Franklyn Dsouza created SPARK-19299:
---------------------------------------

             Summary: Nulls in non nullable columns causes data corruption in 
parquet
                 Key: SPARK-19299
                 URL: https://issues.apache.org/jira/browse/SPARK-19299
             Project: Spark
          Issue Type: Bug
          Components: PySpark, Spark Core
    Affects Versions: 2.1.0, 2.0.2, 2.0.1, 2.0.0, 1.6.0
            Reporter: Franklyn Dsouza


The problem we're seeing is that if a null occurs in a no-nullable field and is 
written down to parquet the resulting file gets corrupt and can not be read 
back correctly.

One way that this can occur is when a long value in python is too big to fit 
into a spark LongType it gets cast to null. 

We're also seeing that the behaviour is slightly different depending on whether 
or not the vectorized reader is enabled.

Here's an example in PySpark

{code}
from datetime import datetime
from pyspark.sql import types

data = [
  (1, 6),
  (2, 7),
  (3, 2 ** 64),
  (4, 8),
  (5, 9)
]

schema = types.StructType([
  types.StructField("index", types.LongType(), False),
  types.StructField("long", types.LongType(), False),
])

df = sc.sql.createDataFrame(data, schema)

df.collect()

df.write.parquet("corrupt_parquet")

df_parquet = sqlCtx.read.parquet("corrupt_parquet/*.parquet")

df_parquet.collect()
{code}

with the vectorized reader on this causes

{code}
In [2]: df.collect()
Out[2]:
[Row(index=1, long=6),
 Row(index=2, long=7),
 Row(index=3, long=None),
 Row(index=4, long=8),
 Row(index=5, long=9)]

In [3]: df_parquet.collect()
Out[3]:
[Row(index=1, long=6),
 Row(index=2, long=7),
 Row(index=3, long=8),
 Row(index=4, long=9),
 Row(index=5, long=5)]
{code}

as you can see reading the data back from disk causes data to get shifted up 
and between columns.

with vectorized reader off we are completely unable to read the file.

{code}
Py4JJavaError: An error occurred while calling o143.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in 
stage 3.0 failed 1 times, most recent failure: Lost task 0.0 in stage 3.0 (TID 
3, localhost): org.apache.parquet.io.ParquetDecodingException: Can not read 
value at 4 in block 0 in file 
file:/Users/franklyndsouza/dev/starscream/corrupt/part-r-00000-4fa5aee8-2138-4e0c-b6d8-22a418d90fd3.snappy.parquet
        at 
org.apache.parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:228)
        at 
org.apache.parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:201)
        at 
org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:39)
        at 
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:91)
        at 
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
 Source)
        at 
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at 
org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
        at 
org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
        at 
org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
        at 
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
        at 
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
        at 
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
        at org.apache.spark.scheduler.Task.run(Task.scala:86)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.parquet.io.ParquetDecodingException: Can't read value in 
column [long] INT64 at value 5 out of 5, 5 out of 5 in currentPage. repetition 
level: 0, definition level: 0
        at 
org.apache.parquet.column.impl.ColumnReaderImpl.readValue(ColumnReaderImpl.java:462)
        at 
org.apache.parquet.column.impl.ColumnReaderImpl.writeCurrentValueToConverter(ColumnReaderImpl.java:364)
        at 
org.apache.parquet.io.RecordReaderImplementation.read(RecordReaderImplementation.java:405)
        at 
org.apache.parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:209)
        ... 19 more
Caused by: org.apache.parquet.io.ParquetDecodingException: could not read long
        at 
org.apache.parquet.column.values.plain.PlainValuesReader$LongPlainValuesReader.readLong(PlainValuesReader.java:131)
        at 
org.apache.parquet.column.impl.ColumnReaderImpl$2$4.read(ColumnReaderImpl.java:258)
        at 
org.apache.parquet.column.impl.ColumnReaderImpl.readValue(ColumnReaderImpl.java:458)
        ... 22 more
Caused by: java.io.EOFException
        at 
org.apache.parquet.bytes.LittleEndianDataInputStream.readFully(LittleEndianDataInputStream.java:90)
        at 
org.apache.parquet.bytes.LittleEndianDataInputStream.readLong(LittleEndianDataInputStream.java:377)
        at 
org.apache.parquet.column.values.plain.PlainValuesReader$LongPlainValuesReader.readLong(PlainValuesReader.java:129)
{code}



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