apache / apache/parquet-java

Cannot read row group larger than 2GB

Aperta
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Component: Java Component: Parquet Priority: Major Type: bug
Lingua principale
Java
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Descrizione

Parquet MR 1.8.2 does not support reading row groups which are larger than 2 GB. See:https://github.com/apache/parquet-mr/blob/parquet-1.8.x/parquet-hadoop/src/main/java/org/apache/parquet/hadoop/ParquetFileReader.java#L1064

We are seeing this when writing skewed records. This throws off the estimation of the memory check interval in the InternalParquetRecordWriter. The following spark code illustrates this:
```
/**
* Create a data frame that will make parquet write a file with a row group larger than 2 GB. Parquet
* only checks the size of the row group after writing a number of records. This number is based on
* average row size of the already written records. This is problematic in the following scenario:
* - The initial (100) records in the record group are relatively small.
* - The InternalParquetRecordWriter checks if it needs to write to disk (it should not), it assumes
* that the remaining records have a similar size, and (greatly) increases the check interval (usually
* to 10000).
* - The remaining records are much larger then expected, making the row group larger than 2 GB (which
* makes reading the row group impossible).
*
* The data frame below illustrates such a scenario. This creates a row group of approximately 4GB.
*/
val badDf = spark.range(0, 2200, 1, 1).mapPartitions { iterator =>
var i = 0
val random = new scala.util.Random(42)
val buffer = new Array[Char](750000)
iterator.map { id =>
// the first 200 records have a length of 1K and the remaining 2000 have a length of 750K.
val numChars = if (i < 200) 1000 else 750000
i += 1

// create a random array
var j = 0
while (j < numChars) {
// Generate a char (borrowed from scala.util.Random)
buffer(j) = (random.nextInt(0xD800 - 1) + 1).toChar
j += 1
}

// create a string: the string constructor will copy the buffer.
new String(buffer, 0, numChars)
}
}
badDf.write.parquet("somefile")
val corruptedDf = spark.read.parquet("somefile")
corruptedDf.select(count(lit(1)), max(length($"value"))).show()
```
The latter fails with the following exception:
```
java.lang.NegativeArraySizeException
at org.apache.parquet.hadoop.ParquetFileReader$ConsecutiveChunkList.readAll(ParquetFileReader.java:1064)
at org.apache.parquet.hadoop.ParquetFileReader.readNextRowGroup(ParquetFileReader.java:698)
...
```

-This seems to be fixed by commit https://github.com/apache/parquet-mr/commit/6b605a4ea05b66e1a6bf843353abcb4834a4ced8 in parquet 1.9.x. Is there any chance that we can fix this in 1.8.x?-

**Reporter**: [Herman van Hövell](https://issues.apache.org/jira/secure/ViewProfile.jspa?name=hvanhovell)

**Note**: *This issue was originally created as [PARQUET-980](https://issues.apache.org/jira/browse/PARQUET-980). Please see the [migration documentation](https://issues.apache.org/jira/browse/PARQUET-2502) for further details.*

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Direzione di ricerca

Iniziate da parquet-hadoop/src/main/java/org/apache/parquet/hadoop/ParquetFileReader.java alla riga 1064 e confrontate il comportamento con il commit 6b605a4ea05b66e1a6bf843353abcb4834a4ced8. Riproducete il problema usando l'esempio Spark nel report, quindi verificate che parquet 1.8.x possa leggere il row group risultante senza NegativeArraySizeException.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
java, scala
Ambito
data-engineering
Tipo di issue
Bug
Difficoltà
4/5
Tempo stimato
3-5 giorni
Stato di attività
Ferma
Chiarezza
Specificata chiaramente
Idoneità per principianti
35/100

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