquetMetadata(ParquetMetadataConverter.java:543)
at
parquet.format.converter.ParquetMetadataConverter.readParquetMetadata(ParquetMetadataConverter.java:520)
at
parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:426)
at
org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$refresh$6.apply(newParquet.scala:298)
at
org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$refresh$6.apply(newParquet.scala:297)
at
scala.collection.parallel.mutable.ParArray$Map.leaf(ParArray.scala:658)
at
scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:54)
at
scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:53)
at
scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:53)
at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:56)
at
scala.collection.parallel.mutable.ParArray$Map.tryLeaf(ParArray.scala:650)
at
scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:165)
at
scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:514)
at
scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at
scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
{code}
What's interesting is that the table works fine in Hive when selecting out of
it, even when doing select * on the whole table and letting it run, it's only
other tools it causes problems for.
All fields are string exception for the first one which is timestamp, but this
is not that known issue since if I create another table with 3 fields including
the timestamp and two string fields it works fine in other tools.
The only thing I can see which appears to cause this is the other fields have
lots of NULLs in them as those json fields may or may not be present.
I've converted this exact same json data set to parquet using Apache Drill and
also using Apache SparkSQL and both of those tools create parquet files from
this data set as a straight conversion that are fine when accessed via Parquet
tools or Drill or Spark or Hive (using an external Hive table definition
layered over the generated parquet files).
This implies that it's Hive's generation of Parquet that is broken since both
Drill and Spark can convert the dataset from JSON to Parquet without any issues
on reading the files back in any of other tools.
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